WO2024064534A1 - Commande et politique de formation de faisceau sans grille de faisceaux (gob) sur l'interface e2 - Google Patents

Commande et politique de formation de faisceau sans grille de faisceaux (gob) sur l'interface e2 Download PDF

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Publication number
WO2024064534A1
WO2024064534A1 PCT/US2023/073748 US2023073748W WO2024064534A1 WO 2024064534 A1 WO2024064534 A1 WO 2024064534A1 US 2023073748 W US2023073748 W US 2023073748W WO 2024064534 A1 WO2024064534 A1 WO 2024064534A1
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WIPO (PCT)
Prior art keywords
ran
control
network
data
beamforming
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PCT/US2023/073748
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English (en)
Inventor
Jaemin HAN
Nicholas Whinnett
Dawei YING
Leifeng RUAN
Jan Schreck
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Intel Corporation
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Publication of WO2024064534A1 publication Critical patent/WO2024064534A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0686—Hybrid systems, i.e. switching and simultaneous transmission
    • H04B7/0689—Hybrid systems, i.e. switching and simultaneous transmission using different transmission schemes, at least one of them being a diversity transmission scheme
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/12—Access point controller devices

Definitions

  • Various embodiments generally may relate to the field of wireless communications. For example, some embodiments may relate to beam forming control and policy.
  • Various embodiments generally may relate to the field of wireless communications.
  • Figure 1 schematically illustrates a wireless network in accordance with various embodiments.
  • FIG. 2 schematically illustrates components of a wireless network in accordance with various embodiments.
  • Figure 3 is a block diagram illustrating components, according to some example embodiments, able to read instructions from a machine-readable or computer-readable medium (e.g., a non-transitory machine-readable storage medium) and perform any one or more of the techniques, processes, and/or methods discussed herein.
  • a machine-readable or computer-readable medium e.g., a non-transitory machine-readable storage medium
  • FIG. 4 provides a high-level view of an Open RAN (O-RAN) architecture, in accordance with various embodiments.
  • O-RAN Open RAN
  • Figure 5 shows the Uu interface between a UE and O-e/gNB as well as between a UE and O-RAN components, in accordance with various embodiments.
  • FIG. 6 illustrates a network in accordance with various embodiments.
  • Figure 7 illustrates a simplified block diagram of artificial (Al)-assisted communication between a UE and a RAN, in accordance with various embodiments.
  • Figure 8 depicts an example procedure for practicing the various embodiments discussed herein.
  • Figure 9 depicts another example procedure for practicing the various embodiments discussed herein.
  • Open radio access network may incorporate components of artificial intelligence (Al) and/or machine learning (ML) (note that “Al and/or ML” may be abbreviated to “AI/ML” herein) based intelligence into wireless communication networks.
  • AI/ML artificial intelligence
  • Introduction of AI/ML may not only to increase performance of existing networks, but also optimize and/or steer various network components to one or more identified key performance indicators (KPIs) of interest in an efficient and elegant way.
  • KPIs key performance indicators
  • Massive multiple-input/multiple-output (mMIMO) optimization may provide various benefits.
  • Non-grid-of-beams (Non-GoB) beamforming approaches have been identified as an important class of beamforming algorithms for fifth generation (5G) mMIMO deployments.
  • Embodiments herein may relate to various requirements for radio access network (RAN) intelligence controller (RIC) and RAN nodes to support this AI/ML based Non-GoB beamforming optimization over an E2 interface.
  • RAN radio access network
  • RIC radio access network intelligence controller
  • RAN nodes to support this AI/ML based Non-GoB beamforming optimization over an E2 interface.
  • an E2 interface terminates at a plurality of E2 nodes.
  • the E2 nodes are logical nodes/entities that terminate the E2 interface.
  • CONTROL and/or POLICY service may be used to control Non-GoB beamforming mode for a UE:
  • Embodiments herein provide enhancements to support the above requirement, and may be based on the E2SM-RC specification (which may stand for E2 Service Model - RAN Control).
  • the enhancements described in this disclosure may enable a RIC to send a control command or policy command to RAN nodes that can configure, reconfigure, or release Non-GoB beamforming mode for UEs of interest, which may be desirable for supporting various O-RAN related AI/ML use cases.
  • Embodiment 1 Mechanisms for RIC to send a control command to configure, reconfigure, or release Non-GoB beamforming mode for a UE.
  • this mechanism can be implemented by defining a new CONTROL style in E2SM-RC that re-uses the legacy Control Header Format 1 and Control Message Format 1.
  • Some example implementations for the corresponding changes for E2SM-RC specification are as follows (note, the example changes may be indicated through the use of italicizatiory.
  • Control Service styles 1-9 listed above may adopt or relate to one or more of the following common features:
  • Control Action ID The index ID for the individual control action under a given Control Service style.
  • Control Action Name Indicates the functionality of the E2 node which is controlled by Near-RT RIC
  • Control Action Description Describes the control action and functionality of the receiving E2 Node.
  • Associated RAN parameters Identifies the RAN parameters to be controlled by Near-RT RIC pertaining to the given control action.
  • the Control Service style 255 supports multiple parallel actions configured per RIC Control Request message by reusing the control actions and the associated RAN parameters defined in the selected fundamental level Control Service style(s).
  • Example details of the individual Control Service styles are provided in subsequent sections (again, italicized to indicate elements that are being introduced to legacy specification portions).
  • This CONTROL Service style provides a mechanism to add, modify or delete beamforming configuration for a UE using the RIC Control Message IE and the RIC Control Header IE.
  • the supported RAN control actions and the corresponding RAN parameters are as follows:
  • the CONTROL Service RIC Control Header IE has the UE ID IE, the Control Service Style ID IE, the Control Action ID IE.
  • the RIC Control Decision IE for this service style is currently not supported for this control service style.
  • This CONTROL Service RIC Control Message IE contains the sequence of RAN parameters, associated with a given Control Action within this Control Service style.
  • This CONTROL style uses RIC Control Message IE Format 1 (9.2.1.7.1 ).
  • such mechanism could be implemented by re-using the legacy CONTROL service in E2SM-RC with addition of the corresponding RAN parameters as shown above.
  • Embodiment 2 Mechanisms for RIC to send a policy command to configure, reconfigure, or release Non-GoB beamforming mode for UEs of interest.
  • this mechanism can be implemented by defining a new POLICY style in E2SM-RC that re-uses the legacy Action Definition Format 2.
  • Some example implementations for the corresponding changes for E2SM-RC specification is as follows (with elements being introduced to the E2SM-RC specification indicated through italicization): /////////////////Example changes
  • This POLICY Service style provides an imperative policy to add, modify or delete beamforming configuration for a UE.
  • the RAN Parameters pertaining to POLICY Conditions for the “Beamforming Configuration Control” policy service style uses the RAN parameters defined in Sections 8.1 and 8.5.1.
  • such mechanism(s) may be implemented by re-using the legacy POLICY service in E2SM-RC with addition of the corresponding RAN parameters as shown above.
  • FIGS 1-7 illustrate various systems, devices, and components that may implement aspects of disclosed embodiments.
  • Figure 1 illustrates a network 100 in accordance with various embodiments.
  • the network 100 may operate in a manner consistent with 3GPP technical specifications for LTE or 5G/NR systems.
  • 3GPP technical specifications for LTE or 5G/NR systems 3GPP technical specifications for LTE or 5G/NR systems.
  • the example embodiments are not limited in this regard and the described embodiments may apply to other networks that benefit from the principles described herein, such as future 3GPP systems, or the like.
  • the network 100 may include a UE 102, which may include any mobile or non-mobile computing device designed to communicate with a RAN 104 via an over-the-air connection.
  • the UE 102 may be communicatively coupled with the RAN 104 by a Uu interface.
  • the UE 102 may be, but is not limited to, a smartphone, tablet computer, wearable computer device, desktop computer, laptop computer, in-vehicle infotainment, in-car entertainment device, instrument cluster, head-up display device, onboard diagnostic device, dashtop mobile equipment, mobile data terminal, electronic engine management system, electronic/engine control unit, electronic/engine control module, embedded system, sensor, microcontroller, control module, engine management system, networked appliance, machine-type communication device, M2M or D2D device, loT device, etc.
  • the network 100 may include a plurality of UEs coupled directly with one another via a sidelink interface.
  • the UEs may be M2M/D2D devices that communicate using physical sidelink channels such as, but not limited to, PSBCH, PSDCH, PSSCH, PSCCH, PSFCH, etc.
  • the UE 102 may additionally communicate with an AP 106 via an over-the-air connection.
  • the AP 106 may manage a WLAN connection, which may serve to offload some/all network traffic from the RAN 104.
  • the connection between the UE 102 and the AP 106 may be consistent with any IEEE 802.11 protocol, wherein the AP 106 could be a wireless fidelity (Wi-Fi®) router.
  • the UE 102, RAN 104, and AP 106 may utilize cellular- WLAN aggregation (for example, LWA/LWIP).
  • Cellular- WLAN aggregation may involve the UE 102 being configured by the RAN 104 to utilize both cellular radio resources and WLAN resources.
  • the RAN 104 may include one or more access nodes, for example, AN 108.
  • AN 108 may terminate air-interface protocols for the UE 102 by providing access stratum protocols including RRC, PDCP, RLC, MAC, and LI protocols. In this manner, the AN 108 may enable data/voice connectivity between CN 120 and the UE 102.
  • the AN 108 may be implemented in a discrete device or as one or more software entities running on server computers as part of, for example, a virtual network, which may be referred to as a CRAN or virtual baseband unit pool.
  • the AN 108 be referred to as a BS, gNB, RAN node, eNB, ng-eNB, NodeB, RSU, TRxP, TRP, etc.
  • the AN 108 may be a macrocell base station or a low power base station for providing femtocells, picocells or other like cells having smaller coverage areas, smaller user capacity, or higher bandwidth compared to macrocells.
