WO2021113883A2 - Appareil et procédé de sélection de cellule flexible - Google Patents

Appareil et procédé de sélection de cellule flexible Download PDF

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Publication number
WO2021113883A2
WO2021113883A2 PCT/US2021/022634 US2021022634W WO2021113883A2 WO 2021113883 A2 WO2021113883 A2 WO 2021113883A2 US 2021022634 W US2021022634 W US 2021022634W WO 2021113883 A2 WO2021113883 A2 WO 2021113883A2
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WO
WIPO (PCT)
Prior art keywords
pss
raster
frequency
frequencies
processing circuit
Prior art date
Application number
PCT/US2021/022634
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English (en)
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WO2021113883A3 (fr
Inventor
Ping Hou
Yamming WANG
Yuanye WANG
Original Assignee
Zeku, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Zeku, Inc. filed Critical Zeku, Inc.
Priority to CN202180022551.6A priority Critical patent/CN115362658B/zh
Publication of WO2021113883A2 publication Critical patent/WO2021113883A2/fr
Publication of WO2021113883A3 publication Critical patent/WO2021113883A3/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H04W56/001—Synchronization between nodes
    • H04W56/0015—Synchronization between nodes one node acting as a reference for the others
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0069—Cell search, i.e. determining cell identity [cell-ID]
    • H04J11/0073—Acquisition of primary synchronisation channel, e.g. detection of cell-ID within cell-ID group
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2602—Signal structure
    • H04L27/26025—Numerology, i.e. varying one or more of symbol duration, subcarrier spacing, Fourier transform size, sampling rate or down-clocking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2657—Carrier synchronisation
    • H04L27/2659—Coarse or integer frequency offset determination and synchronisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2662—Symbol synchronisation
    • H04L27/2663—Coarse synchronisation, e.g. by correlation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/24—Radio transmission systems, i.e. using radiation field for communication between two or more posts
    • H04B7/26—Radio transmission systems, i.e. using radiation field for communication between two or more posts at least one of which is mobile
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2668—Details of algorithms
    • H04L27/2673—Details of algorithms characterised by synchronisation parameters
    • H04L27/2675—Pilot or known symbols

Definitions

  • Embodiments of the present disclosure relate to apparatus and method for wireless communication.
  • Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasts.
  • cellular communication such as the 4th-generation (4G) Long Term Evolution (LTE) and the 5th- generation (5G) New Radio (NR), the 3rd Generation Partnership Project (3GPP) defines various mechanisms for cell selection.
  • 4G Long Term Evolution
  • 5G 5th-generation (5G) New Radio
  • 3GPP 3rd Generation Partnership Project
  • a baseband chip may include a frequency shifting/decimation circuit configured to receive a radio frequency (RF) sample. Frequency shifting/decimation circuit may be further configured to rotate the RF sample by fixed amounts with respect to a synchronization signal block (SSB) center frequency to obtain a plurality of raster frequencies, where each raster frequency in the plurality of raster frequencies may be associated with a rotation by one of the fixed amounts.
  • RF radio frequency
  • SSB synchronization signal block
  • the baseband chip may further include a primary synchronization signal (PSS) processing circuit configured to estimate a set of integer frequency offsets (IFOs) for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different subcarrier spacing (SCS) step across an SCS range.
  • the PSS processing circuit may be further configured to perform PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the PSS processing circuit may be also configured to select a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate is selected for use in SSB detection.
  • an apparatus is disclosed.
  • the apparatus may include a receiver configured to receive an RF sample.
  • the apparatus may also include a baseband chip.
  • the baseband chip may include a frequency shifting/decimation circuit configured to receive a RF sample. Frequency shifting/decimation circuit may be further configured to rotate the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, where each raster frequency in the plurality of raster frequencies may be associated with a rotation by one of the fixed amounts.
  • the baseband chip may further include a PSS processing circuit configured to estimate a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • the PSS processing circuit may be further configured to perform PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the PSS processing circuit may be also configured to select a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate is selected for use in SSB detection.
  • a method is disclosed. The method may include receiving, by a receiver, a RF sample.
  • the method may further include rotating, by a frequency shifting/decimation circuit, the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, each raster frequency in the plurality of raster frequencies being associated with a rotation by one of the fixed amounts.
