WO2025217419A1

WO2025217419A1 - Methods for channel parameter estimation

Info

Publication number: WO2025217419A1
Application number: PCT/US2025/024101
Authority: WO
Inventors: Akshay Malhotra; Yugeswar Deenoo NARAYANAN THANGARAJ; Shahab Hamidi-Rad; Mihaela Beluri; Mohamed Salah IBRAHIM; Akshay Kumar
Original assignee: InterDigital Patent Holdings Inc
Current assignee: InterDigital Patent Holdings Inc
Priority date: 2024-04-11
Filing date: 2025-04-10
Publication date: 2025-10-16
Anticipated expiration: 2026-10-11

Abstract

A WTRU may receive configuration information indicating of a set of channel parameters associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and/or second criteria associated with reporting. The WTRU may determine a first subset of the plurality of paths. The first set of channel parameters may be associated with a first time period. The WTRU may determine one or more values of predicted channel parameters for each path of the first subset of paths. The one or more values of the predicted channel parameters may be associated with a second time period. The WTRU may determine a second subset of the plurality of paths. The WTRU may send an indication that indicates the one or more values of the predicted channel parameters associated with the second subset of the plurality of paths.

Description

METHODS FOR CHANNEL PARAMETER ESTIMATION

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to United States Provisional Patent Application No. 63/632,859 filed in the United States of America on April 11, 2024, the entire contents of which are incorporated herein by reference.

BACKGROUND

[0002] Multiple input multiple output (MIMO) channel state information (CSI) prediction may include prediction of the codebook-based precoding matrix indicator (PMI). Artificial intelligence (Al) / machine learning (ML) CSI prediction may include the prediction of channel matrix and/or eigen vectors.

SUMMARY

[0003] Methods for parameterizing channel into low dimensional explainable components may be described herein. A WTRU may be configured to decompose the channel estimates into parameters, for example, based on preconfigured criteria, and/or may predict future values of these parameters and/or may report to the network. Methods for model selection for channel state information (CSI) compression based on low dimensional channel parameter estimation, including conditions and/or mechanisms for model free reporting may be described herein. Methods for CSI feedback performance monitoring, where the WTRU may be configured to report a subset of low dimensional channel parameters along with compressed CSI to enable performance monitoring may be described herein.

[0004] A wireless transmit/receive unit (WTRU) may receive configuration information associated with channel parameters to be determined and/or reported. The WTRU may receive channel state information - reference signals (CSI-RSs). The WTRU may perform channel estimation. The WTRU may determine a first set of channel parameters for a first set of paths using first criteria. The WTRU may determine a second set of channel parameters for a second set of paths using second criteria. The WTRU may determine the set of paths and/or the parameters associated with each of the paths forming the first set. The WTRU may determine the set of paths forming the second set of paths using the second criteria. The WTRU may send a report to a network node. The report may include the channel parameters and/or the paths included in the second set. [0005] The channel parameters may include one or more of: transmission path, angle of arrival (AoA), angle of departure (AoD), path gain, doppler range, and/or delay spread range.

The first set of channel parameters may be for a tracking set of paths. The first set of channel parameters may correspond to valid paths in the channel that are to be tracked. The WTRU may use the first criteria to determine the valid paths in a channel based on one or more of: maximum number of paths to be tracked, Angle of arrival (AoA) or angle of departure (AoD) is within a first range, and/or the gain is greater than a first threshold.

[0006] A WTRU may receive configuration information. The configuration information may include an indication of a set of channel parameters associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and/or second criteria associated with reporting. The WTRU may determine a first subset of the plurality of paths based on values of channel parameters associated with the first subset of the plurality of paths and/or the first criteria. The first set of channel parameters may be associated with a first time period. The WTRU may determine one or more values of predicted channel parameters for each path of the first subset of paths. The one or more values of the predicted channel parameters may be associated with a second time period. The second time period may be different from the first time period. The WTRU may determine a second subset of the plurality of paths based on the second criteria and/or the one or more values of the predicted channel parameters for each path of the first subset of paths. The second subset of paths may be a subset of the first subset of paths. The WTRU may send an indication that indicates the one or more values of the predicted channel parameters associated with the second subset of the plurality of paths.

[0007] The WTRU may determine one or more values of the channel parameters for each path of the plurality of paths. The WTRU may determine the first subset of the plurality of paths based on a comparison of the first criteria and the one or more values of the channel parameters for each path of the plurality of paths.

[0008] The WTRU may determine one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths. The WTRU may determine the second subset of the plurality of paths based on a comparison of the second criteria and the one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths.

[0009] The second time period may be concurrent with a periodicity associated with CSI-RS transmission. [0010] The WTRU may receive one or more CSI-RSs. The WTRU may determine the channel parameter(s) associated with the first subset of the plurality of paths based on the received CSI-RS(s). [0011] The WTRU may determine the prediction channel parameters, for example, based on the (e.g., first) criteria. The prediction channel parameters may be more than the measured channel parameters. The prediction channel parameters may be less than the measured channel parameters.

[0012] The WTRU may determine a subset of values associated with the second subset of the plurality of paths. The WTRU may send an indication that indicates the subset of values associated with the second subset of the plurality of paths to send the indication. The indication that indicates the one or more values of the predicted channel parameters may be and/or include a subset of one or more values of the predicted channel parameters associated with the second subset of the plurality of paths.

[0013] The plurality of paths may be fewer than a number of paths in a CSI matrix.

[0014] The (e.g., first) set of channel parameters may include one or more of: a transmission path, an angle of arrival (AoA), an angle of departure (AoD), a path gain, a doppler range, and/or a delay spread. [0015] The WTRU may update the first subset of paths of the plurality of paths or the second subset of paths of the plurality of paths based on one or more of: the first criteria, the second criteria, a time window during which the first criteria is evaluated, a configured prediction window, or an observation window length.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG. 1 A is a system diagram illustrating an example communications system in which one or more disclosed embodiments may be implemented.

[0017] FIG. 1 B is a system diagram illustrating an example wireless transmit/receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1A according to an embodiment.

[0018] FIG. 1C is a system diagram illustrating an example radio access network (RAN) and an example core network (CN) that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0019] FIG. 1 D is a system diagram illustrating a further example RAN and a further example CN that may be used within the communications system illustrated in FIG. 1 A according to an embodiment.

[0020] FIG. 2 depicts an example of multiple channel state information (CSI) prediction framework.

[0021] FIG. 3 depicts an example of a high-level framework for orthogonal matching pursuit (OMP) based on channel parameter estimation.

[0022] FIG. 4 depicts a high-level framework for deep learning based channel parameter estimation.

[0023] FIG. 5 depicts an exemplary structure of the deep learning model used for multipath detection and/or multipath parameter regression. DETAILED DESCRIPTION

[0024] FIG. 1A is a diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented. The communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth. For example, the communications systems 100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), zero-tail unique-word DFT-Spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block-filtered OFDM, filter bank multicarrier (FBMC), and the like.

[0025] As shown in FIG. 1 A, the communications system 100 may include wireless transmit/receive units (WTRUs) 102a, 102b, 102c, 102d, a RAN 104/113, a CN 106/115, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and/or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and/or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d, any of which may be referred to as a “station” and/or a “ST A”, may be configured to transmit and/or receive wireless signals and may include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi-Fi device, an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts), a consumer electronics device, a device operating on commercial and/or industrial wireless networks, and the like. Any of the WTRUs 102a, 102b, 102c and 102d may be interchangeably referred to as a WTRU. Further, any description herein that is described with reference to a UE may be equally applicable to a WTRU (or vice versa). For example, a WTRU may be configured to perform any of the processes or procedures described herein as being performed by a UE (or vice versa). [0026] The communications systems 100 may also include a base station 114a and/or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communication networks, such as the CN 106/115, the I nternet 110, and/or the other networks 112. By way of example, the base stations 114a, 114b may be a base transceiver station (BTS), a Node-B, an eNode B, a Home Node B, a Home eNode B, a gNB, a NR NodeB, a site controller, an access point (AR), a wireless router, and the like. While the base stations 114a, 114b are each depicted as a single element, it will be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and/or network elements.

[0027] The base station 114a may be part of the RAN 104/113, which may also include other base stations and/or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 114a and/or the base station 114b may be configured to transmit and/or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum. A cell may provide coverage for a wireless service to a specific geographical area that may be relatively fixed or that may change over time. The cell may further be divided into cell sectors. For example, the cell associated with the base station 114a may be divided into three sectors. Thus, in one embodiment, the base station 114a may include three transceivers, i.e., one for each sector of the cell. In an embodiment, the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each sector of the cell. For example, beamforming may be used to transmit and/or receive signals in desired spatial directions.

[0028] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0029] More specifically, as noted above, the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, and the like. For example, the base station 114a in the RAN 104/113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 115/116/117 using wideband CDMA (WCDMA). WCDMA may include communication protocols such as High-Speed Packet Access (HSPA) and/or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink (DL) Packet Access (HSDPA) and/or High-Speed UL Packet Access (HSUPA).

[0030] I n an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and/or LTE-Advanced (LTE-A) and/or LTE-Advanced Pro (LTE-A Pro).

[0031 ] I n an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR Radio Access , which may establish the air interface 116 using New Radio (NR).

[0032] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for instance using dual connectivity (DC) principles. Thus, the air interface utilized by WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and/or transmissions sent to/from multiple types of base stations (e.g., a eNB and a gNB).

[0033] In other embodiments, the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.

[0034] The base station 114b in FIG. 1 A may be a wireless router, Home Node B, Home eNode B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a roadway, and the like. In one embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR etc.) to establish a picocell or femtocell. As shown in FIG. 1A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the CN 106/115.

[0035] The RAN 104/113 may be in communication with the CN 106/115, which may be any type of network configured to provide voice, data, applications, and/or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. The data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, and the like. The CN 106/115 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and/or perform high-level security functions, such as user authentication. Although not shown in FIG. 1A, it will be appreciated that the RAN 104/113 and/or the CN 106/115 may be in direct or indirect communication with other RANs that employ the same RAT as the RAN 104/113 or a different RAT. For example, in addition to being connected to the RAN 104/113, which may be utilizing a NR radio technology, the CN 106/115 may also be in communication with another RAN (not shown) employing a GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.

[0036] The CN 106/115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and/or the other networks 112. The PSTN 108 may include circuit- switched telephone networks that provide plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and/or the internet protocol (IP) in the TCP/IP internet protocol suite. The networks 112 may include wired and/or wireless communications networks owned and/or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104/113 or a different RAT.

[0037] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links). For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0038] FIG. 1 B is a system diagram illustrating an example WTRU 102. As shown in FIG. 1 B, the WTRU 102 may include a processor 118, a transceiver 120, a transmit/receive element 122, a speaker/microphone 124, a keypad 126, a display/touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and/or other peripherals 138, among others. It will be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0039] The processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. The processor 118 may perform signal coding, data processing, power control, input/output processing, and/or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit/receive element 122. While FIG. 1B depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0040] The transmit/receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116. For example, in one embodiment, the transmit/receive element 122 may be an antenna configured to transmit and/or receive RF signals. In an embodiment, the transmit/receive element 122 may be an emitter/detector configured to transmit and/or receive IR, UV, or visible light signals, for example. In yet another embodiment, the transmit/receive element 122 may be configured to transmit and/or receive both RF and light signals. It will be appreciated that the transmit/receive element 122 may be configured to transmit and/or receive any combination of wireless signals.

[0041] Although the transmit/receive element 122 is depicted in FIG. 1 B as a single element, the WTRU 102 may include any number of transmit/receive elements 122. More specifically, the WTRU 102 may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit/receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0042] The transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit/receive element 122 and to demodulate the signals that are received by the transmit/receive element 122. As noted above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as NR and IEEE 802.11, for example.