  • the RAN 104 may be coupled with one another via an X2 interface (if the RAN 104 is an LTE RAN) or an Xn interface (if the RAN 104 is a 5G RAN).
  • the X2/Xn interfaces which may be separated into control/user plane interfaces in some embodiments, may allow the ANs to communicate information related to handovers, data/context transfers, mobility, load management, interference coordination, etc.
  • the ANs of the RAN 104 may each manage one or more cells, cell groups, component carriers, etc. to provide the UE 102 with an air interface for network access.
  • the UE 102 may be simultaneously connected with a plurality of cells provided by the same or different ANs of the RAN 104.
  • the UE 102 and RAN 104 may use carrier aggregation to allow the UE 102 to connect with a plurality of component carriers, each corresponding to a Pcell or Scell.
  • a first AN may be a master node that provides an MCG and a second AN may be secondary node that provides an SCG.
  • the first/second ANs may be any combination of eNB, gNB, ng-eNB, etc.
  • the RAN 104 may provide the air interface over a licensed spectrum or an unlicensed spectrum.
  • the nodes may use LAA, eLAA, and/or feLAA mechanisms based on CA technology with PCells/Scells.
  • the nodes Prior to accessing the unlicensed spectrum, the nodes may perform medium/carrier-sensing operations based on, for example, a listen-before-talk (LBT) protocol.
  • LBT listen-before-talk
  • the UE 102 or AN 108 may be or act as a RSU, which may refer to any transportation infrastructure entity used for V2X communications.
  • An RSU may be implemented in or by a suitable AN or a stationary (or relatively stationary) UE.
  • An RSU implemented in or by: a UE may be referred to as a “UE-type RSU”; an eNB may be referred to as an “eNB-type RSU”; a gNB may be referred to as a “gNB-type RSU”; and the like.
  • an RSU is a computing device coupled with radio frequency circuitry located on a roadside that provides connectivity support to passing vehicle UEs.
  • the RSU may also include internal data storage circuitry to store intersection map geometry, traffic statistics, media, as well as applications/software to sense and control ongoing vehicular and pedestrian traffic.
  • the RSU may provide very low latency communications required for high speed events, such as crash avoidance, traffic warnings, and the like. Additionally or alternatively, the RSU may provide other cellular/WLAN communications services.
  • the components of the RSU may be packaged in a weatherproof enclosure suitable for outdoor installation, and may include a network interface controller to provide a wired connection (e.g., Ethernet) to a traffic signal controller or a backhaul network.
  • the RAN 104 may be an LTE RAN 110 with eNBs, for example, eNB 112.
  • the LTE RAN 110 may provide an LTE air interface with the following characteristics: SCS of 15 kHz; CP-OFDM waveform for DL and SC-FDMA waveform for UL; turbo codes for data and TBCC for control; etc.
  • the LTE air interface may rely on CSLRS for CSI acquisition and beam management; PDSCH/PDCCH DMRS for PDSCH/PDCCH demodulation; and CRS for cell search and initial acquisition, channel quality measurements, and channel estimation for coherent demodulation/detection at the UE.
  • the LTE air interface may operating on sub-6 GHz bands.
  • the RAN 104 may be an NG-RAN 114 with gNBs, for example, gNB 116, or ng-eNBs, for example, ng-eNB 118.
  • the gNB 116 may connect with 5G-enabled UEs using a 5G NR interface.
  • the gNB 116 may connect with a 5G core through an NG interface, which may include an N2 interface or an N3 interface.
  • the ng-eNB 118 may also connect with the 5G core through an NG interface, but may connect with a UE via an LTE air interface.
  • the gNB 116 and the ng-eNB 118 may connect with each other over an Xn interface.
  • the NG interface may be split into two parts, an NG user plane (NG-U) interface, which carries traffic data between the nodes of the NG-RAN 114 and a UPF 148 (e.g., N3 interface), and an NG control plane (NG-C) interface, which is a signaling interface between the nodes of the NG-RAN114 and an AMF 144 (e.g., N2 interface).
  • NG-U NG user plane
  • N3 interface e.g., N3 interface
  • N-C NG control plane
  • the NG-RAN 114 may provide a 5G-NR air interface with the following characteristics: variable SCS; CP-OFDM for DL, CP-OFDM and DFT-s-OFDM for UL; polar, repetition, simplex, and Reed-Muller codes for control and LDPC for data.
  • the 5G-NR air interface may rely on CSI-RS, PDSCH/PDCCH DMRS similar to the LTE air interface.
  • the 5G-NR air interface may not use a CRS, but may use PBCH DMRS for PBCH demodulation; PTRS for phase tracking for PDSCH; and tracking reference signal for time tracking.
  • the 5G-NR air interface may operating on FR1 bands that include sub-6 GHz bands or FR2 bands that include bands from 24.25 GHz to 52.6 GHz.
  • the 5G-NR air interface may include an SSB that is an area of a downlink resource grid that includes PSS/SSS/PBCH.
  • the 5G-NR air interface may utilize BWPs for various purposes.
  • BWP can be used for dynamic adaptation of the SCS.
  • the UE 102 can be configured with multiple BWPs where each BWP configuration has a different SCS. When a BWP change is indicated to the UE 102, the SCS of the transmission is changed as well.
  • Another use case example of BWP is related to power saving.
  • multiple BWPs can be configured for the UE 102 with different amount of frequency resources (for example, PRBs) to support data transmission under different traffic loading scenarios.
  • a BWP containing a smaller number of PRBs can be used for data transmission with small traffic load while allowing power saving at the UE 102 and in some cases at the gNB 116.
  • a BWP containing a larger number of PRBs can be used for scenarios with higher traffic load.
  • the RAN 104 is communicatively coupled to CN 120 that includes network elements to provide various functions to support data and telecommunications services to customers/subscribers (for example, users of UE 102).
  • the components of the CN 120 may be implemented in one physical node or separate physical nodes.
  • NFV may be utilized to virtualize any or all of the functions provided by the network elements of the CN 120 onto physical compute/storage resources in servers, switches, etc.
  • a logical instantiation of the CN 120 may be referred to as a network slice, and a logical instantiation of a portion of the CN 120 may be referred to as a network sub-slice.
  • the CN 120 may be an LTE CN 122, which may also be referred to as an EPC.
  • the LTE CN 122 may include MME 124, SGW 126, SGSN 128, HSS 130, PGW 132, and PCRF 134 coupled with one another over interfaces (or “reference points”) as shown. Functions of the elements of the LTE CN 122 may be briefly introduced as follows.
  • the MME 124 may implement mobility management functions to track a current location of the UE 102 to facilitate paging, bearer activation/deactivation, handovers, gateway selection, authentication, etc.
  • the SGW 126 may terminate an SI interface toward the RAN and route data packets between the RAN and the LTE CN 122.
  • the SGW 126 may be a local mobility anchor point for inter-RAN node handovers and also may provide an anchor for inter-3GPP mobility. Other responsibilities may include lawful intercept, charging, and some policy enforcement.
  • the SGSN 128 may track a location of the UE 102 and perform security functions and access control. In addition, the SGSN 128 may perform inter-EPC node signaling for mobility between different RAT networks; PDN and S-GW selection as specified by MME 124; MME selection for handovers; etc.
  • the S3 reference point between the MME 124 and the SGSN 128 may enable user and bearer information exchange for inter-3GPP access network mobility in idle/active states.
  • the HSS 130 may include a database for network users, including subscription-related information to support the network entities’ handling of communication sessions.
  • the HSS 130 can provide support for routing/roaming, authentication, authorization, naming/addressing resolution, location dependencies, etc.
  • An S6a reference point between the HSS 130 and the MME 124 may enable transfer of subscription and authentication data for authenticating/authorizing user access to the LTE CN 120.
  • the PGW 132 may terminate an SGi interface toward a data network (DN) 136 that may include an application/content server 138.
  • the PGW 132 may route data packets between the LTE CN 122 and the data network 136.
  • the PGW 132 may be coupled with the SGW 126 by an S5 reference point to facilitate user plane tunneling and tunnel management.
  • the PGW 132 may further include a node for policy enforcement and charging data collection (for example, PCEF).
  • the SGi reference point between the PGW 132 and the data network 1 36 may be an operator external public, a private PDN, or an intra-operator packet data network, for example, for provision of IMS services.
  • the PGW 132 may be coupled with a PCRF 134 via a Gx reference point.
  • the PCRF 134 is the policy and charging control element of the LTE CN 122.
  • the PCRF 134 may be communicatively coupled to the app/content server 138 to determine appropriate QoS and charging parameters for service flows.
  • the PCRF 132 may provision associated rules into a PCEF (via Gx reference point) with appropriate TFT and QCI.
  • the CN 120 may be a 5GC 140.
  • the 5GC 140 may include an AUSF 142, AMF 144, SMF 146, UPF 148, NSSF 150, NEF 152, NRF 154, PCF 156, UDM 158, and AF 160 coupled with one another over interfaces (or “reference points”) as shown. Functions of the elements of the 5GC 140 may be briefly introduced as follows.
  • the AUSF 142 may store data for authentication of UE 102 and handle authentication- related functionality.
  • the AUSF 142 may facilitate a common authentication framework for various access types.
  • the AUSF 142 may exhibit an Nausf service-based interface.
  • the AMF 144 may allow other functions of the 5GC 140 to communicate with the UE 102 and the RAN 104 and to subscribe to notifications about mobility events with respect to the UE 102.
  • the AMF 144 may be responsible for registration management (for example, for registering UE 102), connection management, reachability management, mobility management, lawful interception of AMF-related events, and access authentication and authorization.
  • the AMF 144 may provide transport for SM messages between the UE 102 and the SMF 146, and act as a transparent proxy for routing SM messages.
  • AMF 144 may also provide transport for SMS messages between UE 102 and an SMSF.