  • the method may also include estimating, by a PSS processing circuit, a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • the method may also include performing, by the PSS processing circuit, PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the method may also include selecting, by the PSS processing circuit, a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate may be selected for use in SSB detection.
  • FIG. 1 illustrates an exemplary wireless network, according to some embodiments of the present disclosure.
  • FIG. 2 illustrates a block diagram of an apparatus including a baseband chip, a radio frequency (RF) chip, and a host chip, according to some embodiments of the present disclosure.
  • FIG. 3A illustrates a block diagram of an expanded view of the baseband chip of
  • FIG. 2 according to some embodiments of the present disclosure.
  • FIG. 3B illustrates an expanded view of a PSS processing circuit depicted in FIG.
  • FIG. 3C illustrates a block diagram of an SSB, according to some embodiments of the present disclosure.
  • FIG. 3E illustrates a graphical representation of the degradation of PSS correlation performance versus TO, according to some embodiments of the present disclosure.
  • FIG. 3F illustrates a graphical representation of PSS correlation degradation due to
  • FIG. 4A illustrates a flow chart of a first exemplary method of wireless communication of a baseband chip, according to some embodiments of the present disclosure.
  • FIG. 4B illustrates a flow chart of a second exemplary method of wireless communication of a PSS processing circuit, according to some embodiments of the present disclosure.
  • FIG. 4C illustrates a flow chart of a third exemplary method of wireless communication of a secondary synchronization signal (SSS) processing block, according to some embodiments of the present disclosure.
  • SSS secondary synchronization signal
  • FIG. 4D illustrates a flow chart of a third exemplary method of wireless communication of a physical broadcast channel (PBCH) processing block, according to some embodiments of the present disclosure.
  • PBCH physical broadcast channel
  • FIG. 5 illustrates a block diagram of an exemplary node, according to some embodiments of the present disclosure.
  • references in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” “some embodiments,” “certain embodiments,” etc. indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it would be within the knowledge of a person skilled in the pertinent art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
  • the term “one or more” as used herein, depending at least in part upon context, may be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense.
  • terms, such as “a,” “an,” or “the,” again, may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context.
  • the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.
  • CDMA code division multiple access
  • TDMA time division multiple access
  • FDMA frequency division multiple access
  • OFDMA orthogonal frequency division multiple access
  • SC- FDMA single-carrier frequency division multiple access
  • WLAN wireless local area network
  • a CDMA network may implement a radio access technology (RAT), such as Universal Terrestrial Radio Access (UTRA), evolved UTRA (E-UTRA), CDMA 2000, etc.
  • RAT radio access technology
  • UTRA Universal Terrestrial Radio Access
  • E-UTRA evolved UTRA
  • CDMA 2000 etc.
  • GSM Global System for Mobile Communications
  • An OFDMA network may implement a RAT, such as LTE or NR.
  • a WLAN system may implement a RAT, such as Wi-Fi.
  • the techniques described herein may be used for the wireless networks and RATs mentioned above, as well as other wireless networks and RATs.
  • CRS ubiquitous cell-specific reference signal
  • UE user equipment
  • CRS energy detection of CRS in an RF sample may be used for initial cell selection and acquisition by a user equipment (UE).
  • Cell selection using CRS energy detection may be performed using a RF sample with a wide frequency bandwidth (also referred to as a “wideband frequency”), which is efficient in terms of time and computational simplicity as compared to sampling a narrowband RF sample.
  • a wide frequency bandwidth also referred to as a “wideband frequency”
  • data transmissions may also be included in the wideband frequency searched by the UE, the RF sample may be corrupted. This means that the accuracy of energy detection may be limited when using a wideband frequency for initial cell selection.
  • uplink and downlink transmissions may share the same frequency band, and hence, in certain situations the UE may be unable to separate and detect the control signals (CRS) sent by a base station from uplink data or control signals sent by other UEs located in the vicinity.
  • CRS control signals
  • these conventional approaches may only provide a rough indication of the cell quality and may require combination with time consuming and complex measurements, which increase the power consumption and computational latency when performing initial cell selection.
  • the PSS reference almost achieves orthogonality when shifted in the time domain with the integer sampling period defined by Nyquist rate. Consequently, PSS correlation can be performed in either the frequency domain or the time domain depending on the target implementation latency, complexity, power consumption, shared hardware, etc. of the system.