[0043] The processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128 (e.g., a liquid crystal display (LCD) display unit or organic light-emitting diode (OLED) display unit). The processor 118 may also output user data to the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128. In addition, the processor 118 may access information from, and store data in, any type of suitable memory, such as the non-removable memory 130 and/or the removable memory 132. The non-removable memory 130 may include random-access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0044] The processor 118 may receive power from the power source 134, and may be configured to distribute and/or control the power to the other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, and the like.

[0045] The processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or in lieu of, the information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 116 from a base station (e.g., base stations 114a, 114b) and/or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable locationdetermination method while remaining consistent with an embodiment.

[0046] The processor 118 may further be coupled to other peripherals 138, which may include one or more software and/or hardware modules that provide additional features, functionality and/or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photographs and/or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth® module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, a Virtual Reality and/or Augmented Reality (VR/AR) device, an activity tracker, and the like. The peripherals 138 may include one or more sensors, the sensors may be one or more of a gyroscope, an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and/or a humidity sensor.

[0047] The WTRU 102 may include a full duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for both the UL (e.g., for transmission) and downlink (e.g., for reception) may be concurrent and/or simultaneous. The full duplex radio may include an interference management unit 139 to reduce and or substantially eliminate self-interference via either hardware (e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118). In an embodiment, the WRTU 102 may include a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the UL (e.g, for transmission) or the downlink (e.g, for reception)).

[0048] FIG. 1C is a system diagram illustrating the RAN 104 and the CN 106 according to an embodiment. As noted above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also be in communication with the CN 106.

[0049] The RAN 104 may include eNode-Bs 160a, 160b, 160c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 160a, 160b, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the eNode-Bs 160a, 160b, 160c may implement MIMO technology. Thus, the eNode-B 160a, for example, may use multiple antennas to transmit wireless signals to, and/or receive wireless signals from, the WTRU 102a.

[0050] Each of the eNode-Bs 160a, 160b, 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and/or DL, and the like. As shown in FIG. 1C, the eNode-Bs 160a, 160b, 160c may communicate with one another over an X2 interface.

[0051] The CN 106 shown in FIG. 1 C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. While each of the foregoing elements are depicted as part of the CN 106, it will be appreciated that any of these elements may be owned and/or operated by an entity other than the CN operator. [0052] The MME 162 may be connected to each of the eNode-Bs 162a, 162b, 162c in the RAN 104 via an S1 interface and may serve as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation/deactivation, selecting a particular serving gateway during an initial attach of the WTRUs 102a, 102b, 102c, and the like. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and/or WCDMA.

[0053] The SGW 164 may be connected to each of the eNode Bs 160a, 160b, 160c in the RAN 104 via the S1 interface. The SGW 164 may generally route and forward user data packets to/from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring user planes during inter- eNode B handovers, triggering paging when DL data is available for the WTRUs 102a, 102b, 102c, managing and storing contexts of the WTRUs 102a, 102b, 102c, and the like.

[0054] The SGW 164 may be connected to the PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0055] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the CN 106 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and/or wireless networks that are owned and/or operated by other service providers.

[0056] Although the WTRU is described in FIGS. 1 A-1 D as a wireless terminal, it is contemplated that in certain representative embodiments that such a terminal may use (e.g., temporarily or permanently) wired communication interfaces with the communication network.

[0057] In representative embodiments, the other network 112 may be a WLAN.

[0058] A WLAN in Infrastructure Basic Service Set (BSS) mode may have an Access Point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have an access or an interface to a Distribution System (DS) or another type of wired/wireless network that carries traffic in to and/or out of the BSS. Traffic to STAs that originates from outside the BSS may arrive through the AP and may be delivered to the STAs. Traffic originating from STAs to destinations outside the BSS may be sent to the AP to be delivered to respective destinations. Traffic between ST As within the BSS may be sent through the AP, for example, where the source STA may send traffic to the AP and the AP may deliver the traffic to the destination STA. The traffic between STAs within a BSS may be considered and/or referred to as peer-to- peer traffic. The peer-to-peer traffic may be sent between (e.g., directly between) the source and destination STAs with a direct link setup (DLS). In certain representative embodiments, the DLS may use an 802.11 e DLS or an 802.11 z tunneled DLS (TDLS). A WLAN using an Independent BSS (I BSS) mode may not have an AP, and the STAs (e.g., all of the STAs) within or using the IBSS may communicate directly with each other. The IBSS mode of communication may sometimes be referred to herein as an “ad- hoc” mode of communication.

[0059] When using the 802.11 ac infrastructure mode of operation or a similar mode of operations, the AP may transmit a beacon on a fixed channel, such as a primary channel. The primary channel may be a fixed width (e.g., 20 MHz wide bandwidth) or a dynamically set width via signaling. The primary channel may be the operating channel of the BSS and may be used by the STAs to establish a connection with the AP. In certain representative embodiments, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) may be implemented, for example in in 802.11 systems. For CSMA/CA, the STAs (e.g., every STA), including the AP, may sense the primary channel. If the primary channel is sensed/detected and/or determined to be busy by a particular STA, the particular STA may back off. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0060] High Throughput (HT) STAs may use a 40 MHz wide channel for communication, for example, via a combination of the primary 20 MHz channel with an adjacent or nonadjacent 20 MHz channel to form a 40 MHz wide channel.

[0061] Very High Throughput (VHT) STAs may support 20MHz, 40 MHz, 80 MHz, and/or 160 MHz wide channels. The 40 MHz, and/or 80 MHz, channels may be formed by combining contiguous 20 MHz channels. A 160 MHz channel may be formed by combining 8 contiguous 20 MHz channels, or by combining two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. For the 80+80 configuration, the data, after channel encoding, may be passed through a segment parser that may divide the data into two streams. Inverse Fast Fourier Transform (IFFT) processing, and time domain processing, may be done on each stream separately. The streams may be mapped on to the two 80 MHz channels, and the data may be transmitted by a transmitting STA. At the receiver of the receiving STA, the above described operation for the 80+80 configuration may be reversed, and the combined data may be sent to the Medium Access Control (MAC). [0062] Sub 1 GHz modes of operation are supported by 802.11 af and 802.11 ah. The channel operating bandwidths, and carriers, are reduced in 802.11 af and 802.11 ah relative to those used in 802.11 n, and 802.11ac. 802.11 af supports 5 MHz, 10 MHz and 20 MHz bandwidths in the TV White Space (TVWS) spectrum, and 802.11 ah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non-TVWS spectrum. According to a representative embodiment, 802.11 ah may support Meter Type Control/Machine- Type Communications, such as MTC devices in a macro coverage area. MTC devices may have certain capabilities, for example, limited capabilities including support for (e. g . , only support for) certain and/or limited bandwidths. The MTC devices may include a battery with a battery life above a threshold (e.g., to maintain a very long battery life).

[0063] WLAN systems, which may support multiple channels, and channel bandwidths, such as 802.11 n, 802.11 ac, 802.11 af, and 802.11 ah, include a channel which may be designated as the primary channel. The primary channel may have a bandwidth equal to the largest common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be set and/or limited by a ST A, from among all STAs in operating in a BSS, which supports the smallest bandwidth operating mode. In the example of 802.11 ah, the primary channel may be 1 MHz wide for STAs (e.g., MTC type devices) that support (e.g., only support) a 1 MHz mode, even if the AP, and other STAs in the BSS support 2 MHz, 4 MHz, 8 MHz, 16 MHz, and/or other channel bandwidth operating modes. Carrier sensing and/or Network Allocation Vector (NAV) settings may depend on the status of the primary channel. If the primary channel is busy, for example, due to a STA (which supports only a 1 MHz operating mode), transmitting to the AP, the entire available frequency bands may be considered busy even though a majority of the frequency bands remains idle and may be available.

[0064] In the United States, the available frequency bands, which may be used by 802.11 ah, are from 902 MHz to 928 MHz. In Korea, the available frequency bands are from 917.5 MHz to 923.5 MHz. In Japan, the available frequency bands are from 916.5 MHz to 927.5 MHz. The total bandwidth available for 802.11 ah is 6 MHz to 26 MHz depending on the country code.

[0065] FIG. 1 D is a system diagram illustrating the RAN 113 and the CN 115 according to an embodiment. As noted above, the RAN 113 may employ an NR radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0066] The RAN 113 may include gNBs 180a, 180b, 180c, though it will be appreciated that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, gNBs 180a, 108b may utilize beamforming to transmit signals to and/or receive signals from the gNBs 180a, 180b, 180c. Thus, the gNB 180a, for example, may use multiple antennas to transmit wireless signals to, and/or receive wireless signals from, the WTRU 102a. In an embodiment, the gNBs 180a, 180b, 180c may implement carrier aggregation technology. For example, the gNB 180a may transmit multiple component carriers to the WTRU 102a (not shown). A subset of these component carriers may be on unlicensed spectrum while the remaining component carriers may be on licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement Coordinated Multi-Point (CoMP) technology. For example, WTRU 102a may receive coordinated transmissions from gNB 180a and gNB 180b (and/or gNB 180c).

[0067] The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using transmissions associated with a scalable numerology. For example, the OFDM symbol spacing and/or OFDM subcarrier spacing may vary for different transmissions, different cells, and/or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using subframe or transmission time intervals (TTIs) of various or scalable lengths (e.g., containing varying number of OFDM symbols and/or lasting varying lengths of absolute time).

[0068] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and/or a non-standalone configuration. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c without also accessing other RANs (e.g., such as eNode-Bs 160a, 160b, 160c). In the standalone configuration, WTRUs 102a, 102b, 102c may utilize one or more of gNBs 180a, 180b, 180c as a mobility anchor point. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using signals in an unlicensed band. In a non-standalone configuration WTRUs 102a, 102b, 102c may communicate with/connect to gNBs 180a, 180b, 180c while also communicating with/connecting to another RAN such as eNode-Bs 160a, 160b, 160c. For example, WTRUs 102a, 102b, 102c may implement DC principles to communicate with one or more gNBs 180a, 180b, 180c and one or more eNode-Bs 160a, 160b, 160c substantially simultaneously. In the non-standalone configuration, eNode-Bs 160a, 160b, 160c may serve as a mobility anchor for WTRUs 102a, 102b, 102c and gNBs 180a, 180b, 180c may provide additional coverage and/or throughput for servicing WTRUs 102a, 102b, 102c. [0069] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and/or DL, support of network slicing, dual connectivity, interworking between NR and E-UTRA, routing of user plane data towards User Plane Function (UPF) 184a, 184b, routing of control plane information towards Access and Mobility Management Function (AMF) 182a, 182b and the like. As shown in FIG. 1D, the gNBs 180a, 180b, 180c may communicate with one another over an Xn interface.

[0070] The CN 115 shown in FIG. 1 D may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one Session Management Function (SMF) 183a, 183b, and possibly a Data Network (DN) 185a, 185b. While each of the foregoing elements are depicted as part of the CN 115, it will be appreciated that any of these elements may be owned and/or operated by an entity other than the CN operator.

[0071] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may serve as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, support for network slicing (e.g., handling of different PDU sessions with different requirements), selecting a particular SMF 183a, 183b, management of the registration area, termination of NAS signaling, mobility management, and the like. Network slicing may be used by the AMF 182a, 182b in order to customize CN support for WTRUs 102a, 102b, 102c based on the types of services being utilized WTRUs 102a, 102b, 102c. For example, different network slices may be established for different use cases such as services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access, services for machine type communication (MTC) access, and/or the like. The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-A Pro, and/or non-3GPP access technologies such as WiFi. [0072] The SMF 183a, 183b may be connected to an AMF 182a, 182b in the CN 115 via an N11 interface. The SMF 183a, 183b may also be connected to a UPF 184a, 184b in the CN 115 via an N4 interface. The SMF 183a, 183b may select and control the UPF 184a, 184b and configure the routing of traffic through the UPF 184a, 184b. The SMF 183a, 183b may perform other functions, such as managing and allocating WTRU IP address, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notifications, and the like. A PDU session type may be IP-based, non-IP based, Ethernet-based, and the like. [0073] The UPF 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPF 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, and the like.