  • AMF 144 may interact with the AUSF 142 and the UE 102 to perform various security anchor and context management functions.
  • AMF 144 may be a termination point of a RAN CP interface, which may include or be an N2 reference point between the RAN 104 and the AMF 144; and the AMF 144 may be a termination point of NAS (Nl) signaling, and perform NAS ciphering and integrity protection.
  • AMF 144 may also support NAS signaling with the UE 102 over an N3 IWF interface.
  • the SMF 146 may be responsible for SM (for example, session establishment, tunnel management between UPF 148 and AN 108); UE IP address allocation and management (including optional authorization); selection and control of UP function; configuring traffic steering at UPF 148 to route traffic to proper destination; termination of interfaces toward policy control functions; controlling part of policy enforcement, charging, and QoS; lawful intercept (for SM events and interface to LI system); termination of SM parts of NAS messages; downlink data notification; initiating AN specific SM information, sent via AMF 144 over N2 to AN 108; and determining SSC mode of a session.
  • SM may refer to management of a PDU session, and a PDU session or “session” may refer to a PDU connectivity service that provides or enables the exchange of PDUs between the UE 102 and the data network 136.
  • the UPF 148 may act as an anchor point for intra-RAT and inter-RAT mobility, an external PDU session point of interconnect to data network 136, and a branching point to support multi-homed PDU session.
  • the UPF 148 may also perform packet routing and forwarding, perform packet inspection, enforce the user plane part of policy rules, lawfully intercept packets (UP collection), perform traffic usage reporting, perform QoS handling for a user plane (e.g., packet filtering, gating, UL/DL rate enforcement), perform uplink traffic verification (e.g., SDF- to-QoS flow mapping), transport level packet marking in the uplink and downlink, and perform downlink packet buffering and downlink data notification triggering.
  • UPF 148 may include an uplink classifier to support routing traffic flows to a data network.
  • the NSSF 150 may select a set of network slice instances serving the UE 102.
  • the NSSF 150 may also determine allowed NSSAI and the mapping to the subscribed S-NSSAIs, if needed.
  • the NSSF 150 may also determine the AMF set to be used to serve the UE 102, or a list of candidate AMFs based on a suitable configuration and possibly by querying the NRF 154.
  • the selection of a set of network slice instances for the UE 102 may be triggered by the AMF 144 with which the UE 102 is registered by interacting with the NSSF 150, which may lead to a change of AMF.
  • the NSSF 150 may interact with the AMF 144 via an N22 reference point; and may communicate with another NSSF in a visited network via an N31 reference point (not shown). Additionally, the NSSF 150 may exhibit an Nnssf service-based interface.
  • the NEF 152 may securely expose services and capabilities provided by 3GPP network functions for third party, internal exposure/re-exposure, AFs (e.g., AF 160), edge computing or fog computing systems, etc.
  • the NEF 152 may authenticate, authorize, or throttle the AFs.
  • NEF 152 may also translate information exchanged with the AF 160 and information exchanged with internal network functions. For example, the NEF 152 may translate between an AF-Service-Identifier and an internal 5GC information.
  • NEF 152 may also receive information from other NFs based on exposed capabilities of other NFs. This information may be stored at the NEF 152 as structured data, or at a data storage NF using standardized interfaces. The stored information can then be re-exposed by the NEF 152 to other NFs and AFs, or used for other purposes such as analytics. Additionally, the NEF 152 may exhibit an Nnef service-based interface.
  • the NRF 154 may support service discovery functions, receive NF discovery requests from NF instances, and provide the information of the discovered NF instances to the NF instances. NRF 154 also maintains information of available NF instances and their supported services. As used herein, the terms “instantiate,” “instantiation,” and the like may refer to the creation of an instance, and an “instance” may refer to a concrete occurrence of an object, which may occur, for example, during execution of program code. Additionally, the NRF 154 may exhibit the Nnrf service-based interface.
  • the PCF 156 may provide policy rules to control plane functions to enforce them, and may also support unified policy framework to govern network behavior.
  • the PCF 156 may also implement a front end to access subscription information relevant for policy decisions in a UDR of the UDM 158.
  • the PCF 156 exhibit an Npcf service-based interface.
  • the UDM 158 may handle subscription-related information to support the network entities’ handling of communication sessions, and may store subscription data of UE 102. For example, subscription data may be communicated via an N8 reference point between the UDM 158 and the AMF 144.
  • the UDM 158 may include two parts, an application front end and a UDR.
  • the UDR may store subscription data and policy data for the UDM 158 and the PCF 156, and/or structured data for exposure and application data (including PFDs for application detection, application request information for multiple UEs 102) for the NEF 152.
  • the Nudr service-based interface may be exhibited by the UDR 221 to allow the UDM 158, PCF 156, and NEF 152 to access a particular set of the stored data, as well as to read, update (e.g., add, modify), delete, and subscribe to notification of relevant data changes in the UDR.
  • the UDM may include a UDM- FE, which is in charge of processing credentials, location management, subscription management and so on. Several different front ends may serve the same user in different transactions.
  • the UDM-FE accesses subscription information stored in the UDR and performs authentication credential processing, user identification handling, access authorization, registration/mobility management, and subscription management.
  • the UDM 158 may exhibit the Nudm service-based interface.
  • the AF 160 may provide application influence on traffic routing, provide access to NEF, and interact with the policy framework for policy control.
  • the 5GC 140 may enable edge computing by selecting operator/3 rd party services to be geographically close to a point that the UE 102 is attached to the network. This may reduce latency and load on the network.
  • the 5GC 140 may select a UPF 148 close to the UE 102 and execute traffic steering from the UPF 148 to data network 136 via the N6 interface. This may be based on the UE subscription data, UE location, and information provided by the AF 160. In this way, the AF 160 may influence UPF (re)selection and traffic routing.
  • the network operator may permit AF 160 to interact directly with relevant NFs. Additionally, the AF 160 may exhibit an Naf service-based interface.
  • the data network 136 may represent various network operator services, Internet access, or third party services that may be provided by one or more servers including, for example, application/content server 138.
  • FIG. 2 schematically illustrates a wireless network 200 in accordance with various embodiments.
  • the wireless network 200 may include a UE 202 in wireless communication with an AN 204.
  • the UE 202 and AN 204 may be similar to, and substantially interchangeable with, like-named components described elsewhere herein.
  • the UE 202 may be communicatively coupled with the AN 204 via connection 206.
  • the connection 206 is illustrated as an air interface to enable communicative coupling, and can be consistent with cellular communications protocols such as an LTE protocol or a 5G NR protocol operating at mmWave or sub-6GHz frequencies.
  • the UE 202 may include a host platform 208 coupled with a modem platform 210.
  • the host platform 208 may include application processing circuitry 212, which may be coupled with protocol processing circuitry 214 of the modem platform 210.
  • the application processing circuitry 212 may run various applications for the UE 202 that source/sink application data.
  • the application processing circuitry 212 may further implement one or more layer operations to transmit/receive application data to/from a data network. These layer operations may include transport (for example UDP) and Internet (for example, IP) operations
  • the protocol processing circuitry 214 may implement one or more of layer operations to facilitate transmission or reception of data over the connection 206.
  • the layer operations implemented by the protocol processing circuitry 214 may include, for example, MAC, RLC, PDCP, RRC and NAS operations.
  • the modem platform 210 may further include digital baseband circuitry 216 that may implement one or more layer operations that are “below” layer operations performed by the protocol processing circuitry 214 in a network protocol stack. These operations may include, for example, PHY operations including one or more of HARQ-ACK functions, scrambling/descrambling, encoding/decoding, layer mapping/de-mapping, modulation symbol mapping, received symbol/bit metric determination, multi-antenna port precoding/decoding, which may include one or more of space-time, space-frequency or spatial coding, reference signal generation/detection, preamble sequence generation and/or decoding, synchronization sequence generation/detection, control channel signal blind decoding, and other related functions.
  • PHY operations including one or more of HARQ-ACK functions, scrambling/descrambling, encoding/decoding, layer mapping/de-mapping, modulation symbol mapping, received symbol/bit metric determination, multi-antenna port precoding/decoding, which may
  • the modem platform 210 may further include transmit circuitry 218, receive circuitry 220, RF circuitry 222, and RF front end (RFFE) 224, which may include or connect to one or more antenna panels 226.
  • the transmit circuitry 218 may include a digital-to-analog converter, mixer, intermediate frequency (IF) components, etc.
  • the receive circuitry 220 may include an analog-to-digital converter, mixer, IF components, etc.
  • the RF circuitry 222 may include a low-noise amplifier, a power amplifier, power tracking components, etc.
  • RFFE 224 may include filters (for example, surface/bulk acoustic wave filters), switches, antenna tuners, beamforming components (for example, phase-array antenna components), etc.
  • transmit/receive components may be specific to details of a specific implementation such as, for example, whether communication is TDM or FDM, in mmWave or sub-6 gHz frequencies, etc.
  • the transmit/receive components may be arranged in multiple parallel transmit/receive chains, may be disposed in the same or different chips/modules, etc.
  • the protocol processing circuitry 214 may include one or more instances of control circuitry (not shown) to provide control functions for the transmit/receive components.
  • a UE reception may be established by and via the antenna panels 226, RFFE 224, RF circuitry 222, receive circuitry 220, digital baseband circuitry 216, and protocol processing circuitry 214.
  • the antenna panels 226 may receive a transmission from the AN 204 by receive-beamforming signals received by a plurality of antennas/antenna elements of the one or more antenna panels 226.
  • a UE transmission may be established by and via the protocol processing circuitry 214, digital baseband circuitry 216, transmit circuitry 218, RF circuitry 222, RFFE 224, and antenna panels 226.
  • the transmit components of the UE 204 may apply a spatial filter to the data to be transmitted to form a transmit beam emitted by the antenna elements of the antenna panels 226.