  • the baseband chip of present disclosure may perform PSS correlation (for each narrowband raster frequency obtained from a wideband RF sample) using a set of IFOs estimated for each of the raster frequencies. More specifically, each IFO in the set of IFOs may be estimated for a different SCS step (e.g., 0.25 SCS, 0.5 SCS, etc.) across an SCS range (e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.). Each of the IFOs may be used in PSS correlation and/or convolution for its associated raster frequency. Then, for each raster frequency, the PSS candidate with the largest correlation peak score may be selected for further processing.
  • SCS step e.g. 0.25 SCS, 0.5 SCS, etc.
  • SCS range e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.
  • this and other information may be sent to a physical (PHY) layer controller, which may use the information to determine which of the raster frequencies to acquire for initial cell selection.
  • PHY physical
  • PSS correlation may be extended to cell selection for 5G NR by enabling the UE to operate at the lower SNR conditions as compared to conventional approaches. Additional details of which are described below in connection with FIGs. 1-5.
  • FIG. 1 illustrates an exemplary wireless network 100, in which certain aspects of the present disclosure may be implemented, according to some embodiments of the present disclosure.
  • wireless network 100 may include a network of nodes, such as a user equipment (UE) 102, an access node 104, and a core network element 106.
  • UE user equipment
  • User equipment 102 may be any terminal device, such as a mobile phone, a desktop computer, a laptop computer, a tablet, a vehicle computer, a gaming console, a printer, a positioning device, a wearable electronic device, a smart sensor, or any other device capable of receiving, processing, and transmitting information, such as any member of a vehicle to everything (V2X) network, a cluster network, a smart grid node, or an Internet-of-Things (IoT) node.
  • V2X vehicle to everything
  • cluster network such as a cluster network
  • smart grid node such as a smart grid node
  • IoT Internet-of-Things
  • Access node 104 may be a device that communicates with user equipment 102, such as a wireless access point, a base station (BS), a Node B, an enhanced Node B (eNodeB or eNB), a next-generation NodeB (gNodeB or gNB), a cluster master node, or the like. Access node 104 may have a wired connection to user equipment 102, a wireless connection to user equipment 102, or any combination thereof. Access node 104 may be connected to user equipment 102 by multiple connections, and user equipment 102 may be connected to other access nodes in addition to access node 104. Access node 104 may also be connected to other user equipments.
  • BS base station
  • eNodeB or eNB enhanced Node B
  • gNodeB or gNB next-generation NodeB
  • Core network element 106 may serve access node 104 and user equipment 102 to provide core network services.
  • core network element 106 may include a home subscriber server (HSS), a mobility management entity (MME), a serving gateway (SGW), or a packet data network gateway (PGW).
  • HSS home subscriber server
  • MME mobility management entity
  • SGW serving gateway
  • PGW packet data network gateway
  • EPC evolved packet core
  • Other core network elements may be used in LTE and in other communication systems.
  • core network element 106 includes an access and mobility management function (AMF) device, a session management function (SMF) device, or a user plane function (UPF) device, of a core network for the NR system. It is understood that core network element 106 is shown as a set of rack-mounted servers by way of illustration and not by way of limitation.
  • AMF access and mobility management function
  • SMF session management function
  • UPF user plane function
  • Core network element 106 may connect with a large network, such as the Internet
  • IP Internet Protocol
  • data from user equipment 102 may be communicated to other user equipments connected to other access points, including, for example, a computer 110 connected to Internet 108, for example, using a wired connection or a wireless connection, or to a tablet 112 wirelessly connected to Internet 108 via a router 114.
  • computer 110 and tablet 112 provide additional examples of possible user equipments
  • router 114 provides an example of another possible access node.
  • a generic example of a rack-mounted server is provided as an illustration of core network element 106. However, there may be multiple elements in the core network including database servers, such as a database 116, and security and authentication servers, such as an authentication server 118.
  • Database 116 may, for example, manage data related to user subscription to network services.
  • a home location register (HLR) is an example of a standardized database of subscriber information for a cellular network.
  • authentication server 118 may handle authentication of users, sessions, and so on.
  • an authentication server function (AUSF) device may be the specific entity to perform user equipment authentication.
  • a single server rack may handle multiple such functions, such that the connections between core network element 106, authentication server 118, and database 116, may be local connections within a single rack.