[0074] The CN 115 may facilitate communications with other networks. For example, the CN 115 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and/or wireless networks that are owned and/or operated by other service providers. In one embodiment, the WTRUs 102a, 102b, 102c may be connected to a local Data Network (DN) 185a, 185b through the UPF 184a, 184b via the N3 interface to the UPF 184a, 184b and an N6 interface between the UPF 184a, 184b and the DN 185a, 185b.

[0075] In view of Figures 1A-1 D, and the corresponding description of Figures 1A-1 D, one or more, or all, of the functions described herein with regard to one or more of: WTRU 102a-d, Base Station 114a-b, eNode-B 160a-c, MME 162, SGW 164, PGW 166, gNB 180a-c, AMF 182a-ab, UPF 184a-b, SMF 183a-b, DN 185a-b, and/or any other device(s) described herein, may be performed by one or more emulation devices (not shown). The emulation devices may be one or more devices configured to emulate one or more, or all, of the functions described herein. For example, the emulation devices may be used to test other devices and/or to simulate network and/or WTRU functions.

[0076] The emulation devices may be designed to implement one or more tests of other devices in a lab environment and/or in an operator network environment. For example, the one or more emulation devices may perform the one or more, or all, functions while being fully or partially implemented and/or deployed as part of a wired and/or wireless communication network in order to test other devices within the communication network. The one or more emulation devices may perform the one or more, or all, functions while being temporarily implemented/deployed as part of a wired and/or wireless communication network. The emulation device may be directly coupled to another device for purposes of testing and/or may performing testing using over-the-air wireless communications.

[0077] The one or more emulation devices may perform the one or more, including all, functions while not being implemented/deployed as part of a wired and/or wireless communication network. For example, the emulation devices may be utilized in a testing scenario in a testing laboratory and/or a non-deployed (e.g., testing) wired and/or wireless communication network in order to implement testing of one or more components. The one or more emulation devices may be test equipment. Direct RF coupling and/or wireless communications via RF circuitry (e.g., which may include one or more antennas) may be used by the emulation devices to transmit and/or receive data.

[0078] Multiple input multiple output (MIMO) channel state information (CSI) prediction may include prediction of the codebook-based precoding matrix indicator (PMI). Artificial intelligence (Al) I machine learning (ML) CSI prediction may include the prediction of channel matrix and/or eigen vectors.

[0079] FIG. 2 depicts an example of multiple CSI prediction framework 200. An example framework for AI/ML based feedback may be CSI prediction, as shown in FIG. 2, where the WTRU may predict one or more instances of future CSI (e.g., channel matrices matrices H(t + 1), + P)), by using the current and/or historical CSI measurements (e.g., H (t - N), CSI prediction may reduce the CSI reporting overhead and/or may reduce the number of downlink CSI-reference signals (CSI-RS). The CSI prediction may be (e.g., typically) handled by the UE.

[0080] CSI prediction problem(s) may center around prediction of one or more instances of the future CSI (e.g., H(t + 1), H (t + P)), by using the current and/or historical CSI measurements (e.g., H(t - based CSI prediction methods may (e.g, typically) perform the prediction in raw channel space where the impact of different multipaths between the transmitter and/or receiver may be (e.g, jointly) considered and/or the prediction may be performed across the high dimensional CSI matrix. This may make the prediction problem (e.g, significantly) hard to solve. As a result, the AI/ML model to make such prediction may be large and/or may lead to inference complexity, latency, power consumption, and/or the like.

[0081] Methods for parameterizing channel into low dimensional explainable components and/or determining future values of these components and/or reporting to the network may be described herein. A WTRU may determine a subset of channel parameters to report based on measurements, to reduce complexity of reporting complete CSI.

[0082] A WTRU may receive configuration information associated with channel parameters to be selected and/or reported, including transmission path, angle of arrival (AoA), angle of departure (AoD), path gain, doppler range, and/or delay spread range. The WTRU may (e.g, also) be configured with criteria for channel parameter selection and/or reporting. For example, criteria for channel parameter selection and/or reporting may include minimizing / maximizing a preconfigured criteria I model (e.g, |H - For example, criteria for channel parameter selection and/or reporting may include one or more values under the constraints/bounds configured for parameters (e.g., max number of paths/rank, threshold for number of paths, AoA range, AoD range, range for gains, doppler range, and/or delay spread range). A WTRU may receive configuration information. The configuration information may include an indication of a set of channel parameters (e.g, to be estimated) associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and/or second criteria associated with reporting. The plurality of paths may be fewer than a number of paths in a CSI matrix. The WTRU may determine the prediction channel parameters, for example, based on the (e.g, first) criteria. The prediction channel parameters may be more than the measured channel parameters. The prediction channel parameters may be less than the measured and/or estimated channel parameters.

[0083] The WTRU may be configured with a first criteria to determine a first set of channel parameters for a first set of paths and/or a second criteria to determine a second set of channel parameters for a second set of paths. The first set of channel parameters may be for tracking set of paths, which may include the set of parameters corresponding to valid paths in the channel that may (e.g, need to) be tracked. The (e.g, first) set of channel parameters may include one or more of: a transmission path, one or more angle of arrivals (AoA) associated with one or more different axes (e.g. azimuth AoA and/or elevation AoA), one or more angle of departures (AoD) associated with one or more different axes (e.g. azimuth AoD and/or elevation AoD), a path gain, a doppler range, and/or a delay spread. For example, the WTRU may use the first criteria to determine the valid paths in the channel based on one or more of: the max number of paths to be tracked, AoA/AoD being within a first range, the gain is greater than a first threshold, etc. For example, first criteria may include a first path gain threshold for adding paths to tracking set. For example, first criteria may include a second path gain threshold for removing paths from tracking set. For example, first criteria may include a first AoA and AoD range for adding paths to tracking set. For example, first criteria may include a second AoA and AoD range for removing paths from tracking set. For example, first criteria may include a time window and/or interval during which the criteria are evaluated. For example, first criteria may include an observation window length N and/or a prediction window length L. The second set of channel parameters may be a reporting set of paths that include the set of parameters corresponding to the (e.g, most) useful paths in the channel that may (e.g, need to) be reported. The WTRU may use the second criteria to determine the (e.g, most) useful paths in the channel based on one or more of: dominant path (e.g, gain above a threshold); the time within tracking set above a second threshold; one or more rules based on available uplink (UL) resources (e.g, select maximum number of paths < the available UL resources); prioritization rules (e.g, number of parts as function of priority of CSI report (e.g., higher P value for high priority CSI report and/or low P value for low priority CSI report)); a compression factor (e.g., number of parts as a function of compression factor); performance metric(s) (e.g., reconstruction performance, link performance, acknowledgment (ACK)/ negative ACK (NACK) count, etc.); and/or based on the CSI rank. For example, the second criteria may include one or more of: a gain above a threshold, a time associated with how long each path remains in the plurality of paths, one or more rules based on available uplink resources, one or more prioritization rules, a compression factor, one or more performance metrics, and/or a CSI rank value. The WTRU may determine the second subset of the plurality of paths based on the second criteria.

[0084] A WTRU may receive CSI-RS, may perform channel estimation, and/or may determine the channel parameters including actual number of paths in the channel N_p and/or parameters associated with one or more (e.g., each) of the N_p paths (e.g., AoA 6_k, AoD (p_k, gain b_k, f_k doppler, and/or 8_k delay). The channel parameter estimation criteria |H - h_fca_fi(0_k)a^( _k) | may be minimized. For example, the WTRU may receive one or more CSI-RSs. The WTRU may determine the channel parameter(s) associated with the first subset of the plurality of paths, for example, based on the received CSI-RS(s).

[0085] A WTRU may apply the first criteria to determine the set of paths and/or the parameters associated with each of the paths forming the first (e.g., tracking) set (e.g., adding parameters that satisfy the first criteria to the first set, removing parameters that do not satisfy the first criteria from the set). First criteria may include WTRU side conditions (e.g., memory, processing availability, etc.). For example, the WTRU may determine a first subset of the plurality of paths based on values of channel parameters associated with the first subset of the plurality of paths and/or the first criteria. The first set of channel parameters may be associated with a first time period. The WTRU may determine one or more values of the channel parameters for each path of the plurality of paths. The WTRU may determine the first subset of the plurality of paths based on a comparison of the first criteria and the one or more values of the channel parameters for each path of the plurality of paths.

[0086] For one or more (e.g., each) prediction instance(s) t (e.g., possibly same or different from CSI-RS periodicity) and/or for one or more (e.g., each) paths in the first set and/or determined subset of channel parameters for each paths in the first set, the WTRU may obtain the predicted channel parameters of the paths in the first set at future time instance t L For example, the WTRU may determine one or more values of predicted channel parameters for each path of the first subset of paths. The one or more values of the predicted channel parameters may be associated with a second time period. The second time period may be different from the first time period. The second time period may be concurrent with a periodicity associated with CSI-RS transmission.

[0087] The WTRU may apply the second criteria to determine the set of paths forming the second (e.g., reporting) set of paths. The WTRU may determine the (e.g., predicted) channel parameters associated with the second set based on the predicted channel parameters of the paths in the first set. For example, the WTRU may determine a second subset of the plurality of paths based on the second criteria and/or the one or more values of the predicted channel parameters for each path of the first subset of paths. The second subset of paths may be a subset of the first subset of paths. The WTRU may determine one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths. The WTRU may determine the second subset of the plurality of paths based on a comparison of the second criteria and the one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths. The WTRU may determine a subset of values associated with the second subset of the plurality of paths.

[0088] The WTRU may report the (e.g., predicted) channel parameters associated with the second (e.g, reporting) set (e.g, in CSI report). The report may include the number of parameters in the second set. The WTRU may be configured to transmit the first set (e.g, statistics thereof) for performance monitoring. For example, the WTRU may send an indication that indicates the one or more values of the predicted channel parameters associated with the second subset of the plurality of paths. The WTRU may send an indication that indicates the subset of values associated with the second subset of the plurality of paths to send the indication. The indication may be indicative of a channel matrix associated with the downlink transmission. [0089] One or more (e.g, current) methods for CSI prediction may be based on (e.g, rely on) predicting parts of the CSI matrix (e.g, per sub-band, per TX/RX antenna, and/or any combination of these entities), and/or the entire CSI matrix across time slots. Irrespective of how the CSI matrix may be predicted, the CSI matrix may be affected by a combination of independently evolving multipath components and/or (e.g, thus) predicting the cumulative effect of these multipaths may be a (e.g, very) hard problem. Using the channel parameter estimation framework, the CSI matrix can be decomposed into independent propagation paths, (e.g, thus) allowing time domain prediction of one or more (e.g, each) path separately, which may be a (e.g, more) tractable problem. Decomposing each path as 6_k, (p_k, b_k, f_k, 8_k may reduce the complexity further, (e.g, thus) allowing for a smaller set of parameters that require prediction. Additionally or alternatively, the channel parameterization approach may enable interpretability of AI/ML model behavior. This approach of channel parameterization can be (e.g., further) leveraged for enhancing other aspects including CSI compression, performance monitoring, and/or the like. For example, the set of channel parameters may be determined based on one or more of: an orthogonal matching pursuit based determination of the multipath channel (MPC) parameter(s), a deep learning-based MPC determination, and/or an optimization function-based determination.

[0090] Machine learning based approaches may be utilized to decompose the MIMO channel matrix and/or may extract one or more (e.g., all of) the (e.g., necessary and/or sufficient) parameters to reconstruct the channel. These parameters may be (e.g., primarily) associated with the multipaths within the channel. Having access to these parameters can support multiple different wireless communication tasks. CSI prediction may include predictions that could be more efficiently performed for tracking and/or predicting the changes in one or more (e.g., each) multipath independently. CSI Compression may include the multipath parameters extracted from the channel matrix serving as a compressed representation for the channel. The angels corresponding to the strongest beams and/or paths could be (e.g., directly) used as directions for beamforming. Methods, apparatuses, and/or systems described herein may allow for the prediction to be performed independently for the parameters associated with each path independently and/or (e.g., thus) isolating the impact on each path and/or reducing the overall dimensionality of the features and/or variables to be predicted.