  • the AN 204 may include a host platform 228 coupled with a modem platform 230.
  • the host platform 228 may include application processing circuitry 232 coupled with protocol processing circuitry 234 of the modem platform 230.
  • the modem platform may further include digital baseband circuitry 236, transmit circuitry 238, receive circuitry 240, RF circuitry 242, RFFE circuitry 244, and antenna panels 246.
  • the components of the AN 204 may be similar to and substantially interchangeable with like-named components of the UE 202.
  • the components of the AN 208 may perform various logical functions that include, for example, RNC functions such as radio bearer management, uplink and downlink dynamic radio resource management, and data packet scheduling.
  • Figure 3 is a block diagram illustrating components, according to some example embodiments, able to read instructions from a machine-readable or computer-readable medium (e.g., a non-transitory machine-readable storage medium) and perform any one or more of the methodologies discussed herein.
  • Figure 3 shows a diagrammatic representation of hardware resources 300 including one or more processors (or processor cores) 310, one or more memory/storage devices 320, and one or more communication resources 330, each of which may be communicatively coupled via a bus 340 or other interface circuitry.
  • node virtualization e.g., NFV
  • a hypervisor 302 may be executed to provide an execution environment for one or more network slices/sub- slices to utilize the hardware resources 300.
  • the processors 310 may include, for example, a processor 312 and a processor 314.
  • the processors 310 may be, for example, a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a DSP such as a baseband processor, an ASIC, an FPGA, a radio-frequency integrated circuit (RFIC), another processor (including those discussed herein), or any suitable combination thereof.
  • CPU central processing unit
  • RISC reduced instruction set computing
  • CISC complex instruction set computing
  • GPU graphics processing unit
  • DSP such as a baseband processor, an ASIC, an FPGA, a radio-frequency integrated circuit (RFIC), another processor (including those discussed herein), or any suitable combination thereof.
  • the memory/storage devices 320 may include main memory, disk storage, or any suitable combination thereof.
  • the memory/storage devices 320 may include, but are not limited to, any type of volatile, non-volatile, or semi-volatile memory such as dynamic random access memory (DRAM), static random access memory (SRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), Flash memory, solid-state storage, etc.
  • DRAM dynamic random access memory
  • SRAM static random access memory
  • EPROM erasable programmable read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • Flash memory solid-state storage, etc.
  • the communication resources 330 may include interconnection or network interface controllers, components, or other suitable devices to communicate with one or more peripheral devices 304 or one or more databases 306 or other network elements via a network 308.
  • the communication resources 330 may include wired communication components (e.g., for coupling via USB, Ethernet, etc.), cellular communication components, NFC components, Bluetooth® (or Bluetooth® Low Energy) components, Wi-Fi® components, and other communication components.
  • Instructions 350 may comprise software, a program, an application, an applet, an app, or other executable code for causing at least any of the processors 310 to perform any one or more of the methodologies discussed herein.
  • the instructions 350 may reside, completely or partially, within at least one of the processors 310 (e.g., within the processor’s cache memory), the memory/storage devices 320, or any suitable combination thereof.
  • any portion of the instructions 350 may be transferred to the hardware resources 300 from any combination of the peripheral devices 304 or the databases 306.
  • the memory of processors 310, the memory/storage devices 320, the peripheral devices 304, and the databases 306 are examples of computer-readable and machine-readable media.
  • FIG 4 provides a high-level view of an Open RAN (O-RAN) architecture 400.
  • the O- RAN architecture 400 includes four O-RAN defined interfaces - namely, the Al interface, the 01 interface, the 02 interface, and the Open Fronthaul Management (M)-plane interface - which connect the Service Management and Orchestration (SMO) framework 402 to O-RAN network functions (NFs) 404 and the O-Cloud 406.
  • the SMO 402 (described in [013]) also connects with an external system 410, which provides enrighment data to the SMO 402.
  • FIG 4 also illustrates that the Al interface terminates at an O-RAN Non-Real Time (RT) RAN Intelligent Controller (RIC) 412 in or at the SMO 402 and at the O-RAN Near-RT RIC 414 in or at the O-RAN NFs 404.
  • the O-RAN NFs 404 can be VNFs such as VMs or containers, sitting above the O-Cloud 406 and/or Physical Network Functions (PNFs) utilizing customized hardware. All O-RAN NFs 404 are expected to support the 01 interface when interfacing the SMO framework 4O2.
  • the O- RAN NFs 404 connect to the NG-Core 408 via the NG interface (which is a 3GPP defined interface).
  • the Open Fronthaul M-plane interface between the SMO 402 and the O-RAN Radio Unit (O-RU) 416 supports the O-RU 416 management in the O-RAN hybrid model as specified in [016].
  • the Open Fronthaul M-plane interface is an optional interface to the SMO 402 that is included for backward compatibility purposes as per [016], and is intended for management of the O-RU 416 in hybrid mode only.
  • the management architecture of flat mode [012] and its relation to the 01 interface for the O-RU 416 is for future study.
  • the O-RU 416 termination of the 01 interface towards the SMO 402 as specified in [012].
  • Figure 5 shows an O-RAN logical architecture 500 corresponding to the O-RAN architecture 400 of Figure 4.
  • the SMO 502 corresponds to the SMO 402
  • O-Cloud 506 corresponds to the O-Cloud 406
  • the non-RT RIC 512 corresponds to the non-RT RIC 412
  • the near-RT RIC 514 corresponds to the near-RT RIC 414
  • the O-RU 516 corresponds to the O-RU 416 of Figure 5, respectively.
  • the O-RAN logical architecture 500 includes a radio portion and a management portion.
  • the management portion/side of the architectures 500 includes the SMO Framework 502 containing the non-RT RIC 512, and may include the O-Cloud 506.
  • the O-Cloud 506 is a cloud computing platform including a collection of physical infrastructure nodes to host the relevant O- RAN functions (e.g., the near-RT RIC 514, O-CU-CP 521, O-CU-UP 522, and the 0-DU 515), supporting software components (e.g., OSs, VMMs, container runtime engines, ML engines, etc.), and appropriate management and orchestration functions.
  • the radio portion/side of the logical architecture 500 includes the near-RT RIC 514, the O-RAN Distributed Unit (0-DU) 515, the O-RU 516, the O-RAN Central Unit - Control Plane (O-CU-CP) 521, and the O-RAN Central Unit - User Plane (O-CU-UP) 522 functions.
  • the radio portion/side of the logical architecture 500 may also include the O-e/gNB 510.
  • the 0-DU 515 is a logical node hosting RLC, MAC, and higher PHY layer entities/elements (High-PHY layers) based on a lower layer functional split.
  • the O-RU 516 is a logical node hosting lower PHY layer entities/elements (Low-PHY layer) (e.g., FFT/iFFT, PRACH extraction, etc.) and RF processing elements based on a lower layer functional split. Virtualization of O-RU 516 is FFS.
  • the O-CU-CP 521 is a logical node hosting the RRC and the control plane (CP) part of the PDCP protocol.
  • the O O-CU-UP 522 is a a logical node hosting the user plane part of the PDCP protocol and the SDAP protocol.
  • An E2 interface terminates at a plurality of E2 nodes.
  • the E2 nodes are logical nodes/entities that terminate the E2 interface.
  • the E2 nodes include the O-CU- CP 521, O-CU-UP 522, O-DU 515, or any combination of elements as defined in [015].
  • the E2 nodes include the O-e/gNB 510.
  • the E2 interface also connects the O-e/gNB 510 to the Near-RT RIC 514.
  • the protocols over E2 interface are based exclusively on Control Plane (CP) protocols.
  • CP Control Plane
  • the E2 functions are grouped into the following categories: (a) near-RT RIC 514 services (REPORT, INSERT, CONTROL and POLICY, as described in [015]); and (b) near-RT RIC 514 support functions, which include E2 Interface Management (E2 Setup, E2 Reset, Reporting of General Error Situations, etc.) and Near-RT RIC Service Update (e.g., capability exchange related to the list of E2 Node functions exposed over E2).
  • E2 Interface Management E2 Setup, E2 Reset, Reporting of General Error Situations, etc.
  • Near-RT RIC Service Update e.g., capability exchange related to the list of E2 Node functions exposed over E2.
  • FIG. 5 shows the Uu interface between a UE 501 and O-e/gNB 510 as well as between the UE 501 and 0-RAN components.
  • the Uu interface is a 3GPP defined interface (see e.g., sections 5.2 and 5.3 of [007]), which includes a complete protocol stack from LI to L3 and terminates in the NG-RAN or E-UTRAN.
  • the O-e/gNB 510 is an LTE eNB [004], a 5G gNB or ng-eNB [006] that supports the E2 interface.
  • the O-e/gNB 510 may be the same or similar as eNB 112, gNB 116, ng-eNB 118, RAN 608, RAN 710, or some other base station, RAN, or nodeB discussed previously.
  • the a UE 501 may correspond to UEs 102, 202, 602, UE 705, or some other UE discussed with respect to other Figures herein, and/or the like.
  • the O-e/gNB 510 supports O-DU 515 and O-RU 516 functions with an Open Fronthaul interface between them.
  • the Open Fronthaul (OF) interface(s) is/are between O-DU 515 and O-RU 516 functions [016] [017].
  • the OF interface(s) includes the Control User Synchronization (CUS) Plane and Management (M) Plane.
  • CCS Control User Synchronization
  • M Management
  • Figures 4 and 5 also show that the O-RU 516 terminates the OF M-Plane interface towards the O-DU 515 and optionally towards the SMO 502 as specified in [016].
  • the O-RU 516 terminates the OF CUS-Plane interface towards the O-DU 515 and the SMO 502.
  • the Fl-c interface connects the O-CU-CP 521 with the O-DU 515.
  • the Fl-c interface is between the gNB-CU-CP and gNB-DU nodes [007] [O10].