  • Each element in FIG. 1 may be considered a node of wireless network 100. More detail regarding the possible implementation of a node is provided by way of example in the description of a node 500 in FIG. 5.
  • Node 500 may be configured as user equipment 102, access node 104, or core network element 106 in FIG. 1.
  • node 500 may also be configured as computer 110, router 114, tablet 112, database 116, or authentication server 118 in FIG. 1.
  • node 500 may include a processor 502, a memory 504, and a transceiver 506. These components are shown as connected to one another by a bus, but other connection types are also permitted.
  • Transceiver 506 may include any suitable device for sending and/or receiving data.
  • Node 500 may include one or more transceivers, although only one transceiver 506 is shown for simplicity of illustration.
  • An antenna 508 is shown as a possible communication mechanism for node 500. Multiple antennas and/or arrays of antennas may be utilized for receiving multiple spatially multiplex data streams.
  • examples of node 500 may communicate using wired techniques rather than (or in addition to) wireless techniques.
  • access node 104 may communicate wirelessly to user equipment 102 and may communicate by a wired connection (for example, by optical or coaxial cable) to core network element 106.
  • Other communication hardware such as a network interface card (NIC), may be included as well.
  • NIC network interface card
  • node 500 may include processor 502. Although only one processor is shown, it is understood that multiple processors can be included.
  • Processor 502 may include microprocessors, microcontroller units (MCUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functions described throughout the present disclosure.
  • Processor 502 may be a hardware device having one or more processing cores.
  • Processor 502 may execute software.
  • node 500 may also include memory 504. Although only one memory is shown, it is understood that multiple memories can be included. Memory 504 can broadly include both memory and storage.
  • memory 504 may include random-access memory (RAM), read-only memory (ROM), static RAM (SRAM), dynamic RAM (DRAM), ferro electric RAM (FRAM), electrically erasable programmable ROM (EEPROM), CD-ROM or other optical disk storage, hard disk drive (HDD), such as magnetic disk storage or other magnetic storage devices, Flash drive, solid-state drive (SSD), or any other medium that can be used to carry or store desired program code in the form of instructions that can be accessed and executed by processor 502.
  • RAM random-access memory
  • ROM read-only memory
  • SRAM static RAM
  • DRAM dynamic RAM
  • FRAM ferro electric RAM
  • EEPROM electrically erasable programmable ROM
  • CD-ROM or other optical disk storage such as hard disk drive (HDD), such as magnetic disk storage or other magnetic storage devices, Flash drive, solid-state drive (SSD), or any other medium that can be used to carry or store desired program code in the form of instructions that can be accessed and executed by processor 502.
  • HDD hard disk drive
  • Processor 502, memory 504, and transceiver 506 may be implemented in various forms in node 500 for performing wireless communication functions.
  • processor 502, memory 504, and transceiver 506 of node 500 are implemented (e.g., integrated) on one or more system-on-chips (SoCs).
  • SoCs system-on-chips
  • processor 502 and memory 504 may be integrated on an application processor (AP) SoC (sometimes known as a “host,” referred to herein as a “host chip”) that handles application processing in an operating system (OS) environment, including generating raw data to be transmitted.
  • API application processor
  • OS operating system
  • processor 502 and memory 504 may be integrated on a baseband processor (BP) SoC (sometimes known as a “modem,” referred to herein as a “baseband chip”) that converts the raw data, e.g., from the host chip, to signals that can be used to modulate the carrier frequency for transmission, and vice versa, which can ran a real-time operating system (RTOS).
  • BP baseband processor
  • RTOS real-time operating system
  • processor 502 and transceiver 506 may be integrated on an RF SoC (sometimes known as a “transceiver,” referred to herein as an “RF chip”) that transmits and receives RF signals with antenna 508.
  • RF SoC sometimes known as a “transceiver,” referred to herein as an “RF chip”
  • some or all of the host chip, baseband chip, and RF chip may be integrated as a single SoC.
  • a baseband chip and an RF chip may be integrated into a single SoC that manages all the radio functions for cellular communication.
  • any suitable node of wireless network 100 in transmitting signals to another node, for example, from user equipment 102 to access node 104 via, or vice versa, may perform PSS processing to determine a set of IFOs across a range of SCS steps to improve the accuracy and latency associated with cell selection by select candidate PSS samples for further processing rather than processing all samples, as described below in detail.