[0091] Embodiments described herein may include configuration for channel parameter estimation. A WTRU that is capable of performing channel parameter estimation may receive configuration for the operation, including configuration to accomplish parameter estimation, configuration for parameter estimation aided CSI feedback and/or reporting, configuration for determining a set of parameters to be tracked and/or to achieve prediction of CSI, where the configuration and/or reconfiguration may be performed via radio resource control (RRC) signaling. In examples, a WTRU may be configured with information pertaining to estimation underlying multipath related parameters from a MIMO channel matrix. [0092] In examples, a WTRU may (e.g., first) inform the network (NW) about the available resources at the WTRU to achieve channel parameter estimation and/or CSI prediction. The WTRU may send on-device capability and/or processing constraints (e.g., maximum available memory, maximum processing delay, processing power, feedback delay class with information about acceptable feedback delay, minimum required RS density and/or specific RS density/pattern, and/or the like) to the NW.

[0093] The WTRU may (e.g., then) receive information regarding a pre-configured criteria and/or a model of the environment from the NW that may represent the overall optimization problem and/or may indicate the objective that may (e.g., need to) be maximized or minimized to effectively achieve the parameter estimation. One example of this criterion and/or model in a setup with uniform linear arrays may be |H - ‘b_fca_R (0_fe)a^ ( _fc) |, where H may represent the MIMO channel matrix at a given time instant at one of more frequencies/resource blocks/sub-bands. N_p may indicate the number of underlying multipaths within the channel between the transmitter and the receiver. 6_k may represent the angle of receptions and/or angle of arrival (AoA). (p_k may represent the angle of departure (AoD) and/or angle of transmission. a_R may be the array response vector at the receive side and/or a_T may be the array response vector at the transmit side. The NW may indicate that the indicated criterion may (e.g., needs to) be maximized or minimized in the parameter estimation process. Examples described herein may consider a uniform linear array, in the setup with planar arrays there may be two angles associated with angles of transmission/departure and/or angles of arrival/reception representing the azimuth and/or elevation angles. With respect to planar arrays, for example, the angles of arrival/reception may be referred as azimuth of arrival (AoA) and/or elevation of arrival (ZoA); the departure angles may be referred to as azimuth of departure (AoD) and/or elevation of departure (ZoD).

[0094] In examples, the WTRU may be (e.g., explicitly) configured to estimate one or more (e.g., all) and/or a subset of parameters that may be estimated and/or (e.g., also) provide bounds and/or constraints on these parameters to aid and/or configure the estimation process. For example, maximum number of paths/rank may indicate the upper bound on the number of paths that may exist in the channel matrix and/or the maximum rank that the channel matrix may have. For example, threshold for number of paths and/or rank may indicate the maximum number of paths that may be estimated and/or the maximum rank up to which this path(s) may be estimated. For example, AoA and/or AoD range may include constraints and/or bounds on the range of angle of arrival and/or angle of departure of one or more (e.g., each) path. For example, range for gains may include constrains and/or bounds on the potential range of values that the gain parameter may take for each path. For example, doppler range may include constraints and/or bounds on the potential range of values for the doppler parameter associated with each path component. For example, delay range may include constraints and/or bounds on the potential range of values for the delay associated with each multipath.

[0095] In examples, the WTRU may (e.g., further) be configured with the appropriate array response vector associated with the NWs antenna array setup. The configuration may (e.g., either) directly include the entire array response and/or parameters for evaluating the array response, example number of transmit (or NW) antennas, antenna spacing, antenna array configuration (e.g., uniform linear array (ULA), uniform rectangular array (URA), etc.), and/or the (e.g., exact) element configuration. In examples, the WTRU may utilize a default configuration of the NW’s array response. In examples, the WTRU may (e.g., also) inform the NW about its own array response, and/or parameters required to estimate them. In examples, the WTRU may be configured with a reference array response. The WTRU may perform channel parameter estimation using the reference array response.

[0096] In examples, the WTRU may be configured with a first set (e.g. tracking set) and/or a first set of criterions to setup and/or include paths and/or parameters into the first set. The first set of criteria may be utilized to identify the set of valid paths that may (e.g., need to) be tracked and/or may be useful for CSI prediction and/or feedback reporting. The first set of criteria may be (e.g., also) utilized to identify the set of parameters corresponding to each valid path that may (e.g., need to) be tracked. One or more (e.g., some) examples of the first set of criterion may include one or more of the filing. The first set of criterion may include a first path gain threshold for adding paths to set. The first set of criterion may include a second path gain threshold for removing paths from set. The first set of criterion may include a first AoA and/or AoD range for adding paths to set. The first set of criterion may include a second AoA and/or AoD range for removing paths to set. The first set of criterion may include time window/interval during which the criteria are evaluated. The first set of criterion may include, based on configured prediction window length L, for example, Observation window length N.

[0097] In examples, the WTRU may be configured with a second set (e.g. reporting set) and/or a second set of criterions to setup and/or may include paths and/or parameters into the second set. The second set of criteria may be utilized to identify the set of (e.g., most) useful paths that may (e.g., need to) be tracked and/or may be (e.g., most) useful for CSI feedback reporting. The second set of criteria may (e.g., also) be utilized to identify the subset of parameters corresponding to each useful path that may (e.g., need to) be tracked and/or reported . One or more (e.g., some) examples of the second set of criterion may include one or more of the following. The second set of criterion may include selection of dominant paths using thresholds (e.g., a threshold may be defined on the gain associated with each path to check if the path can be considered a dominant path or not). The second set of criterion may include the time within tracking set (e.g., the time above a second threshold). The second set of criterion may include rules based on available UL resources (e.g., select maximum number of paths < the available UL resources). The second set of criterion may include prioritization rules (e.g., number of parts as a function of priority of CSI report (e.g., higher P value for high priority CSI report and/or low P value for low priority CSI report)). The second set of criterion may include a compression factor (e.g., number of parts as a function of compression factor). The second set of criterion may include performance metric(s) (e.g., reconstruction performance, link performance, ACK/NACK count, etc.). The second set of criterion may be based on the CSI rank.

[0098] Embodiments described herein may relate to methods for channel parameter estimation. The (e.g., exact) algorithm may be (e.g., mostly) WTRU implementation. The support for specific algorithm may imply impact to WTRU capability and/or may be indicated implicitly via WTRU sends on-device capability and/or processing constraints to gNB (e.g., (a) maximum available memory, (b)max processing delay, (c) processing power, (d) feedback delay class with information about acceptable feedback delay, (e) minimum required RS density and/or specific RS density/pattern).

[0099] The overall problem may focus on estimating the channel related parameters (e.g. number of multipath components, parameters associated with each multipath like, gain, AoA, AoD, doppler, etc.) from MIMO channel matrices. Different methods can be employed to recover these parameters, and/or depending on the methods, additional configurations may be required. One or more example implementations and/or frameworks for channel estimation may be described herein (e.g., orthogonal matching pursuit (OMP) based channel parameter estimation, deep learning based channel parameter estimation, and/or optimization based channel parameter estimation).

[0100] OMP based channel parameter estimation may be described herein. This method may use the OMP algorithm to calculate the OMP residual information from the given channel matrix. This residual information may (e.g., then) be fed to a classifier, for example, Linear Discriminant Analysis (LDA) model that may output the predicted number of multipaths. The combination of this OMP and LDA model can be viewed as a classifier that predicts the number of multipath component (MPC) information. The term channel parameters and/or MPC parameters may be used interchangeably herein.

[0101] The channel matrix may be (e.g., again) fed to the OMP algorithm. The predicted number of MPCs may be used as a stopping criterion for the OMP algorithm. The output may be the actual values of the multi-path components. The second OMP may be related to (e.g., solving) a regression problem of predicting the MPC values (e.g., angles of arrival and/or departures, gains, delays, etc. for each MPC component).

[0102] FIG. 3 depicts a high-level framework for OMP based channel parameter estimation 300. At the classification stage, the OMP algorithm may be utilized to process the channel and/or may produce intermediate components which may be (e.g., then) utilized by a classifier (e.g., LDA based classifier) to determine the number of multipaths. At the regression stage, the OMP based algorithm may be utilized to produce the multipath parameters and/or channel parameters. [0103] Deep learning based MPC prediction may be described herein. Like the OMP-based method described herein, a two-step approach may be employed that uses trained deep neural networks (DNN) in one or more (e.g. , each) procedures. For example, it may use the same DNN for one or more procedures and/or it may use different DNNs for one or more of the procedures. The input to these models may be a channel matrix and/or a transformation of it. FIG. 4 shows an example implementation that uses the Discrete Furrier Transform (DFT) of the channel matrix as the input to the DNN models.

[0104] FIG. 4 illustrates an example of a high-level framework for Deep learning based channel parameter estimation 400. At the classification stage a deep learning model (e.g., Multi Path Detector) may be used to extract multi path classification features. These features may (e.g., then) be utilized by a classifier (e.g., LDA based classifier) to determine the number of multipaths. At the regression stage (e.g., next), a deep learning based model may be utilized to produce the multipath parameters and/or channel parameters.

[0105] In the classification procedure, for example, a DNN model may be used to extract the classification features. Similar to the OMP method, for example, these features may be fed to a LDA, which may predict the number of multipaths.

[0106] For the regression procedure, for example, a preconfigured number of DNNs may be trained one for each (e.g., possible) value of the number of MPCs. Each model may be structured and/or trained for the specific number of MPCs and/or outputs predictions for a fixed number of MPC values (e.g., Angels of arrival and/or departures, gains, delays, etc.) for each MPC component). Based on the predicted number of multipath components in the classification procedure, for example, the corresponding regression model may be selected and/or used to predict the MPC values.

[0107] FIG. 5 shows an exemplary structure of the DNNs, which may use residual blocks as the (e.g., main) building block of the model 500. The same model structure may be used for (e.g., both) classification and/or regression procedures, which may be trained independently. For example, FIG. 5 depicts an exemplary structure of the deep learning model used for multipath detection and/or multipath parameter regression. The model may use a combination of convolution neural network layers (CNN), fully connected (FC) layers, batch normalization (BN) layer and/or residual connections.

[0108] Optimization based channel parameter estimation may be described herein. Channel parameters may be estimated by optimizing for the individual parameters. For example, the channel parameters can be estimated by minimizing the cost (e.g., Minimize |H - w.r.t ³k> ^k’ k> ^p)- [0109] In examples, the optimization problem can be solved in its raw form using gradient based methods. In examples, the optimization formulation may be modified before solving. The modifications may include relaxations designed to reduce the non-convexity of the overall optimization problem.

[0110] In examples, a sparse over parametrized version of the optimization problem can be solved, where the optimization may be solved as |H - \, where N_o » N_p. This overparametrized formulation may allow instantiation of N_o multipath components spread across the entre optimization landscape and/or increasing the probability that out of N_o paths, N_p of them may correctly identify the true multipaths. Additionally or alternatively, to enforce that (e.g., only) N_p strong paths are selected out of the potential N_o, paths, additional sparsity inducing formulations may be included. For example, and L1 and/or norm-1 based penalty on the gains may be included to enforce sparsity in the number of paths. In examples, accelerated gradient descent strategy may be utilized where the overall optimization may be modified as. : |H - ' _k ^p ₌₁ b_k a_R 0_k)a!} (l)_k)\, with the gain, b_k, being raised to the power of n (b_k), to ensure that (e.g., only) one or more (e.g., a few) strong paths are selected and/or a sparse optimization can be reached. Other sparsity inducing formulations may also be utilized.