  • the Fl-c interface is adopted between the O-CU-CP 521 with the O-DU 515 functions while reusing the principles and protocol stack defined by 3GPP and the definition of interoperability profile specifications.
  • the Fl-u interface connects the O-CU-UP 522 with the O-DU 515.
  • the Fl-u interface is between the gNB-CU-UP and gNB-DU nodes [007] [010].
  • the Fl-u interface is adopted between the O-CU-UP 522 with the O-DU 515 functions while reusing the principles and protocol stack defined by 3GPP and the definition of interoperability profile specifications.
  • the NG-c interface is defined by 3 GPP as an interface between the gNB-CU-CP and the AMF in the 5GC [006].
  • the NG-c is also referred as the N2 interface (see [006]).
  • the NG-u interface is defined by 3 GPP, as an interface between the gNB-CU-UP and the UPF in the 5GC [006].
  • the NG-u interface is referred as the N3 interface (see [006]).
  • NG-c and NG- u protocol stacks defined by 3GPP are reused and may be adapted for 0-RAN purposes.
  • the X2-c interface is defined in 3 GPP for transmitting control plane information between eNBs or between eNB and en-gNB in EN-DC.
  • the X2-u interface is defined in 3GPP for transmitting user plane information between eNBs or between eNB and en-gNB in EN-DC (see e.g., [005], [006]).
  • X2-c and X2-u protocol stacks defined by 3GPP are reused and may be adapted for 0-RAN purposes
  • the Xn-c interface is defined in 3 GPP for transmitting control plane information between gNBs, ng-eNBs, or between an ng-eNB and gNB.
  • the Xn-u interface is defined in 3GPP for transmitting user plane information between gNBs, ng-eNBs, or between ng-eNB and gNB (see e.g., [006], [008]).
  • Xn-c and Xn-u protocol stacks defined by 3GPP are reused and may be adapted for 0-RAN purposes
  • the El interface is defined by 3GPP as being an interface between the gNB-CU-CP (e.g., gNB-CU-CP 3728) and gNB-CU-UP (see e.g., [007], [009]).
  • gNB-CU-CP e.g., gNB-CU-CP 3728
  • gNB-CU-UP see e.g., [007], [009].
  • El protocol stacks defined by 3GPP are reused and adapted as being an interface between the O-CU-CP 521 and the O-CU-UP 522 functions.
  • the 0-RAN Non-Real Time (RT) RAN Intelligent Controller (RIC) 512 is a logical function within the SMO framework 402, 502 that enables non-real-time control and optimization of RAN elements and resources; APmachine learning (ML) workflow(s) including model training, inferences, and updates; and policy-based guidance of applications/features in the Near-RT RIC 514.
  • RT Non-Real Time
  • RIC RAN Intelligent Controller
  • the 0-RAN near-RT RIC 514 is a logical function that enables near-real-time control and optimization of RAN elements and resources via fine-grained data collection and actions over the E2 interface.
  • the near-RT RIC 514 may include one or more AI/ML workflows including model training, inferences, and updates.
  • the non-RT RIC 512 can be an ML training host to host the training of one or more ML models. ML training can be performed offline using data collected from the RIC, O-DU 515 and O-RU 516.
  • non-RT RIC 512 is part of the SMO 502
  • the ML training host and/or ML model host/actor can be part of the non-RT RIC 512 and/or the near-RT RIC 514.
  • the ML training host and ML model host/actor can be part of the non- RT RIC 512 and/or the near-RT RIC 514.
  • the ML training host and ML model host/actor may be co-located as part of the non-RT RIC 512 and/or the near-RT RIC 514.
  • the non-RT RIC 512 may request or trigger ML model training in the training hosts regardless of where the model is deployed and executed. ML models may be trained and not currently deployed.
  • the non-RT RIC 512 provides a query-able catalog for an ML designer/developer to publish/install trained ML models (e.g., executable software components).
  • the non-RT RIC 512 may provide discovery mechanism if a particular ML model can be executed in a target ML inference host (MF), and what number and type of ML models can be executed in the MF.
  • MF target ML inference host
  • ML catalogs made disoverable by the non-RT RIC 512: a design-time catalog (e.g., residing outside the non-RT RIC 512 and hosted by some other ML platform(s)), a training/deployment-time catalog (e.g., residing inside the non-RT RIC 512), and a run-time catalog (e.g., residing inside the non-RT RIC 512).
  • the non-RT RIC 512 supports necessary capabilities for ML model inference in support of ML assisted solutions running in the non-RT RIC 512 or some other ML inference host. These capabilities enable executable software to be installed such as VMs, containers, etc.
  • the non-RT RIC 512 may also include and/or operate one or more ML engines, which are packaged software executable libraries that provide methods, routines, data types, etc., used to run ML models.
  • the non-RT RIC 512 may also implement policies to switch and activate ML model instances under different operating conditions.
  • the non-RT RIC 52 is be able to access feedback data (e.g., FM and PM statistics) over the 01 interface on ML model performance and perform necessary evaluations. If the ML model fails during runtime, an alarm can be generated as feedback to the non-RT RIC 512. How well the ML model is performing in terms of prediction accuracy or other operating statistics it produces can also be sent to the non-RT RIC 512 over 01.
  • the non-RT RIC 512 can also scale ML model instances running in a target MF over the 01 interface by observing resource utilization in MF.
  • the environment where the ML model instance is running (e.g., the MF) monitors resource utilization of the running ML model.
  • the scaling mechanism may include a scaling factor such as an number, percentage, and/or other like data used to scale up/down the number of ML instances.
  • ML model instances running in the target ML inference hosts may be automatically scaled by observing resource utilization in the MF. For example, the Kubernetes® (K8s) runtime environment typically provides an auto-scaling feature.
  • the Al interface is between the non-RT RIC 512 (within or outside the SMO 502) and the near-RT RIC 514.
  • the Al interface supports three types of services as defined in [014], including a Policy Management Service, an Enrichment Information Service, and ML Model Management Service.
  • Al policies have the following characteristics compared to persistent configuration [014]: Al policies are not critical to traffic; Al policies have temporary validity; Al policies may handle individual UE or dynamically defined groups of UEs; Al policies act within and take precedence over the configuration; and Al policies are non-persistent, i.e., do not survive a restart of the near-RT RIC.
  • 0-RAN Alliance Working Group 1 0-RAN Operations and Maintenance Architecture Specification, version 2.0 (Dec 2019) (“0-RAN-WG1.0AM-Architecture-v02.00”).
  • 0-RAN Alliance Working Group 1 0-RAN Operations and Maintenance Interface Specification, version 2.0 (Dec 2019) (“0-RAN-WG1.01-Interface-v02.00”).
  • Figure 6 illustrates a network 600 in accordance with various embodiments.
  • the network 600 may operate in a matter consistent with 3 GPP technical specifications or technical reports for 6G systems.
  • the network 600 may operate concurrently with network 100.
  • the network 600 may share one or more frequency or bandwidth resources with network 100.
  • a UE e.g., UE 602
  • UE 602 may be configured to operate in both network 600 and network 100.
  • Such configuration may be based on a UE including circuitry configured for communication with frequency and bandwidth resources of both networks 100 and 600.
  • several elements of network 600 may share one or more characteristics with elements of network 100. For the sake of brevity and clarity, such elements may not be repeated in the description of network 600.
  • the network 600 may include a UE 602, which may include any mobile or non-mobile computing device designed to communicate with a RAN 608 via an over-the-air connection.
  • the UE 602 may be similar to, for example, UE 102.
  • the UE 602 may be, but is not limited to, a smartphone, tablet computer, wearable computer device, desktop computer, laptop computer, in- vehicle infotainment, in-car entertainment device, instrument cluster, head-up display device, onboard diagnostic device, dashtop mobile equipment, mobile data terminal, electronic engine management system, electronic/engine control unit, electronic/engine control module, embedded system, sensor, microcontroller, control module, engine management system, networked appliance, machine-type communication device, M2M or D2D device, loT device, etc.
  • the network 600 may include a plurality of UEs coupled directly with one another via a sidelink interface.
  • the UEs may be M2M/D2D devices that communicate using physical sidelink channels such as, but not limited to, PSBCH, PSDCH, PSSCH, PSCCH, PSFCH, etc.
  • the UE 602 may be communicatively coupled with an AP such as AP 106 as described with respect to Figure 1.
  • the RAN 608 may include one or more ANss such as AN 108 as described with respect to Figure 1.
  • the RAN 608 and/or the AN of the RAN 608 may be referred to as a base station (BS), a RAN node, or using some other term or name.
  • the UE 602 and the RAN 608 may be configured to communicate via an air interface that may be referred to as a sixth generation (6G) air interface.
  • the 6G air interface may include one or more features such as communication in a terahertz (THz) or sub-THz bandwidth, or joint communication and sensing.
  • THz terahertz
  • sub-THz bandwidth may refer to a system that allows for wireless communication as well as radar-based sensing via various types of multiplexing.
  • THz or sub-THz bandwidths may refer to communication in the 80 GHz and above frequency ranges. Such frequency ranges may additionally or alternatively be referred to as “millimeter wave” or “mmWave” frequency ranges.
  • the RAN 608 may allow for communication between the UE 602 and a 6G core network (CN) 610. Specifically, the RAN 608 may facilitate the transmission and reception of data between the UE 602 and the 6G CN 610.
  • the 6G CN 610 may include various functions such as NSSF 150, NEF 152, NRF 154, PCF 156, UDM 158, AF 160, SMF 146, and AUSF 142.
  • the 6G CN 610 may additional include UPF 148 and DN 136 as shown in Figure 6.
  • the RAN 608 may include various additional functions that are in addition to, or alternative to, functions of a legacy cellular network such as a 4G or 5G network.
  • Two such functions may include a Compute Control Function (Comp CF) 624 and a Compute Service Function (Comp SF) 636.