  • PSS processing may perform PSS processing to determine a set of IFOs across a range of SCS steps to improve the accuracy and latency associated with cell selection by select candidate PSS samples for further processing rather than processing all samples, as described below in detail.
  • FIG. 2 illustrates a block diagram of an apparatus 200 including a baseband chip
  • Apparatus 200 may be an example of any suitable node of wireless network 100 in FIG. 1, such as user equipment 102 or access node 104. As shown in FIG. 2, apparatus 200 may include baseband chip 202, RF chip 204, host chip 206, and one or more antennas 210. In some embodiments, baseband chip 202 is implemented by processor 502 and memory 504, and RF chip 204 is implemented by processor 502, memory 504, and transceiver 506, as described above with respect to FIG. 5.
  • apparatus 200 may further include an external memory 208 (e.g., the system memory or main memory) that can be shared by each chip 202, 204, or 206 through the system/main bus.
  • external memory 208 e.g., the system memory or main memory
  • baseband chip 202 is illustrated as a standalone SoC in FIG.
  • baseband chip 202 and RF chip 204 may be integrated as one SoC; in another example, baseband chip 202 and host chip 206 may be integrated as one SoC; in still another example, baseband chip 202, RF chip 204, and host chip 206 may be integrated as one SoC, as described above.
  • host chip 206 may generate raw data and send it to baseband chip 202 for encoding, modulation, and mapping.
  • Baseband chip 202 may also access the raw data generated by host chip 206 and stored in external memory 208, for example, using the direct memory access (DMA).
  • DMA direct memory access
  • Baseband chip 202 may first encode (e.g., by source coding and/or channel coding) the raw data and modulate the coded data using any suitable modulation techniques, such as multi-phase shift keying (MPSK) modulation or quadrature amplitude modulation (QAM).
  • MPSK multi-phase shift keying
  • QAM quadrature amplitude modulation
  • Baseband chip 202 may perform any other functions, such as symbol or layer mapping, to convert the raw data into a signal that can be used to modulate the carrier frequency for transmission.
  • baseband chip 202 may send the modulated signal to RF chip 204.
  • RF chip 204 through the transmitter, may convert the modulated signal in the digital form into analog signals, i.e., RF signals, and perform any suitable front-end RF functions, such as filtering, digital pre-distortion, up-conversion, or sample-rate conversion.
  • Antenna 210 e.g., an antenna array
  • antenna 210 may receive RF signals and pass the RF signals to the receiver (Rx) of RF chip 204.
  • RF chip 204 may perform any suitable front-end RF functions, such as filtering, IQ imbalance compensation, down-conversion, or sample-rate conversion, and convert the RF signals into low-frequency digital signals (baseband signals) that can be processed by baseband chip 202.
  • baseband chip 202 may demodulate and decode the baseband signals to extract raw data that can be processed by host chip 206.
  • Baseband chip 202 may perform additional functions, such as error checking, de-mapping, channel estimation, descrambling, etc.
  • baseband chip 202 may perform PSS correlation (for each narrowband raster frequency obtained from a wideband RF sample) using a set of IFOs estimated for each of the raster frequencies. More specifically, each IFO in the set of IFOs may be estimated for a different SCS step (e.g., 0.25 SCS, 0.5 SCS, etc.) across an SCS range (e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.). Each of the IFOs may be used in PSS correlation and/or convolution for its associated raster frequency.
  • PSS correlation for each narrowband raster frequency obtained from a wideband RF sample
  • each IFO in the set of IFOs may be estimated for a different SCS step (e.g., 0.25 SCS, 0.5 SCS, etc.) across an SCS range (e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.).
  • SCS step e.g. 0.25 SCS,
  • the PSS candidate with the largest correlation peak score may be selected for further processing.
  • this and other information determined for each raster frequency may be sent to a PHY layer controller, which may use the information in totality to determine which of the raster frequencies to acquire for initial cell selection.
  • PSS correlation may be extended to cell selection for 5G NR by enabling the UE to operate at the lower SNR conditions as compared to conventional approaches. Additional details of which are described below in connection with FIGs. 3A-4.
  • FIG. 3 A illustrates a detailed view of the baseband chip 202 of FIG. 2, according to some embodiments of the present disclosure.
  • FIG. 3B illustrates a detailed view of a PSS processing circuit 304 depicted in FIG. 3A, according to some embodiments of the present disclosure.