[0111] One or more of the strategies (e.g., as described herein) may be utilized for channel parameter estimation. Post parameter estimation, path/parameter prediction may be performed using machine learning based, non-ML based, and/or statistical prediction methods.

[0112] Parameters estimated using the channel parameter estimation framework can be predicted under different paradigms. In examples, parameters associated with one or more paths may be (e.g., jointly) predicted. In examples, each parameter of each path may be (e.g., individually) predicted. In examples, the channel associated with each path may be (e.g., independently) predicted.

[0113] Embodiments described herein may include channel parameter prediction. A WTRU (e.g., that is capable of performing prediction of channel response parameters), for CSI feedback reporting, may receive CSI-RS. The WTRU may estimate the (e.g., current) channel response matrix, for example, based on the (e.g., current) received CSI-RS. The WTRU may determine the number of paths (e.g., significant paths) of the channel response, N_p, that meet a configured criterion (e.g., path power (or relative path power) exceeding a threshold). The WTRU may perform parameter estimation using the determined number of paths N_p, where for each path, the WTRU may estimate the configured parameters for the current measured channel response. For example, the WTRU may be configured to estimate the AoA, ZoA, AoD, ZoD, path gain, path delay, and/or Doppler parameters for each path. [0114] The WTRU may use the configured first criteria to determine a first (e.g., tracking) set of paths to track (e.g., for predicting future instances of the path parameters), where the tracking set may help reduce the computational complexity and/or latency associated with predicting the parameters of one or more (e.g., all) N_p paths. The tracking set may be a subset of one or more (e.g, all) paths of the measured channel response, included of N_{p track} paths, where N_{p track} < N_p. In examples, the WTRU may use the tracking set as a subset N_{p track} < N_p of one or more (e.g, all) channel response paths (e.g, when the WTRU computational capabilities may be limited). In examples, the tracking set may include one or more (e.g, all) N_p channel response paths (N_p>track - N_p), for example, in case of line-of-sight (LOS) channels, and/or when the prediction complexity may be lower than a configured threshold.

[0115] The WTRU may perform prediction for the parameters of each path in the tracking set, where the WTRU may predict one or more instances of the parameters, per the prediction window configuration. [0116] The WTRU may apply a second criteria on the predicted parameters of paths in the tracking set, to determine a second (e.g, reporting) set of paths to be reported (e.g, to reduce the CSI feedback reporting overhead). The reporting set may have N_{p report} paths, where N_{p report} < N_{p track} . In examples, the reporting set may include the same number of paths as the tracking set (N_p>report = N_{p track}), for example, when the UL resources available for CSI reporting may be sufficient to accommodate the full tracking set. In examples, the reporting set may be a subset of the tracking set (N_{p report} = N_{p track}), for example, when the UL report may be resource limited.

[0117] A WTRU may perform one or more of the following actions, for example, to determine the tracking set. For each path of the full channel response (W_p), compare the path gain to a first path gain threshold; when the path gain exceeds the first threshold, the path is included in the tracking set. For each path of the full channel response (/V_p), the WTRU may compare the path gain to a second path gain threshold, where the second gain threshold may be lower than the first gain threshold; when the path gain is lower than second first threshold, the path may not not included in the tracking set. For each path of the full channel response (A/_p), the WTRU may compare the AoA/AoD to a first AoA/AoD range threshold; when the path AoA/AoD is within the first AoA/AoD range, the path may be included in the tracking set. For each path of the full channel response (/V_p), the WTRU may compare the AoA/AoD to a second AoA/AoD range threshold, where the second AoA/AoD range is wider than the first AoA/AoD range; when the path AoA/AoD is outside of the second AoA/AoD range, the path may not be included in the tracking set. The WTRU may update the tracking set as a function of UE-side processing resources availability. For example, the WTRLI may include in the tracking set N_{p cpu} strongest paths, such that the processing of parameter prediction of the N_{p cpu} paths fits in the available processing resources. The WTRU may update the tracking set as a function of WTRU-side memory availability. For example, the WTRU may include in the tracking set N_{p mem} strongest paths, such that the storage requirements associated with the observation window for the parameter prediction of the N_{p mem} paths fits in the available memory. For example, the WTRU may update the first subset of paths of the plurality of paths or the second subset of paths of the plurality of paths based on one or more of: the first criteria, the second criteria, a time window during which the first criteria is evaluated, a configured prediction window, or an observation window length.

[0118] When the WTRU determines that a path is included in the tracking set, for example, the WTRU may add the path to the tracking set, for example, if the path was not previously included in the tracking set. In examples, when the WTRU adds another (e.g., new) path to the tracking set, the WTRU may perform (e.g., only perform) prediction of the path parameters once it accumulates the configured number of samples in the observation buffer, for example, to enable accurate prediction. In examples, when the WTRU adds another (e.g., new) path to the tracking set, the WTRU may run the prediction model for the (e.g., newly) added path. In (e.g., both) examples, the WTRU may associate a flag to the other (e.g., new) path, for example, to indicate that another (e.g., new) path was added to the tracking set, and/or that the parameter prediction associate to the new path may be based on incomplete observations.

[0119] When the WTRU determines that a path is not included in the tracking set, for example, the WTRU may remove the path from the tracking set, for example, if the path was previously included in the tracking set. In examples, if the path was previously in the tracking set, the WTRU may (e.g., still) update the observation buffer and/or may perform parameter prediction for that path and/or may remove the path from the tracking set at the next time instance (e.g., CSI-RS transmission instance).

[0120] A WTRU may perform prediction of parameters of paths included in the tracking set, where the prediction may be performed in one or more (e.g., any) of the following approaches. Performing prediction of parameters may include joint prediction of one or more (e.g., all) parameters associated with a path. In examples, for each path in the tracking set, the WTRU may use a prediction model (e.g., the same prediction model), where the observation buffer stores the historical samples of the estimated parameters for that path, and/or may predict one or more instances of the path parameters, for the configured prediction window. In examples, for an observation window length of K samples, the observation buffer may store the most recent K historical tuples of (AoA, AoD, path gain, Doppler, path delay) for that path.

Performing prediction of parameters may include separate prediction for each parameter associated with a path. For example, to predict the future instances of AoA, AoD, path gain, Doppler, and/or path delay associated with a path in the tracking set, the WTRU may use separate prediction models (e.g., possibly one for each parameter). For example, when predicting future instances of the AoA using a model dedicated for AoA prediction, the observation buffer may store the most recent K values of the estimated AoA parameter for that path. The model may predict one or more future instances of the AoA for that path, as configured.

[0121] The WTRU may use the predicted parameters of paths in the tracking set, to determine a second (e.g., reporting) set of paths to be reported, for example, to reduce the CSI feedback overhead. The WTRU may use a second criteria to determine the reporting set and/or may apply one or more (e.g., any) of the following mechanisms. The WTRU may include (e.g., only include) in the reporting set, the paths (and/or their corresponding parameters) with the gain exceeding a third configured threshold (e.g., most significant paths). The WTRU may make this determination for each prediction instance in the prediction window. The WTRU may include in the reporting set, paths within the tracking set that exceed a fourth configured threshold for a configured number of instances within the respective observation window. For the determination of the reporting set, the WTRU may include paths from the tracking set with the associated flag cleared (e.g., paths newly added to the tracking set may not be used in the determination of the reporting set). The WTRU may determine the reporting set as a function of resources available for CSI feedback reporting. For example, the WTRU may include in the reporting set the strongest N_{p UL} paths, such that the memory requirements associated with the parameter reporting of the N_{p UL} paths fits in the available feedback resources. The WTRU may determine to increase the size of the reporting set (e.g., include more predicted paths (and/or their corresponding parameters) from the tracking set), as a function of the ACK/NACK statistics and/or the block error rate (BLER), for example when the WTRU detects that the BLER increases above a configured threshold. The WTRU may be configured with priority rules, to determine the reporting set for a multi-part report. For example, the WTRU may include the most significant path in part 1 of the CSI report and/or may include lower power paths (and/or the corresponding path parameters) in part 2 of the CSI report.

[0122] Embodiments described herein may relate to channel parameter reporting. In examples, the WTRU may be configured to perform channel parameter estimation based on a preconfigured condition. Such condition may be expressed as a minimization or maximization objective, given a set of constraints. In examples, the WTRU may be configured with plurality of preconfigured conditions - wherein each preconfigured condition may enable parameter estimation specific to a use case. For example, the WTRU may apply a first condition to determine channel parameters for CSI compression use case. For example, the WTRU may apply a second condition to determine channel parameters for beam management (BM) use case. For example, the WTRU may apply a third condition to determine channel parameters for positioning and/or sensing use case. For example, the WTRU may apply a fourth condition to determine channel parameters for mobility and/or radio resource management (RRM) use case. For example, the WTRU may apply a fifth condition to determine channel parameters for data collection and/or performance monitoring, etc.

[0123] In examples, the WTRU may be configured to estimate channel parameters associated with channel response based on preconfigured decomposition model. The WTRU may determine one or more channel parameters so that the difference between estimated model and the decomposition based on channel parameters are minimized. The WTRU may be configured to determine one or more channel parameters associated with a future time instance. The WTRU may be configured to report a subset of the predicted channel parameters.

[0124] In examples, the WTRU may be configured to report on one or more channel parameters from a preconfigured set. In examples, the WTRU may be configured to report on one or more channel parameters from a reporting set. For example, such report may be configured for CSI reporting. For example, such reporting may be configured for CSI mismatch verification. For example, such reporting may be configured for data collection. In examples, the WTRU may be configured to report one or more channel parameters from the tracking set. For example, such report may be configured for performance monitoring at the gNB side. In examples, the WTRU may be configured to report statistics of one or more channel parameters from the tracking set and/or reporting set. For example, the WTRU may report distribution of number of paths, path gains, AoD, AoA, and/or delay, etc. For example, such report may be configured for data collection. For example, such report may be configured for generating data for downstream model life cycle management including, but not limited, to training, monitoring, and/or fine-tuning, etc.

[0125] In examples, the WTRU may be configured to report channel parameters when one or more preconfigured conditions are satisfied. In examples, the WTRU may be configured with different trigger conditions to report different channel parameters. These conditions may be in part based on the number, value range, and/or status of channel parameters in the reporting set. For example, the WTRU may report channel parameters when another (e.g., new) path is added to the reporting set. For example, the WTRU may report channel parameters when an existing path is removed from the reporting set. For example, the WTRU may report channel parameters for the paths that stay in the reporting set for a preconfigured time duration. For example, the WTRU may report channel parameters when one or more paths in the reporting set satisfy a preconfigured threshold, wherein the threshold may be expressed as a range of AoA, AoD, path gain, and/or delay, etc. For example, the WTRU may report channel parameters when one or more paths in the reporting set change by an offset compared to the previous reporting, where the offset may be expressed as a difference in AoA, AoD, path gain, and/or delay, etc. In examples, the WTRU may be configured to report channel parameters upon a change in one or more of additional conditions. Such additional conditions may be associated with Al model operation. For example, the WTRU may trigger channel parameter reporting when one or more measurements (e.g., reference signal received power (RSRP), reference signal strength indicator (RSSI), reference signal received quality (RSRQ), rank indicator (Rl), PMI, channel quality indicator (CQI), signal to noise interference ratio (SINR), doppler spread, doppler shift, delay spread, average delay, position coordinates, WTRU speed) is above or below a threshold. For example, the WTRU may trigger channel parameter reporting when it detects a change from non-LOS (NLOS) to LOS and/or vice versa. For example, the WTRU may trigger channel parameter reporting upon a change in antenna port configuration, bandwidth part (BWP) configuration, secondary cell (SCell) addition/removal, BWP switch, beam failure, and/or beam recovery, etc.