  • the Comp CF 624 and the Comp SF 636 may be parts or functions of the Computing Service Plane.
  • Comp CF 624 may be a control plane function that provides functionalities such as management of the Comp SF 636, computing task context generation and management (e.g., create, read, modify, delete), interaction with the underlaying computing infrastructure for computing resource management, etc..
  • Comp SF 636 may be a user plane function that serves as the gateway to interface computing service users (such as UE 602) and computing nodes behind a Comp SF instance. Some functionalities of the Comp SF 636 may include: parse computing service data received from users to compute tasks executable by computing nodes; hold service mesh ingress gateway or service API gateway; service and charging policies enforcement; performance monitoring and telemetry collection, etc.
  • a Comp SF 636 instance may serve as the user plane gateway for a cluster of computing nodes.
  • a Comp CF 624 instance may control one or more Comp SF 636 instances.
  • Two other such functions may include a Communication Control Function (Comm CF) 628 and a Communication Service Function (Comm SF) 638, which may be parts of the Communication Service Plane.
  • the Comm CF 628 may be the control plane function for managing the Comm SF 638, communication sessions creation/configuration/releasing, and managing communication session context.
  • the Comm SF 638 may be a user plane function for data transport.
  • Comm CF 628 and Comm SF 638 may be considered as upgrades of SMF 146 and UPF 148, which were described with respect to a 5G system in Figure 1.
  • the upgrades provided by the Comm CF 628 and the Comm SF 638 may enable service-aware transport. For legacy (e.g., 4G or 5G) data transport, SMF 146 and UPF 148 may still be used.
  • Data CF 622 may be a control plane function and provides functionalities such as Data SF 632 management, Data service creation/configuration/releasing, Data service context management, etc.
  • Data SF 632 may be a user plane function and serve as the gateway between data service users (such as UE 602 and the various functions of the 6G CN 610) and data service endpoints behind the gateway. Specific functionalities may include include: parse data service user data and forward to corresponding data service endpoints, generate charging data, report data service status.
  • SOCF Service Orchestration and Chaining Function
  • SOCF 620 may discover, orchestrate and chain up communication/computing/data services provided by functions in the network.
  • SOCF 620 may interact with one or more of Comp CF 624, Comm CF 628, and Data CF 622 to identify Comp SF 636, Comm SF 638, and Data SF 632 instances, configure service resources, and generate the service chain, which could contain multiple Comp SF 636, Comm SF 638, and Data SF 632 instances and their associated computing endpoints. Workload processing and data movement may then be conducted within the generated service chain.
  • the SOCF 620 may also responsible for maintaining, updating, and releasing a created service chain.
  • SRF service registration function
  • NRF 154 may act as the registry for network functions.
  • eSCP evolved service communication proxy
  • SCP service communication proxy
  • eSCP-U 634 service communication proxy
  • SICF 626 may control and configure eCSP instances in terms of service traffic routing policies, access rules, load balancing configurations, performance monitoring, etc.
  • the AMF 644 may be similar to 144, but with additional functionality. Specifically, the AMF 644 may include potential functional repartition, such as move the message forwarding functionality from the AMF 644 to the RAN 608.
  • SOEF service orchestration exposure function
  • the SOEF may be configured to expose service orchestration and chaining services to external users such as applications.
  • the UE 602 may include an additional function that is referred to as a computing client service function (comp CSF) 604.
  • the comp CSF 604 may have both the control plane functionalities and user plane functionalities, and may interact with corresponding network side functions such as SOCF 620, Comp CF 624, Comp SF 636, Data CF 622, and/or Data SF 632 for service discovery, request/response, compute task workload exchange, etc.
  • the Comp CSF 604 may also work with network side functions to decide on whether a computing task should be run on the UE 602, the RAN 608, and/or an element of the 6G CN 610.
  • the UE 602 and/or the Comp CSF 604 may include a service mesh proxy 606.
  • the service mesh proxy 606 may act as a proxy for service-to-service communication in the user plane. Capabilities of the service mesh proxy 606 may include one or more of addressing, security, load balancing, etc.
  • Figure 7 illustrates a simplified block diagram of artificial (Al)-assisted communication between a UE 705 and a RAN 710, in accordance with various embodiments. More specifically, as described in further detail below, Al/machine learning (ML) models may be used or leveraged to facilitate over-the-air communication between UE 705 and RAN 710.
  • ML machine learning
  • One or both of the UE 705 and the RAN 710 may operate in a matter consistent with 3 GPP technical specifications or technical reports for 6G systems.
  • the wireless cellular communication between the UE 705 and the RAN 710 may be part of, or operate concurrently with, networks 600, 100, and/or some other network described herein.
  • the UE 705 may be similar to, and share one or more features with, UE 602, UE 102, and/or some other UE described herein.
  • the UE 705 may be, but is not limited to, a smartphone, tablet computer, wearable computer device, desktop computer, laptop computer, in-vehicle infotainment, in-car entertainment device, instrument cluster, head-up display device, onboard diagnostic device, dashtop mobile equipment, mobile data terminal, electronic engine management system, electronic/engine control unit, electronic/engine control module, embedded system, sensor, microcontroller, control module, engine management system, networked appliance, machine-type communication device, M2M or D2D device, loT device, etc.
  • the RAN 710 may be similar to, and share one or more features with, RAN 114, RAN 608, and/or some other RAN described herein.
  • the Al-related elements of UE 705 may be similar to the AL related elements of RAN 710.
  • description of the various elements will be provided from the point of view of the UE 705, however it will be understood that such discussion or description will apply to equally named/numbered elements of RAN 710, unless explicitly stated otherwise.
  • the UE 705 may include various elements or functions that are related to AI/ML. Such elements may be implemented as hardware, software, firmware, and/or some combination thereof. In embodiments, one or more of the elements may be implemented as part of the same hardware (e.g., chip or multi-processor chip), software (e.g., a computing program), or firmware as another element.
  • the data repository 715 may be responsible for data collection and storage. Specifically, the data repository 715 may collect and store RAN configuration parameters, measurement data, performance key performance indicators (KPIs), model performance metrics, etc., for model training, update, and inference. More generally, collected data is stored into the repository. Stored data can be discovered and extracted by other elements from the data repository 715. For example, as may be seen, the inference data selection/filter element 750 may retrieve data from the data repository 715.
  • the UE 705 may be configured to discover and request data from the data repository 710 in the RAN, and vice versa. More generally, the data repository 715 of the UE 705 may be communicatively coupled with the data repository 715 of the RAN 710 such that the respective data repositories of the UE and the RAN may share collected data with one another.
  • the training data selection/filter functional block 720 may be configured to generate training, validation, and testing datasets for model training. Training data may be extracted from the data repository 715. Data may be selected/filtered based on the specific AI/ML model to be trained. Data may optionally be transformed/augmented/pre-processed (e.g., normalized) before being loaded into datasets. The training data selection/filter functional block 720 may label data in datasets for supervised learning. The produced datasets may then be fed into model training the model training functional block 725.
  • model training functional block 725 may be responsible for training and updating(re-training) AI/ML models.
  • the selected model may be trained using the fed-in datasets (including training, validation, testing) from the training data selection/filtering functional block.
  • the model training functional block 725 may produce trained and tested AI/ML models which are ready for deployment.
  • the produced trained and tested models can be stored in a model repository 735.
  • the model repository 735 may be responsible for AI/ML models’ (both trained and untrained) storage and exposure. Trained/updated model(s) may be stored into the model repository 735. Model and model parameters may be discovered and requested by other functional blocks (e.g., the training data selection/filter functional block 720 and/or the model training functional block 725).
  • the UE 705 may discover and request AI/ML models from the model repository 735 of the RAN 710.
  • the RAN 710 may be able to discover and/or request AI/ML models from the model repository 735 of the UE 705.
  • the RAN 710 may configure models and/or model parameters in the model repository 735 of the UE 705.
  • the model management functional block 740 may be responsible for management of the AI/ML model produced by the model training functional block 725. Such management functions may include deployment of a trained model, monitoring model performance, etc. In model deployment, the model management functional block 740 may allocate and schedule hardware and/or software resources for inference, based on received trained and tested models. As used herein, “inference” refers to the process of using trained AI/ML model(s) to generate data analytics, actions, policies, etc. based on input inference data. In performance monitoring, based on wireless performance KPIs and model performance metrics, the model management functional block 740 may decide to terminate the running model, start model re-training, select another model, etc. In embodiments, the model management functional block 740 of the RAN 710 may be able to configure model management policies in the UE 705 as shown.
  • the inference data selection/filter functional block 750 may be responsible for generating datasets for model inference at the inference functional block 745, as described below. Specifically, inference data may be extracted from the data repository 715. The inference data selection/filter functional block 750 may select and/or filter the data based on the deployed AI/ML model. Data may be transformed/augmented/pre-processed following the same transformation/augmentation/pre-processing as those in training data selection/filtering as described with respect to functional block 720. The produced inference dataset may be fed into the inference functional block 745.
  • the inference functional block 745 may be responsible for executing inference as described above. Specifically, the inference functional block 745 may consume the inference dataset provided by the inference data selection/filtering functional block 750, and generate one or more outcomes. Such outcomes may be or include data analytics, actions, policies, etc. The outcome(s) may be provided to the performance measurement functional block 730.
  • the performance measurement functional block 730 may be configured to measure model performance metrics (e.g., accuracy, model bias, run-time latency, etc.) of deployed and executing models based on the inference outcome(s) for monitoring purpose.
  • Model performance data may be stored in the data repository 715.
  • the electronic device(s), network(s), system(s), chip(s) or component(s), or portions or implementations thereof, of Figures 1-7, or some other figure herein may be configured to perform one or more processes, techniques, or methods as described herein, or portions thereof.
  • One such process is depicted in Figure 8.