  • FIG. 3C illustrates a block diagram of an SSB 350, according to some embodiments of the present disclosure.
  • FIG. 3E illustrates a graphical representation 360 of the degradation of PSS correlation performance versus TO, according to some embodiments of the present disclosure.
  • FIG. 3F illustrates a graphical representation 370 of PSS correlation degradation due to FO, according to some embodiments of the present disclosure.
  • FIGs. 3 A-3E will be described together.
  • baseband chip 202 may include a plurality of functional blocks configured to perform PSS correlation that is compatible with initial cell selection for 5G NR communication. These functional blocks may include, e.g., a frequency shifting/decimating circuit 302 (hereinafter “FSD circuit 302”), a PSS processing circuit 304, a SSS processing circuit 306, a PBCH processing circuit 308, and an SSS/PBCH measurement circuit 310 (hereinafter referred to as “measurement circuit 310”). Each circuit in baseband chip 202 may be implemented as an integrated circuit (IC) dedicated to performing its functions disclosed herein, such as an ASIC. The operations may begin when a UE is switched from a powered off state to a powered- on state.
  • IC integrated circuit
  • a SSB 350 may be used by the baseband chip 202 of the UE to perform synchronization in the stage of initial cell selection.
  • a UE When a UE is powered on, it tries to find a cell for acquisition.
  • the UE’s initial task is to identify a proper frequency (e.g., RF sample) on which NR cells are deployed and that can be detected by the UE.
  • the SSB 350 of NR cells must be deployed on a synchronization raster frequency. That is, the synchronization raster indicates the frequency position of the SSBs that can be used by the UE for system acquisition during initial cell selection.
  • Each of the raster frequencies may be associated with a cell (e.g., base station), and the base station may transmit a SSB 350 on its dedicated raster frequency at predetermined intervals (e.g., 20ms) known a priori by the UE.
  • RF sample 301 may include a plurality of different SSBs each transmitted at predetermined intervals (e.g., 20ms) by a corresponding base station. As illustrated in FIG.
  • SSB 350 may include one or more PSS symbols 330, one or more SSS symbols 332, and one or more PBCH symbols 334, as illustrated in FIG. 3C.
  • RF sample 301 The receiver of baseband chip 202 in FIG. 2 may obtain a wideband RF sample 301 (hereinafter referred to as “RF sample 301”) that includes a plurality of RF signals each associated with a different narrowband frequency (also referred to as a “raster frequency”).
  • FSD circuit 302 may be configured to receive RF sample 301 as an input from the receiver (Rx) illustrated in FIG. 2, which may initiate the operations associated with initial cell selection described below.
  • FSD circuit 302 may be configured to translate RF sample 301 into lower sampling rate narrowband raster frequencies (hereinafter “raster frequencies”) for subsequent PSS/SSS/PBCH processing. Each of the raster frequencies may be associated with potential cells for selection by the UE. To obtain the plurality of raster frequencies from the RF sample 301, FSD circuit 302 may be configured to rotate the RF sample 301 by fixed amounts with respect to a SSB center frequency. For example, FSD circuit 302 may rotate RF sample 301 to a desired raster frequency as the RF center frequency may be different from the SSB center frequency.
  • SSB center frequency narrowband raster frequencies
  • the RF band usually is very wide, e.g., 20MHz, 40MHz, 100MHz bandwidth for NR.
  • SCS 15KHz
  • the SSB bandwidth is 3.6MHz.
  • the RF center frequency is different from an individual SSB center frequency.
  • RF center frequency and the SSB center frequency is D (in units of MHz), and that the RF sample must be rotated by the amount D, so that the RF sample can be shifted to the desired SSB center frequency, in order to qualify the SSB frequency with PSS and SSS detection.
  • FSD circuit 302 may include a decimator to lower the sampling rate of the individual raster frequencies.
  • the PSS/SSS symbol bandwidth in SSB 350 may be equal to 127 SCS, and, by Nyquist Sampling Theorem, the sampling rate to recover the PSS/SSS bandwidth is, at a minimum, 127 SCS.
  • the minimum sampling rate of 128 SCS is not large enough for high-quality PSS based detection, especially with practical impairments such as low SNR, fading, FO, TO, Doppler effect, etc.