[0126] In examples, the WTRU may transmit the channel parameters as a part of CSI feedback. Such reporting may be periodic, semi-persistent, and/or event triggered. For example, the WTRU may be configured with a CSI reporting type that indicates if channel parameters are to be transmitted. For example, the WTRU may be configured with a CSI report quantity that indicates if channel parameters are to be transmitted and/or what type of channel parameters are to be transmitted. In examples, the WTRU may be configured to report the channel parameters (e.g., periodically) based on expiry of a preconfigured timer. In examples, the WTRU may be configured to report the channel parameters (e.g., periodically) where the periodicity may be (e.g., implicitly) configured based on the periodicity of a preconfigured reporting resource. In examples, the WTRU may be configured to report the channel parameters (e.g., periodically) where the periodicity may be (e.g., implicitly) configured based on the periodicity of a RS (e.g., CSI-RS) configured for channel parameter estimation. In examples, the WTRU may be configured to report one or more (e.g., all) the channel parameters with same periodicity. In examples, the WTRU may be configured to report different channel parameters at different periodicity.

[0127] In examples, the WTRU may be configured to report channel parameters upon receiving an aperiodic trigger from the NW. For example, such aperiodic request message may indicate how many paths to be reported. The WTRU may be configured to report top-N paths, wherein the value of N may be indicated in the aperiodic request. For example, such aperiodic request message may indicate criteria for what paths may be reported. For example, such criteria may be expressed based on range of AoA, AoD, path gain, and/or delay values, etc.

[0128] In one or more examples herein, the WTRU may report channel parameters in a configured reporting resource. The reporting resource may be physical uplink control channel (PUCCH) and/or a physical uplink shared channel (PUSCH). In examples, the resources configured for channel parameter reporting may be a function of number and/or type of channel parameters. In examples, the WTRU may report channel parameters in an uplink control information (UCI), a medium access control control element (MAC CE), and/or a RRC message. For example, the WTRU may report dynamic change in channel parameters in a UCI. For example, the WTRU may report semi-static change in channel parameters in a MAC CE. For example, the WTRU may report long term statistics of channel parameters in a RRC message.

[0129] Embodiments described herein may relate to CSI compression basd on channel parameter estimation.

[0130] The WTRU may be configured to receive CSI-RS to be used for channel estimation purposes. The WTRU may be configured to process the estimated channel to determine and/or estimate one or more of the channel parameters. The channel parameters may include the number of paths, N_p, the angle of arrival (AoA) 0_fc associated with the fc-th path, the angle of departure (AoD) 4>_k associated with the fc-th path, the gain b_k associated with the Ar -th path, for k =1,.. , N_p. The WTRU may be configured to determine and/or report the number of the dominant paths P, where P may be less than the total number of paths N_p. In examples, the dominant P paths may have the highest gains across one or more (e.g., all) N_p paths. The WTRU may be configured with one or more parameters associated with the channel parameters. For example, the WTRU may be configured with the maximum number of paths to report. For example, the WTRU may be configured with a specific range for the AoAs, AoDs, and/or the paths gains. The WTRU may be configured with one or more performance metric to determine one or more of the channel parameters. For example, the WTRU may be configured with a reconstruction performance threshold. This may assist the WTRU to determine the CSI reporting format, for example, model-free (e.g., an AI/ML model may not be used and/or the channel parameters are directly reported) , or model-based format (e.g., model based reporting utilizes an AI/ML model for the CSI feedback/reporting).

[0131] In examples, the WTRU may be configured with one or more CSI reporting formats. The first CSI reporting format may include (e.g., only) the channel parameter (e.g., number of paths, AoAs, AoDs, path gains). The second CSI reporting format may include a compressed version of the CSI (e.g., possibly preprocessed). The compression may be performed using a two-sided AI/ML model. The CSI reporting format may be configured (e.g., explicitly) in a DCI field, RRC message, MAC CE, etc. In examples, the CSI reporting format may be (e.g., implicitly) configured as a function of one or more (e.g., some) other configured parameter(s) (e.g., carrier frequency, sub band size, number of transmit/receive ports). In examples, the CSI reporting format may be configured as a function of the UL feedback resource configuration.

[0132] The WTRU may be configured to determine the channel parameters based on one or more measurements. For example, given the estimated channel H, the WTRU may determine the number of paths as a function of the estimated channel (e.g., N_p For example, f(W) may represent the number of non-zero eigenvalues of the channel H. For example, /(//) may represent the number of N_p elements with energy greater than a configured threshold where the energy may be defined by the projection of H on the DFT matrix B. For example, e =diag(|B^H HH^H B |) where diag(.) may return the diagonal of a given square matrix, and/or B may be the transmit codebook (e.g., Discrete Fourier Transformation (DFT) based codebook, and/or a codebook including of a set of transmit beams). The WTRU may determine N_p as the number of elements in the energy vector e with energy greater than a configured threshold. In examples, the WTRU may be configured to determine the number of dominant paths P, where P < N_P. For example, the WTRU may be configured with a first threshold and/or a second threshold, where the WTRU may determine the number of paths based on the first threshold and/or the number of dominant paths based on the second threshold. In examples, the second threshold may be greater than the first threshold since the number of dominant paths may have higher gains relative to the rest of paths.

[0133] In examples, the WTRU may determine the paths gains, angle of arrivals, and/or angle of departure based on solving the following optimization problem: wherein N_p may be determined based on one of the mentioned approaches (e.g., eigenvalues-based and/or projection-based) described herein. The optimization problem (e.g., as described herein) may be solved based on one or more of the methods described herein. In examples, the WTRU may solve the optimization problem using the number of dominant paths P (e.g., as opposed to the number of paths N_p~). In examples, the WTRU may solve the optimization problem for a maximum number of configured paths and/or may report (e.g., only) the paths with gains satisfying a certain configured threshold.

[0134] The WTRU may be configured to select and/or determine the CSI processing format as a function of the estimated parameters. The CSI formats may include a first format and/or a second format. The first format may include the channel parameters, (e.g., also) referred to as model-free compression. The second format may include the compressed CSI (e.g., using two-sided AI/ML model), (e.g., also) referred to as model-based compression. The WTRU may determine the CSI reporting format as a function of the channel parameters. For example, the WTRU may select the model-free format if the number of dominant paths is below a configured threshold. For example, the WTRU may select the model-free format if the reconstruction quality using a specific number of paths is above one or more (e.g., some) configured thresholds. For example, the WTRU may select the model-free format if the determined AoAs and AoDs are within a configured range. For example, the WTRU may select the model-free format based on the link type (e.g., line of sight).

[0135] In examples, the WTRU may select the model-based CSI reporting format if one or more (e.g., any) of the (e.g., above) conditions are violated. The WTRU may perform model-based compression as a function of channel parameters (e.g., delay spread and/or number of paths). For example, the WTRU may select a two-sided AI/ML model for CSI compression based on the number of determined, (e.g., possibly) dominant, paths, exceeding a preconfigured threshold. In examples, the WTRU may select the compression model based on the determined range of the AoA and/or AoD.

[0136] In examples, the WTRU may be configured to select and/or determine the post-processing type based on the selected CSI reporting format. For example, if the determined CSI reporting format is model- free, the WTRU may apply one or more of the following post-processing. The WTRU may apply different post-processing for one or more (e.g., each) determined paths. For example, the first/dominant path information (e.g., , gain, AoA, and/or AoD) may use higher number of quantization bits relative to other paths. In examples, the first K paths may use higher quantization bits relative to the other N_p- K paths, where K may be configured. The WTRU may use one or more (e.g., a number of) quantization bits that is proportional to the gain associated with each path. In examples, the number of quantization bits may be obtained as a function of the determined AOA and/or AoD range. The WTRU may be configured to attach different cyclical redundancy check (CRC) based on the path priority. For example, higher gain paths may be using higher number of redundancy bits relative to lower gain paths. For example, the WTRU may be configured with a gain threshold, where the paths with higher gain above the threshold may be encoded with higher number of bits compared to the paths with gains below the threshold.

[0137] In examples, the WTRU may be configured and/or indicated to report one or more of the following associated with the channel parameters: the CSI reporting format, the channel parameters (e.g., number of paths, AoAs, AoDs, paths gains), and/or performance metric(s) associated with the reconstruction quality of the channel from the determined channel parameters. The WTRU may be configured with resources for reporting the channel parameters (e.g., periodically), for example, every N slots. The WTRU may be configured to transmit the channel parameters in one or more of UCI, MAC CE, etc. In examples, the channel parameters may be reported as separate part of the CSI report. For example, a first part may include CQI, Rl, CSI-RS resource indicator (CRI). A second part may include the channel parameters (e.g., number of paths, AoAs, AoDs and/or paths gains), and/or post-processing information (e.g., quantization type associated with each path). The WTRU may report the model-based CSI compression in the second part along with the determined number of dominant paths.

[0138] Embodiments described herein my relate to monitoring CSI compression performance using channel parameter estimation.

[0139] AI/ML based methods for CSI feedback may be based (e.g., rely) on auto-encoders to compress the CSI and/or to report it to the gNB. In cases where the auto-encoder performance for CSI reconstruction may be poor (which may be due to the CSI matrix being out of distribution or other reasons), it may be challenging to verify whether the reconstructed CSI at gNB is a good representation of the actual CSI.

Using the channel parameter estimation framework, for example, the CSI matrix can be decomposed into a compressed path-wise presentation. Additionally or alternatively (e.g., in addition to the AIML based compressed CSI feedback), the parameters associated with one or more paths could be sent back to the gNB (e.g., to validate if the AIML based reconstructed (e.g, decompressed) CSI does incorporate the specified path).

[0140] In examples aimed at enabling the performance monitoring using the channel parameter estimation framework, the WTRU may (e.g, further) be configured with the channel parameter estimation method . This may be done to ensure the same parameter estimation methodology is being utilized at (e.g, both) the WTRU side and/or the network side. The gNB may configure the WTRU with the channel parameter estimation method (e.g, deep learning based, optimization based, OMP, etc.).

[0141] For the configured channel parameter estimation method, the WTRU may (e.g, further) be configured with other parameters to enable the method. For example, in the deep learning-based method, the WTRLI may be configured with the (e.g., exact) deep learning model and/or its weights; in the optimization-based method, the WTRU may be configured with the number of over-parametrized paths and/or the sparsity related parameters. In the OMP based method, the additional configurations may be with regard to the dictionary of array response vectors (e.g., number depends on granularity) and/or the stopping criterion and/or convergence criterion.

[0142] The WTRU may (e.g., further) be configured with different methods and/or rule sets to enable performance monitoring and/or verification. In examples, the WTRU may be configured to report one or more (e.g., all) parameters associated with the strongest multipath (e.g., AoA, AOD, gain, doppler, etc.). In examples, the WTRU may be configured to report a subset of parameters associated with the strongest path.

[0143] In examples, the information about one or more (e.g., all) the parameters of the parameters may be set for a specifically and/or randomly selected path and/or a group of paths.

[0144] In examples, the WTRU may report information pertaining to a single parameter (e.g., AoA, gain, AOD, etc.) across one or more (e.g., all) the estimated paths. In examples, the WTRU may report information pertaining to a single parameter (e.g, AoA, gain, AOD, etc.) but (e.g, only) across a subset of the estimated paths.

[0145] In examples, the WTRU may report information pertaining to different parameters from different paths. For example, for one path the AOA may be reported; for another path the AoD may be reported; and/or for another path (e.g, only) the gain may be reported.

[0146] Post configuration, in the operation stage, the WTRU may receive the reference symbols (CSI-RS) and/or may perform channel estimation. Once the channel is estimated, for example, the cannel parameter estimation method may be utilized to estimate the actual number of paths in the channel and/or the parameters (e.g. AoA, ZoA, AoD, ZoD, path gain, path delay, Doppler) associated with each of the N_p paths.

[0147] The WTRU may utilize the configured performance monitoring method to select the set of paths and/or the set of parameters corresponding to each path, that may (e.g, need to) be reported.