  • the process may be performed by a RIC or a portion thereof, such as the near RT-RIC.
  • the process may include, at 801, determining to add, modify, or delete a beamforming configuration for one or more user equipments (UEs), wherein the beamforming configuration is associated with a non-grid-of beams (non-GoB) beamforming mode.
  • UEs user equipments
  • non-GoB non-grid-of beams
  • the process may further include encoding a message for transmission to RAN Node, such as an O-DU, to add, modify, or delete the beamforming configuration for the one or more UEs.
  • the message may be a control command (e.g., to control the beamforming mode for a single UE) or a policy command (e.g., to control the beamforming mode for a plurality of UEs).
  • the message may include a MIMO mode index, a SSB index, and/or a non-GoB beamforming mode index associated with the beamforming configuration.
  • FIG. 9 illustrates another process in accordance with various embodiments.
  • the process may be performed by a RAN Node, such as an O-DU, or a portion thereof.
  • the process may include receiving, from a radio access network (RAN) intelligence controller (RIC), a message to add, modify, or delete a beamforming configuration that is associated with a non- grid-of beams (non-GoB) beamforming mode.
  • RAN radio access network
  • RIC radio access network intelligence controller
  • the message may be a control command (e.g., to control the beamforming mode for a single UE) or a policy command (e.g., to control the beamforming mode for a plurality of UEs).
  • the message may include a MIMO mode index, a SSB index, and/or a non-GoB beamforming mode index associated with the beamforming configuration.
  • the process may further include adding, modifying, or deleting the beamforming configuration based on the message.
  • the RAN Node such as an O-DU may communicate (e.g., send and/or receive messages) on a wireless cellular network to or from a UE based on the beamforming configuration.
  • At least one of the components set forth in one or more of the preceding figures may be configured to perform one or more operations, techniques, processes, and/or methods as set forth in the example section below.
  • the baseband circuitry as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below.
  • circuitry associated with a UE, base station, network element, etc. as described above in connection with one or more of the preceding figures may be configured to operate in accordance with one or more of the examples set forth below in the example section.
  • Example 1 may include a mechanism for a RIC (RAN Intelligence Controller) to send a control command to configure, reconfigure, or release a Non-GoB beamforming mode for a UE.
  • RIC Radio Network Controller
  • Example 2 may include a mechanism for a RIC (RAN Intelligence Controller) to send a policy command to configure, reconfigure, or release Non-GoB beamforming mode for UEs of interest.
  • RIC RAN Intelligence Controller
  • Example 3 may include a method of a near real-time (RT) radio access network (RAN) intelligence controller (RIC), the method comprising: determining to add, modify, or delete a beamforming configuration for one or more user equipments (UEs), wherein the beamforming configuration is associated with a non-grid-of beams (non-GoB) beamforming mode; and encoding a message for transmission to the RAN Node, such as an O-DUto add, modify, or delete the beamforming configuration for one or more user equipments (UEs).
  • RT near real-time
  • RAN radio access network
  • RIC radio access network intelligence controller
  • Example 4 may include the method of example 3 or some other example herein, wherein the message is a control command.
  • Example 5 may include the method of example 4 or some other example herein, wherein the control command has a control service style type to indicate that the control command is associated with beamforming configuration control.
  • Example 6 may include the method of example 4-5 or some other example herein, wherein the one or more UEs is a single UE.
  • Example 7 may include the method of example 3 or some other example herein, wherein the message is a policy command.
  • Example 8 may include the method of example 7 or some other example herein, wherein the policy command has a policy service style type to indicate that the control command is associated with beamforming configuration control.
  • Example 9 may include the method of example 7-8 or some other example herein, wherein the one or more UEs includes a plurality of UEs.
  • Example 10 may include the method of example 3-9 or some other example herein, wherein the message indicates a MIMO mode index, a SSB index, and/or a non-GoB beamforming mode index associated with the beamforming configuration.
  • Example 11 may include a method of a RAN Node, such as an O-DU, the method comprising: receiving, from a radio access network (RAN) intelligence controller (RIC), a message to add, modify, or delete a beamforming configuration that is associated with a non-grid-of beams (non-GoB) beamforming mode for a user equipment (UE); and adding, modifying, or deleting the beamforming configuration based on the message.
  • RAN radio access network
  • RIC radio access network intelligence controller
  • UE user equipment
  • Example 12 may include the method of example 11 or some other example herein, wherein the message is a control command.
  • Example 13 may include the method of example 12 or some other example herein, wherein the control command has a control service style type to indicate that the control command is associated with beamforming configuration control.
  • Example 14 may include the method of example 11 or some other example herein, wherein the message is a policy command.
  • Example 15 may include the method of example 14 or some other example herein, wherein the policy command has a policy service style type to indicate that the control command is associated with beamforming configuration control.
  • Example 16 may include the method of example 11-15 or some other example herein, wherein the message indicates a MIMO mode index, a SSB index, and/or a non-GoB beamforming mode index associated with the beamforming configuration.
  • Example Z01 may include an apparatus comprising means to perform one or more elements of a method described in or related to any of examples 1-16, or any other method or process described herein.
  • Example Z02 may include one or more non-transitory computer-readable media comprising instructions to cause an electronic device, upon execution of the instructions by one or more processors of the electronic device, to perform one or more elements of a method described in or related to any of examples 1-16, or any other method or process described herein.
  • Example Z03 may include an apparatus comprising logic, modules, or circuitry to perform one or more elements of a method described in or related to any of examples 1-16, or any other method or process described herein.
  • Example Z04 may include a method, technique, or process as described in or related to any of examples 1-16, or portions or parts thereof.
  • Example Z05 may include an apparatus comprising: one or more processors and one or more computer-readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the method, techniques, or process as described in or related to any of examples 1-16, or portions thereof.
  • Example Z06 may include a signal as described in or related to any of examples 1-16, or portions or parts thereof.
  • Example Z07 may include a datagram, packet, frame, segment, protocol data unit (PDU), or message as described in or related to any of examples 1-16, or portions or parts thereof, or otherwise described in the present disclosure.
  • PDU protocol data unit
  • Example Z08 may include a signal encoded with data as described in or related to any of examples 1-16, or portions or parts thereof, or otherwise described in the present disclosure.
  • Example Z09 may include a signal encoded with a datagram, packet, frame, segment, protocol data unit (PDU), or message as described in or related to any of examples 1-16, or portions or parts thereof, or otherwise described in the present disclosure.
  • Example Z10 may include an electromagnetic signal carrying computer-readable instructions, wherein execution of the computer-readable instructions by one or more processors is to cause the one or more processors to perform the method, techniques, or process as described in or related to any of examples 1-16, or portions thereof.
  • Example Z11 may include a computer program comprising instructions, wherein execution of the program by a processing element is to cause the processing element to carry out the method, techniques, or process as described in or related to any of examples 1-16, or portions thereof.
  • Example Z12 may include a signal in a wireless network as shown and described herein.
  • Example Z13 may include a method of communicating in a wireless network as shown and described herein.
  • Example Z14 may include a system for providing wireless communication as shown and described herein.
  • Example Z15 may include a device for providing wireless communication as shown and described herein.
  • Gateway Function Premise Measurement CHF Charging Equipment CSI-RS CSI
  • Digital 70 Provider 105 E-UTRAN Node B EN-DC E- Protocol Access
  • EREG enhanced REG 50 Channel/Half 85 Programmable Gate enhanced resource rate Array element groups FACH Forward Access FR Frequency
  • E-UTRA Evolved 65 FDD Frequency 100 GGSN Gateway GPRS
  • NodeB Automatic ICCID Integrated centralized unit 45 Repeat Request 80 Circuit Card gNB-DU gNB- HANDO Handover Identification distributed unit, Next HFN HyperFrame IAB Integrated
  • Tunnelling Protocol Speed Uplink Packet IEIDL Information for User Plane Access Element Identifier GTS Go To Sleep HTTP Hyper Text Data Length Signal (related to 70 Transfer Protocol 105 IETF Internet Engineering Task IP-M IP Multicast authentication Force IPv4 Internet Protocol key
  • Network 70 subscriber 105 LCID Logical Channel ID used for Data Analytics
  • MAC-A MAC 70 MDAS Management 105 CHannel MPDCCH MTC MTC Machine-Type Descriptor Physical Downlink Communications NFV Network
  • MS Mobile Station 50 NAS Non-Access 85 Manager MSB Most Significant Stratum, Non- Access NMS Network Bit Stratum layer Management System
  • Termination 70 Forwarding Path 105 Downlink Shared CHannel NSSAI Personal NPRACH NSSF Network Slice Computer Narrowband Selection Function PCC Primary
  • Protocol 70 Signal 105 RADIUS Remote Authentication Dial In Failure RSSI Received Signal
  • Component Carrier 40 SDU Service Data 75 Management
  • AI/ML application may refer to a complete and deployable package, environment to achieve a certain function in an operational environment.
  • AI/ML application or the like may be an application that contains some AI/ML models and application-level descriptions.
  • circuitry refers to, is part of, or includes hardware components such as an electronic circuit, a logic circuit, a processor (shared, dedicated, or group) and/or memory (shared, dedicated, or group), an Application Specific Integrated Circuit (ASIC), a field-programmable device (FPD) (e.g., a field-programmable gate array (FPGA), a programmable logic device (PLD), a complex PLD (CPLD), a high-capacity PLD (HCPLD), a structured ASIC, or a programmable SoC), digital signal processors (DSPs), etc., that are configured to provide the described functionality.
  • FPD field-programmable device
  • FPGA field-programmable gate array
  • PLD programmable logic device
  • CPLD complex PLD
  • HPLD high-capacity PLD
  • DSPs digital signal processors
  • the circuitry may execute one or more software or firmware programs to provide at least some of the described functionality.