  • the raster frequency 303 may be oversampled by a factor of 2 to achieve a sampling rate of 256 SCS.
  • a sampling rate of 256 SCS will capture the PBCH bandwidth of 240 SCS as well as the PSS/SSS symbol bandwidth of 127 SCS.
  • a sampling rate of 256 SCS will capture the demodulation reference signal(s) (DMRS) in PBCH symbols 334, which may further enhance the cell detection probability when used by baseband chip 202 for initial cell selection.
  • oversampling may increase the number of samples tested within the same or smaller time period, thereby increasing the probability of estimating the TO of PSS symbol 330 with a high degree of accuracy.
  • the graphical representation 370 of FIG. 3E illustrates the degradation of PSS correlation performance versus TO without any other impairments (e.g., FO, Doppler Effect, etc.).
  • the x-axis is the timing in the unit of Nyquist sampling period, and the y-axis is the degradation of correlation performance in dB. From graphical representation 370, it can be observed that, as TO increases from 0 to 0.5 period at Nyquist sampling rate, the degradation grows from 0 dB to - 1.95 dB, which is a significant degradation of performance.
  • Graphical representation 370 further illustrates that performance degradation increases to -0.45dB when the TO is greater than or equal to a 0.25 period at Nyquist sampling rate, where a TO of at least 0.25 period can be achieved by an oversampling rate of two.
  • a TO of at least 0.25 period can be achieved by an oversampling rate of two.
  • the worst case for TO is at most 0.25 period at Nyquist sampling rate, which could cause, at most, a performance loss of -0.45dB.
  • FSD circuit 302 may be configured to pass a raster frequency 303 through a low- pass filter before performing down sampling. By using a low-pass filter, FSD circuit 302 may perform anti-aliasing and remove any unnecessary signal/noise from the designated raster frequency 303 prior to passing the raster frequency 303 to one or more of PSS processing circuit 304, SSS processing circuit 306, PBCH processing circuit 308, and/or measurement circuit 310 for further processing.
  • SSB processing may begin with PSS processing circuit 304 as depicted in FIGs. 3A and 3B.
  • FIG. 3B illustrates two equivalent implementations that may be used by PSS processing circuit 304 for PSS correlation.
  • the upper branch in FIG. 3B that includes convolution circuit 314 e.g., a filter
  • the lower branch that includes Fourier Transform (FFT) 316, correlation circuit 318, and IFFT 320 illustrates the frequency domain implementation, respectively, where outputl 313 and output2 315 yield the same result.
  • Convolution circuit 314 in the time domain and correlation circuit 318 in the frequency domain may not have the same format, but these two circuits may be associated.
  • convolution circuit 314 e.g., a filter
  • correlation circuit 318 have a 1-to-l mapping
  • frequency-domain multiplication is equivalent to time-domain convolution.
  • FFT 316 and IFFT 320 are orthogonal transforms
  • time-domain correlation and frequency-domain correlation may be equivalent, that means, 1-to-l mapping or 1-to-l corresponding.
  • Correlation may be performed in either domain and achieve the result by applying either the filter or the correlator, correspondingly.
  • Convolution circuit 314 may be a PSS reference filter defined in the time domain and convoluted with the streaming samples of raster frequency 303. In this way, convolution circuit 314 may obtain the equivalent PSS correlation result in the time domain as well as the sample index for PSS location, correspondingly.
  • estimating IFOs at different SCS steps across an SCS range may require multiplication for each sample prior to performing convolution in the time domain.
  • multiplication may not be needed if correlation is considered in frequency domain with the help of subcarrier shifting.
  • the benefits of estimating a plurality of IFOs across an SCS range in the frequency domain is further enhanced with the use of FFT 316 and IFFT 320 because these two transforms reduce or eliminate multiplication, thereby reducing computational complexity and power consumption when estimating FO hypotheses, as compared to performing computations in the time domain.
  • PSS processing circuit 304 may be able to take advantage of correlation since, if the PSS sequence in the time domain and the PSS sequence in the frequency domain are similar, their normalized linear correlation coefficient may be relatively high.
  • the correlation result in the frequency domain e.g., output2315
  • FO is estimated to reduce and/or eliminate the signal disturbance caused by FO, since otherwise PSS correlation performance degrades as shown in FIG. 3F.