[0148] In examples, the selected paths may have an ordering/ranking/priority associated with each path and/or the set of parameters corresponding to the path with a higher priority may be quantized with a larger number of bits and/or the set of parameters corresponding to the path with a lower priority may be quantized with a fewer number of bits. [0149] In examples, the set of parameters corresponding to the path with a higher priority may be protected with a larger number of error protection bits and/or redundancy bits and/or the set of parameters corresponding to the path with a lower priority may be protected with a fewer number of error protection bits and/or redundancy bits.

[0150] In examples, one or more (e.g., some) parameters may be considered to be more important than the others and/or may be quantized with a larger number of bits and/or may be error protected with a larger number of bits. For example, the AoA and/or AOD may be considered more important and/or the path delay and/or doppler may be considered less important, (e.g., thus) allocating a larger number of bits for quantizing and/or protecting AoA and/or AOD.

[0151] The performance monitoring/verification-based reporting may be performed at regular (e.g., periodic) and/or aperiodic intervals. In examples, the reporting for performance monitoring and/or verification may be done at the same interval as the CSI feedback and/or reporting. CSI feedback may be accompanied with parameters for monitoring. In examples, the performance monitoring report may be sent (e.g., once) for every N CSI feedback reporting instances. In examples, the performance monitoring reports may be sent aperiodically and/or may be triggered by an event, for example, if the overall throughput drops below a threshold and/or if a hybrid automatic repeat request (HARQ)ZNACK request is issued. In examples, the performance monitoring reporting may be sequential, so a few parameters corresponding to one or more paths may be sent initially and/or additional parameters may be sent based on triggers from the network.

[0152] The WTRU may send the CSI feedback report and/or the parameter(s) related to performance monitoring and/or verification to the network. The network may reconstruct the CSI based on the CSI feedback and/or may utilize a channel parameter estimation method to estimate the paths and/or the parameters associated with each path and/or may compare these parameters with the ones reported by the WTRU to check the performance of the CSI feedback framework.

[0153] Methods for channel parameter prediction may be described herein. For example, method(s) for parameterizing channel into low dimensional explainable components and/or determining future values of these components and/or reporting to the network may be described herein. The WTRU may determine a subset of channel parameters to report, for example, based on measurements, to reduce complexity of reporting complete CSI.

[0154] A WTRU may receive configuration associated with channel parameters to be selected and/or reported, including transmission path, AoA, AoD, path gain, doppler range, and/or delay spread range. The WTRU may (e.g., also) be configured with criteria for channel parameter selection and/or reporting, including: Minimizing/maximizing a preconfigured criteria/model (e.g., |H - 2) | ) under the constraints/bounds configured for parameters (e.g., maximum number of paths/rank, threshold for number of paths, AoA and/or AoD range, range for gains, doppler range, and/or delay spread range). A WTRU may receive configuration information. The configuration information may include an indication of a set of channel parameters (e.g., to be estimated and/or tracked and/or reported), associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and/or second criteria associated with reporting. The plurality of paths may be fewer than a number of paths in a CSI matrix. The WTRU may determine the prediction channel parameters, for example, based on the (e.g., first) criteria. The prediction channel parameters may be more than the measured channel parameters. The prediction channel parameters may be less than the measured channel parameters.

[0155] The WTRU may be configured with a first criteria to determine a first set of channel parameters for a first set of paths and/or a second criteria to determine a second set of channel parameters for a second set of paths. The first set of channel parameters may be for a Tracking set of paths. The first of channel parameters may include the set of parameters corresponding to valid paths in the channel that may be (e.g., need to be) tracked. The (e.g., first) set of channel parameters may include one or more of: a transmission path, an angle of arrival (AoA) (e.g. along the azimuth and/or elevation axes), an angle of departure (AoD) (e.g. along the azimuth and/or elevation axes), a path gain, a doppler range, and/or a delay spread. For example, the WTRU may use the first criteria to determine the valid paths in the channel based on one or more of: the max number of paths to be tracked, AoA/AoD is within a first range, the gain is greater than a first threshold, etc. For example, first criteria may include a first path gain threshold for adding paths to tracking set. For example, first criteria may include a second path gain threshold for removing paths from tracking set. For example, first criteria may include a first AoA and AoD range for adding paths to tracking set. For example, first criteria may include a second AoA and AoD range for removing paths from tracking set. For example, first criteria may include a time window and/or interval during which the criteria are evaluated. For example, first criteria may include an observation window length N and/or a prediction window length L. The second set of channel parameters may be a reporting set of paths that include the set of parameters corresponding to the (e.g., most) useful paths in the channel that may (e.g., need to) be reported. The WTRU may use the second criteria to determine the (e.g., most) useful paths in the channel based on one or more of: dominant path (e.g., gain above a threshold); the time within tracking set above a second threshold; one or more rules based on available uplink (UL) resources (e.g., select maximum number of paths < the available UL resources); prioritization rules (e.g., number of parts as function of priority of CSI report (e.g., higher P value for high priority CSI report and/or low P value for low priority CSI report)); a compression factor (e.g., number of parts as a function of compression factor); performance metric(s) (e.g., reconstruction performance, link performance, acknowledgment (ACK)/ negative ACK (NACK) count, etc.); and/or based on the CSI rank. For example, the second criteria may include one or more of: a gain above a threshold, a time associated with how long each path remains in the plurality of paths, one or more rules based on available uplink resources, one or more prioritization rules, a compression factor, one or more performance metrics, and/or a CSI rank value. The WTRU may determine the second subset of the plurality of paths based on the second criteria.

[0156] A WTRU may receive CSI-RS, may perform channel estimation, and/or may determine the channel parameters including actual number of paths in the channel N_p and/or parameters associated with one or more (e.g., each) of the N_p paths (e.g., AoA 6_k, AoD (p_k, gain b_k, f_k doppler, and/or 8_k delay). The channel parameter estimation criteria |H - h_fca_fi(0_k)a^( _k) | may be minimized. For example, the WTRU may receive one or more CSI-RSs. The WTRU may determine the channel parameter(s) associated with the first subset of the plurality of paths, for example, based on the received CSI-RS(s).

[0157] A WTRU may apply the first criteria to determine the set of paths and/or the parameters associated with each of the paths forming the first (e.g., tracking) set (e.g., adding parameters that satisfy the first criteria to the first set, removing parameters that do not satisfy the first criteria from the set). First criteria may include WTRU side conditions (e.g., memory, processing availability, etc.). For example, the WTRU may determine a first subset of the plurality of paths based on values of channel parameters associated with the first subset of the plurality of paths and/or the first criteria. The first set of channel parameters may be associated with a first time period. The WTRU may determine one or more values of the channel parameters for each path of the plurality of paths. The WTRU may determine the first subset of the plurality of paths based on a comparison of the first criteria and the one or more values of the channel parameters for each path of the plurality of paths.

[0158] For one or more (e.g., each) prediction instance(s) t (e.g., possibly same or different from CSI-RS periodicity) and/or for one or more (e.g., each) paths in the first set and/or determined subset of channel parameters for each paths in the first set, the WTRU may obtain the predicted channel parameters of the paths in the first set at future time instance t-d_. For example, the WTRU may determine one or more values of predicted channel parameters for each path of the first subset of paths. The one or more values of the predicted channel parameters may be associated with a second time period. The second time period may be different from the first time period. The second time period may be concurrent with a periodicity associated with CSI-RS transmission.

[0159] The WTRU may apply the second criteria to determine the set of paths forming the second (e.g., reporting) set of paths. The WTRU may determine the (e.g., predicted) channel parameters associated with the second set based on the predicted channel parameters of the paths in the first set. For example, the WTRU may determine a second subset of the plurality of paths based on the second criteria and/or the one or more values of the predicted channel parameters for each path of the first subset of paths. The second subset of paths may be a subset of the first subset of paths. The WTRU may determine one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths. The WTRU may determine the second subset of the plurality of paths based on a comparison of the second criteria and the one or more values of the prediction channel parameters for each path of the first subset of the plurality of paths. The WTRU may determine a subset of values associated with the second subset of the plurality of paths.

[0160] The WTRU may report the (e.g., predicted) channel parameters associated with the second (e.g, reporting) set (e.g, in CSI report). The report may include the number of parameters in the second set. The WTRU may be configured to transmit the first set (e.g, statistics thereof) for performance monitoring. For example, the WTRU may send an indication that indicates the one or more values of the predicted channel parameters associated with the second subset of the plurality of paths. The WTRU may send an indication that indicates the subset of values associated with the second subset of the plurality of paths to send the indication. The indication may be indicative of a channel matrix associated with the downlink transmission. [0161] One or more (e.g, current) methods for CSI prediction may be based on (e.g, rely on) predicting parts of the CSI matrix (e.g, per sub-band, per TX/RX antenna, and/or any combination of these entities), and/or the entire CSI matrix across time slots. Irrespective of how the CSI matrix may be predicted, the CSI matrix may be affected by a combination of independently evolving multipath components and/or (e.g, thus) predicting the cumulative effect of these multipaths may be a (e.g, very) hard problem. Using the channel parameter estimation framework, the CSI matrix can be decomposed into independent propagation paths, (e.g, thus) allowing time domain prediction of one or more (e.g, each) path separately, which may be a (e.g, more) tractable problem. Decomposing each path as 6_k, (p_k, b_k, f_k, 8_k may reduce the complexity further, (e.g, thus) allowing for a smaller set of parameters that require prediction. Additionally or alternatively, the channel parameterization approach may enable interpretability of AI/ML model behavior. This approach of channel parameterization can be (e.g., further) leveraged for enhancing other aspects including CSI compression, performance monitoring, and/or the like. For example, the set of channel parameters may be determined based on one or more of: an orthogonal matching pursuit based determination of the multipath channel (MPC) parameter(s), a deep learning-based MPC parameter determination, and/or an optimization function-based determination.

[0162] Embodiments described herein may relate to CSI compression based parameter estimation. The MIMO channel matrix can be utilized to estimate the information corresponding to one or more (e.g., all) the propagation paths that a transmitted signal may take to reach the receiver. AI/ML models may be utilized to recover these parameters efficiently and/or effectively. Having access to these parameters may be beneficial for the CSI feedback, beamforming, and/or CSI prediction tasks: parametrized channel can be better compressed for CSI reporting; and/or may allow access to fundamental raw information, which may applicable for one or more (e.g., multiple) procedures (e.g. angle of departure information may be used for downlink beamforming).

[0163] A WTRU may receive configuration associated with channel parameters to be estimated including criteria for channel parameter estimation (e.g., |H - ), bounds for parameters (e.g., maximum number of paths/rank, threshold for number of paths, AoA and AoD range, range for gains, doppler range, delay spread range, etc.), and/or methods and/or a rule set to be utilized for selecting the dominant path(s). For example, selecting the dominant path(s) may include: one or more rules based on available uplink (UL) resources (e.g., select maximum number of paths < the available UL resources); prioritization rules (e.g., number of parts as function of priority of CSI report (e.g., higher P value for high priority CSI report and/or low P value for low priority CSI report)); a compression factor (e.g., number of parts as a function of compression factor); performance metric(s) (e.g., reconstruction performance, link performance, acknowledgment (ACK)/ negative ACK (NACK) count, etc.); and/or based on the CSI rank.

[0164] A WTRU may receive CSI-RS, may perform channel estimation, and/or may determine the channel parameters including actual number of paths in the channel N_p and/or parameters associated with one or more (e.g., each) of the N_p paths (e.g., AoA 6_k, AoD (p_k, gain b_k, f_k doppler, and/or 8_k delay). The channel parameter estimation criteria |H - £^= may be minimized.

[0165] The WTRU may determine the dominant path(s) P for CSI feedback and/or beamforming. The determination may be based on a configured rule.