  • the term “circuitry” may also refer to a combination of one or more hardware elements (or a combination of circuits used in an electrical or electronic system) with the program code used to carry out the functionality of that program code. In these embodiments, the combination of hardware elements and program code may be referred to as a particular type of circuitry.
  • processor circuitry refers to, is part of, or includes circuitry capable of sequentially and automatically carrying out a sequence of arithmetic or logical operations, or recording, storing, and/or transferring digital data.
  • Processing circuitry may include one or more processing cores to execute instructions and one or more memory structures to store program and data information.
  • processor circuitry may refer to one or more application processors, one or more baseband processors, a physical central processing unit (CPU), a single-core processor, a dual-core processor, a triple-core processor, a quad-core processor, and/or any other device capable of executing or otherwise operating computerexecutable instructions, such as program code, software modules, and/or functional processes.
  • Processing circuitry may include more hardware accelerators, which may be microprocessors, programmable processing devices, or the like.
  • the one or more hardware accelerators may include, for example, computer vision (CV) and/or deep learning (DL) accelerators.
  • CV computer vision
  • DL deep learning
  • application circuitry and/or “baseband circuitry” may be considered synonymous to, and may be referred to as, “processor circuitry.”
  • interface circuitry refers to, is part of, or includes circuitry that enables the exchange of information between two or more components or devices.
  • interface circuitry may refer to one or more hardware interfaces, for example, buses, I/O interfaces, peripheral component interfaces, network interface cards, and/or the like.
  • user equipment refers to a device with radio communication capabilities and may describe a remote user of network resources in a communications network.
  • the term “user equipment” or “UE” may be considered synonymous to, and may be referred to as, client, mobile, mobile device, mobile terminal, user terminal, mobile unit, mobile station, mobile user, subscriber, user, remote station, access agent, user agent, receiver, radio equipment, reconfigurable radio equipment, reconfigurable mobile device, etc.
  • the term “user equipment” or “UE” may include any type of wireless/wired device or any computing device including a wireless communications interface.
  • network element refers to physical or virtualized equipment and/or infrastructure used to provide wired or wireless communication network services.
  • network element may be considered synonymous to and/or referred to as a networked computer, networking hardware, network equipment, network node, router, switch, hub, bridge, radio network controller, RAN device, RAN node, gateway, server, virtualized VNF, NFVI, and/or the like.
  • computer system refers to any type interconnected electronic devices, computer devices, or components thereof. Additionally, the term “computer system” and/or “system” may refer to various components of a computer that are communicatively coupled with one another. Furthermore, the term “computer system” and/or “system” may refer to multiple computer devices and/or multiple computing systems that are communicatively coupled with one another and configured to share computing and/or networking resources.
  • appliance refers to a computer device or computer system with program code (e.g., software or firmware) that is specifically designed to provide a specific computing resource.
  • program code e.g., software or firmware
  • a “virtual appliance” is a virtual machine image to be implemented by a hypervisor-equipped device that virtualizes or emulates a computer appliance or otherwise is dedicated to provide a specific computing resource.
  • resource refers to a physical or virtual device, a physical or virtual component within a computing environment, and/or a physical or virtual component within a particular device, such as computer devices, mechanical devices, memory space, processor/CPU time, processor/CPU usage, processor and accelerator loads, hardware time or usage, electrical power, input/output operations, ports or network sockets, channel/link allocation, throughput, memory usage, storage, network, database and applications, workload units, and/or the like.
  • a “hardware resource” may refer to compute, storage, and/or network resources provided by physical hardware element(s).
  • a “virtualized resource” may refer to compute, storage, and/or network resources provided by virtualization infrastructure to an application, device, system, etc.
  • network resource or “communication resource” may refer to resources that are accessible by computer devices/systems via a communications network.
  • system resources may refer to any kind of shared entities to provide services, and may include computing and/or network resources. System resources may be considered as a set of coherent functions, network data objects or services, accessible through a server where such system resources reside on a single host or multiple hosts and are clearly identifiable.
  • channel refers to any transmission medium, either tangible or intangible, which is used to communicate data or a data stream.
  • channel may be synonymous with and/or equivalent to “communications channel,” “data communications channel,” “transmission channel,” “data transmission channel,” “access channel,” “data access channel,” “link,” “data link,” “carrier,” “radiofrequency carrier,” and/or any other like term denoting a pathway or medium through which data is communicated.
  • link refers to a connection between two devices through a RAT for the purpose of transmitting and receiving information.
  • instantiate refers to the creation of an instance.
  • An “instance” also refers to a concrete occurrence of an object, which may occur, for example, during execution of program code.
  • Coupled may mean two or more elements are in direct physical or electrical contact with one another, may mean that two or more elements indirectly contact each other but still cooperate or interact with each other, and/or may mean that one or more other elements are coupled or connected between the elements that are said to be coupled with each other.
  • directly coupled may mean that two or more elements are in direct contact with one another.
  • communicatively coupled may mean that two or more elements may be in contact with one another by a means of communication including through a wire or other interconnect connection, through a wireless communication channel or link, and/or the like.
  • information element refers to a structural element containing one or more fields.
  • field refers to individual contents of an information element, or a data element that contains content.
  • SMTC refers to an SSB-based measurement timing configuration configured by SSB-MeasurementTimingConfiguration.
  • SSB refers to an SS/PBCH block.
  • Primary Cell refers to the MCG cell, operating on the primary frequency, in which the UE either performs the initial connection establishment procedure or initiates the connection re-establishment procedure.
  • Primary SCG Cell refers to the SCG cell in which the UE performs random access when performing the Reconfiguration with Sync procedure for DC operation.
  • Secondary Cell refers to a cell providing additional radio resources on top of a Special Cell for a UE configured with CA.
  • Secondary Cell Group refers to the subset of serving cells comprising the PSCell and zero or more secondary cells for a UE configured with DC.
  • Server Cell refers to the primary cell for a UE in RRC_CONNECTED not configured with CA/DC there is only one serving cell comprising of the primary cell.
  • serving cell refers to the set of cells comprising the Special Cell(s) and all secondary cells for a UE in RRC_CONNECTED configured with CA/.
  • Special Cell refers to the PCell of the MCG or the PSCell of the SCG for DC operation; otherwise, the term “Special Cell” refers to the Pcell.
  • machine learning refers to the use of computer systems implementing algorithms and/or statistical models to perform specific task(s) without using explicit instructions, but instead relying on patterns and inferences.
  • ML algorithms build or estimate mathematical model(s) (referred to as “ML models” or the like) based on sample data (referred to as “training data,” “model training information,” or the like) in order to make predictions or decisions without being explicitly programmed to perform such tasks.
  • training data referred to as “training data,” “model training information,” or the like
  • an ML algorithm is a computer program that learns from experience with respect to some task and some performance measure, and an ML model may be any object or data structure created after an ML algorithm is trained with one or more training datasets. After training, an ML model may be used to make predictions on new datasets.
  • ML algorithm refers to different concepts than the term “ML model,” these terms as discussed herein may be used interchangeably for the purposes of the present disclosure.
  • machine learning model may also refer to ML methods and concepts used by an ML-assisted solution.
  • An “ML-assisted solution” is a solution that addresses a specific use case using ML algorithms during operation.
  • ML models include supervised learning (e.g., linear regression, k-nearest neighbor (KNN), descision tree algorithms, support machine vectors, Bayesian algorithm, ensemble algorithms, etc.) unsupervised learning (e.g., K-means clustering, principle component analysis (PCA), etc.), reinforcement learning (e.g., Q-learning, multi-armed bandit learning, deep RL, etc.), neural networks, and the like.
  • supervised learning e.g., linear regression, k-nearest neighbor (KNN), descision tree algorithms, support machine vectors, Bayesian algorithm, ensemble algorithms, etc.
  • unsupervised learning e.g., K-means clustering, principle component analysis (PCA), etc.
  • reinforcement learning e.g., Q-learning, multi-armed bandit learning,
  • An “ML pipeline” is a set of functionalities, functions, or functional entities specific for an ML-assisted solution; an ML pipeline may include one or several data sources in a data pipeline, a model training pipeline, a model evaluation pipeline, and an actor.
  • the “actor” is an entity that hosts an ML assisted solution using the output of the ML model inference).
  • ML training host refers to an entity, such as a network function, that hosts the training of the model.
  • ML inference host refers to an entity, such as a network function, that hosts model during inference mode (which includes both the model execution as well as any online learning if applicable).
  • the ML-host informs the actor about the output of the ML algorithm, and the actor takes a decision for an action (an “action” is performed by an actor as a result of the output of an ML assisted solution).
  • model inference information refers to information used as an input to the ML model for determining inference(s); the data used to train an ML model and the data used to determine inferences may overlap, however, “training data” and “inference data” refer to different concepts.

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  • Computer Networks & Wireless Communication (AREA)
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Abstract

Selon divers modes de réalisation, la présente invention concerne des techniques relatives à un RIC (contrôleur intelligent de RAN (réseau d'accès radio)), à un nœud RAN et/ou à un équipement utilisateur (UE). Le RIC peut être configuré pour déterminer d'ajouter, de modifier ou de supprimer une configuration de formation de faisceau pour un ou plusieurs équipements utilisateur (UE), la configuration de formation de faisceau étant associée à un mode de formation de faisceau sans grille de faisceaux (non-GoB). Le RIC peut en outre être configuré pour coder, sur la base de la détermination, un message destiné à être transmis au nœud RAN pour ajouter, modifier ou supprimer la configuration de formation de faisceau pour l'UE. Le nœud RAN peut être configuré pour ajouter, modifier ou supprimer en conséquence la configuration de formation de faisceau. D'autres modes de réalisation peuvent être décrits et/ou revendiqués.
PCT/US2023/073748 2022-09-19 2023-09-08 Commande et politique de formation de faisceau sans grille de faisceaux (gob) sur l'interface e2 WO2024064534A1 (fr)

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