[0166] The WTRU may select the CSI reporting format as a function of a channel parameter (e.g., number of dominant paths). For example, if the number of dominant paths is below a threshold, (e.g., with respect to model-free), the WTRU may perform model-free CSI compression (e.g., may report the channel parameters p, 0_k, (p_k, b_k directly). For example, if the number of dominant paths is equal to or greater than a threshold (e.g., for larger number of dominant paths), the WTRU may perform one or more of the following. The WTRU may perform model-based CSI compression. The WTRU may perform model section as a function of channel parameters (e.g., model selection based on the number of paths P, input to the model (Eigenvector vs Full CSI) may be a function of channel parameter, model selection based on the AoA/AoD of the dominant paths, time domain vs frequency domain compression based on the delay spread, etc.).

[0167] The WTRU may select the post processing to apply, for example, based on type of CSI compression applied (e.g., model-free vs model-based). For example, in case of model free reporting, the WTRU may apply different post processing for each of the P paths. For example, the first (e.g., and/or strongest) path may be quantized with the highest bits and/or the P^th may be quantized with the lowest number of bits. For example, quantization bits may be proportional to the gain associated with each path. For example, error protection (e.g., redundancy bits) may be proportional to the priority of the paths. [0168] The WTRU may transmit the CSI feedback (e.g., in terms of parameterized channel) with P selected paths of the channel (e.g., in case of model-free operation). CSI feedback may indicate the number of paths (P) in report carrying compressed CSI with model-based methods.

[0169] Embodiments described herein may relate to monitoring CSI compression performance using channel parameter estimation. AI/ML based methods for CSI feedback may be based (e.g., rely) on autoencoders to compress the CSI and to report it to the gNB. In cases where the auto-encoder performance for CSI reconstruction is poor (e.g., which may be due to the CSI matrix being out of distribution or other reasons), there may be no way to identify and/or verify that whether the reconstructed CSI at gNB is a good representation of the actual CSI or not. For example, poor reconstruction performance may refer to the gap between the reconstructed CSI and actual CSI. For example, if the normalized mean square error (NMSE) between the actual CSI and reconstructed CSI is high, that may mean there is a high degree of error in the reconstructed CSI and/or the reconstruction is poor. Different metrics could be used for measuring the reconstruction performance and/or to quantify the error being introduced in the reconstructed CSI (e.g., NMSE, cosine similarity, squared generalized cosine similarity (SGCS), MSE, etc.). Using the channel parameter estimation framework, for example, the CSI matrix can be decomposed into a compressed pathwise presentation. Additionally or alternatively (e.g., in addition to the AI/ML based CSI feedback), the parameters associated with one or more paths may be sent back to the gNB and/or it may be validated if the AI/ML based reconstructed CSI does incorporate the specified path.

[0170] A WTRU may receive configuration associated with channel parameters to be estimated including criteria for channel parameter estimation (e.g. , |H - ), bounds for parameters (e.g., maximum number of paths/rank, threshold for number of paths, AoA and AoD range, range for gains, doppler range, delay spread range, etc.), and/or methods and/or a rule set to be utilized for selecting the verification paths (e.g., all and/or or selected parameters of the strongest path, all and/or selected parameters of a randomly selected path, all and/or selected parameters of multiple selected paths, only a specific parameter for all the paths (e.g., gain only only b_k, and/or AoA only p_k, etc., and/or different parameters from different paths).

[0171] Additionally or alternatively, the gNB may (e.g., explicitly) configure the WTRU with the channel parameter estimation method and/or one or more (e.g., any) parameters associated with these methods (e.g, optimization based estimation, deep learning-based estimation based, OMP based estimation).

[0172] A WTRU may receive CSI-RS, may perform channel estimation, and/or may determine the channel parameters including actual number of paths in the channel N_p and/or parameters associated with one or more (e.g, each) of the N_p paths (e.g, AoA 0_k, AoD <p_k, gain b_k, f_k doppler, and/or 8_k delay). The channel parameter estimation criteria |H - b_ka_R(0_fe)a^( _fc) | may be minimized.

[0173] The WTRU may select the path(s) and/or parameter(s) to be reported for verification. Path/parameter selection may be done based on the configured criterion. Each path and/or parameter may (e.g, further) be quantized before reporting. One or more (e.g, some) paths and/or parameters may be prioritized with more granularity than others.

[0174] The verification-based reporting may happen periodically at one or more (e.g, some) intervals and/or aperiodically (e.g, if the throughput drops below a threshold, trigger to send more paths if mismatch between sent parameters and estimated parameters is observed.

[0175] The WTRU may report CSI. For example, the WTRU may report the path(s) and/or parameter(s). [0176] One or more of the following abbreviations and/or acronyms may be included herein:

ACK Acknowledgement

BLER Block Error Rate

BWP Bandwidth Part

CAP Channel Access Priority

CAPC Channel access priority class

CCA Clear Channel Assessment CCE Control Channel Element

CE Control Element

CG Configured grant or cell group

CP Cyclic Prefix

CP-OFDM Conventional OFDM (relying on cyclic prefix)

CQI Channel Quality Indicator

CRC Cyclic Redundancy Check

CSI Channel State Information

CW Contention Window

CWS Contention Window Size

CO Channel Occupancy

DAI Downlink Assignment Index

DCI Downlink Control Information

DFI Downlink feedback information

DG Dynamic grant

DL Downlink

DM-RS Demodulation Reference Signal

DRB Data Radio Bearer eLAA enhanced Licensed Assisted Access

FeLAA Further enhanced Licensed Assisted Access HARQ Hybrid Automatic Repeat Request

LAA License Assisted Access

LBT Listen-Before-Talk

LTE Long Term Evolution e.g. from 3GPP LTE R8 and up

NACK Negative ACK

MCS Modulation and Coding Scheme

MIMO Multiple Input Multiple Output

NR New Radio

OFDM Orthogonal Frequency-Division Multiplexing PHY Physical Layer

PID Process ID

PO Paging Occasion

PRACH Physical Random-Access Channel PSS Primary Synchronization Signal

RA Random Access (or procedure)

RACH Random Access Channel

RAR Random Access Response

RCU Radio access network Central Unit

RF Radio Front end

RLF Radio Link Failure

RLM Radio Link Monitoring

RNTI Radio Network Identifier

RO RACH occasion

RRC Radio Resource Control

RRM Radio Resource Management

RS Reference Signal

RSRP Reference Signal Received Power RSSI Received Signal Strength Indicator

SDU Service Data Unit

SRS Sounding Reference Signal

SS Synchronization Signal

SSS Secondary Synchronization Signal

SWG Switching Gap (in a self-contained subframe)

SPS Semi-persistent scheduling.

SUL Supplemental Uplink

TB Transport Block

TBS T ransport Block Size

TRP Transmission I Reception Point

TSC Time-sensitive communications

TSN Time-sensitive networking

UL Uplink

URLLC Ultra-Reliable and Low Latency Communications

WBWP Wide Bandwidth Part

WLAN Wireless Local Area Networks and related technologies (IEEE 8O2.xx domain)

Claims

CLAIMS:

1 . A wireless transmit/receive unit (WTRU) comprising: a processor configured to: receive configuration information, the configuration information comprising an indication of a set of channel parameters associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and second criteria associated with reporting; determine a first subset of the plurality of paths based on values of channel parameters associated with the first subset of the plurality of paths and the first criteria, wherein the first set of channel parameters are associated with a first time period; determine values of predicted channel parameters for each path of the first subset of paths, wherein the values of predicted channel parameters are associated with a second time period that is different from the first time period; determine a second subset of the plurality of paths based on the second criteria and the values of the predicted channel parameters for each path of the first subset of paths, wherein the second subset of the plurality of paths is a subset of the first subset of the plurality of paths; and send an indication that indicates the values of the predicted channel parameters associated with the second subset of the plurality of paths.

2. The WTRU of claim 1 , wherein the processor is configured to: determine values of the channel parameters for each path of the plurality of paths; and determine the first subset of the plurality of paths based on a comparison of the first criteria and the values of the channel parameters for each path of the plurality of paths.

3. The WTRU of claim 1 , wherein the processor is configured to: determine values of the prediction channel parameters for each path of the first subset of the plurality of paths; and determine the second subset of the plurality of paths based on a comparison of the second criteria and the values of the prediction channel parameters for each path of the first subset of the plurality of paths.

4. The WTRU of claim 1 , wherein the second time period is concurrent with a periodicity associated with channel state information (CSI) reference signal (CSI-RS) transmissions.

5. The WTRU of claim 1 , wherein the processor is configured to: receive one or more channel state information (CSI) reference signals (CSI-RSs); and determine the channel parameters associated with the first subset of the plurality of paths based on the received CSI-RSs.

6. The WTRU of claim 1 , wherein the processor is configured to determine the prediction channel parameters based on the first criteria.

7. The WTRU of claim 1 , wherein the processor is configured to determine a subset of values associated with the second subset of the plurality of paths, and wherein the processor is configured to send an indication that indicates the subset of values associated with the second subset of the plurality of paths to send the indication.

8. The WTRU of claim 1 , wherein the plurality of paths is fewer than a number of paths in a channelstate information (CSI) matrix.

9. The WTRU of claim 1 , wherein the set of channel parameters comprises one or more of: a transmission path, an angle of arrival (AoA), an angle of departure (AoD), a path gain, a doppler range, or a delay spread.

10. The WTRU of claim 1 , processor is configured to update the first subset of paths of the plurality of paths or the second subset of paths of the plurality of paths based on one or more of: the first criteria, the second criteria, a time window during which the first criteria is evaluated, a configured prediction window, or an observation window length.

11. A method performed by a wireless transmit/receive unit (WTRU), the method comprising: receiving configuration information, the configuration information comprising an indication of a set of channel parameters associated with a plurality of paths of a downlink transmission, first criteria associated with tracking, and second criteria associated with reporting; determining a first subset of the plurality of paths based on values of channel parameters associated with the first subset of the plurality of paths and the first criteria, wherein the first set of channel parameters are associated with a first time period; determining values of predicted channel parameters for each path of the first subset of paths, wherein the values of predicted channel parameters are associated with a second time period that is different from the first time period; determining a second subset of the plurality of paths based on the second criteria and the values of the predicted channel parameters for each path of the first subset of paths, wherein the second subset of the plurality of paths is a subset of the first subset of the plurality of paths; and sending an indication that indicates the values of the predicted channel parameters associated with the second subset of the plurality of paths.

12. The method of claim 11 , further comprising: determining values of the channel parameters for each path of the plurality of paths; and determining the first subset of the plurality of paths based on a comparison of the first criteria and the values of the channel parameters for each path of the plurality of paths.

13. The method of claim 11 , further comprising: determining values of the prediction channel parameters for each path of the first subset of the plurality of paths; and determining the second subset of the plurality of paths based on a comparison of the second criteria and the values of the prediction channel parameters for each path of the first subset of the plurality of paths.

14. The method of claim 11 , wherein the second time period is concurrent with a periodicity associated with channel state information (CSI) reference signal (CSI-RS) transmissions.

15. The method of claim 1 , further comprising: receiving one or more channel state information (CSI) reference signals (CSI-RSs); and determining the channel parameters associated with the first subset of the plurality of paths based on the received CSI-RSs.

16. The method of claim 11 , further comprising determining the prediction channel parameters based on the first criteria.

17. The method of claim 11 , further comprising determining a subset of values associated with the second subset of the plurality of paths, and wherein sending the indication comprises sending an indication that indicates the subset of values associated with the second subset of the plurality of paths.

18. The method of claim 11 , wherein the plurality of paths is fewer than a number of paths in a channel-state information (CSI) matrix.

19. The method of claim 11 , wherein the set of channel parameters comprises one or more of: a transmission path, an angle of arrival (AoA), an angle of departure (AoD), a path gain, a doppler range, or a delay spread.

20. The method of claim 1 , further comprising updating the first subset of paths of the plurality of paths or the second subset of paths of the plurality of paths based on one or more of: the first criteria, the second criteria, a time window during which the first criteria is evaluated, a configured prediction window, or an observation window length.