  • the FO of multiple SCSs can cause more than 20dB loss for
  • the SCS range across which the IFOs are estimated may be provided to PSS processing circuit 304 by the upper layer management, e.g., based upon the information from the largest possible FO in units of SCS.
  • FIG. 3F illustrates that the performance loss at 0.25 SCS is about 0.4768dB.
  • PSS processing circuit 304 estimates FO at the SCS step of 0.5
  • the performance degradation of PSS correlation at worst case, will be decreased from 2dB to 0.4768dB as compared to using a SCS step of 1.0.
  • the performance loss is less than 0.5 dB.
  • the FO error may be reduced as compared to conventional techniques. Reducing the FO error achieves a more accurate PSS correlation.
  • PSS processing circuit 304 may reduce the error associated with FO estimation is to perform correlation in the frequency domain with a resolution of 1.0 SCS. After determining IFO, compensating the related PSS samples with the estimated IFO first, the compensated and oversampled PSS samples then may be used to estimate the residual FO. Simulation shows that, with multiple antennas, the estimation accuracy can also reach 0.25 SCS in the sense of statistics. . Using this solution can reduce the number of IFFT iterations by half since a fine step is not needed for evaluating PSS correlation, and, in turn, increase processing speed and/or save power, but may be at the cost of performance sacrifice under condition of weak signal and severe fading.
  • chunk-based processing may be used to perform convolution in the time domain before implementation in the frequency domain.
  • convolution circuit 314 also referred to herein as “convolution filter”
  • convolution filter include a filter in time domain with length of L
  • any chunk of input samples to the filter for convolution with a size of M will generate M+L-l output samples (e.g., outputl 313).
  • M input samples may have M output samples by convolution with the convolution circuit 314.
  • some of the output samples may be dropped from the outputl 313.
  • sequence g may pass through filter f
  • the 3-tap filter of convolution circuit 314 attempts to sum over the three adjacent samples up to current sample timing index, it can be found that the first (3-1) arrays of y assume g has two more 0 samples assumed ahead of the first sample 0.1 and the last (3-1) arrays of y are incorrect.
  • each chunk of samples will be translated into frequency domain before doing correlation with the corresponding correlation circuit 318 (associated with convolution circuit 314 in time domain) of size of (L+M).
  • the corresponding correlation circuit 318 associated with convolution circuit 314 in time domain
  • correlation between NFFT pairs is done where the correlation output will be mapped back to time domain by IFFT. Since IFFT size is 1024 and the last M output samples are the convolution result of the first M input samples with the filter.
  • PSS processing circuit 304 may implement PSS score processing and related the samples of PSS/SSS can be saved (SSS samples could be in the next chunk, in this case, a “flag” will be used to imply that when the samples for the next chunk arrive, the PSS peak related SSS samples in this chunk will be firstly recorded). These PSS/SSS samples may be used for subsequent frequency offset estimation/compensation and SSS cell detection as well measurement.
  • PSS processing circuit 304 may conclude the detection by selecting the final PSS candidates for detection based on the results of PSS correlation. By oversampling by 2 times the Nyquist sampling rate (as discussed above) and searching for a cell in the raster frequency with step of 0.25 SCS (for low SNR and/or larger uncertain FO scenarios) can substantially reduce the correlation performance loss, and hence, the probability of finding the correct raster frequency and cell ID may be increased. Note that PSS processing circuit 304 may maintain the finite number of correlation peaks and the associated SSB samples for additional measurement, which may increase the chance of correct cell selection and raster frequency. This finite number of winners will be updated by the efficient sorting scheme when the new PSS peaks are found.
  • a threshold can be defined adaptively, which can be filtered out many detected PSS scores so that search is more meaningful and power-saving.
  • PSS processing circuit 304 may be configured to determine information 305 that includes coarse FO estimate, symbol timing, and the sector ID for each PSS candidate. Additional details associated with the operations performed by PSS processing circuit 304 are set forth below in connection with FIG. 4B.
  • PSS processing circuit 304 may be configured to input information 305 that includes coarse FO estimate, symbol timing, and the sector ID into SSS processing circuit 306. With the already estimated FO and PSS symbol timing determined by the largest correlation peak score, and using information 305, SSS processing circuit 306 may determine SSS symbol timing correspondingly, and the SSS samples can be extracted, and, with the proper FO compensation, SSS detection can be done more accurately, using the same correlation approach as discussed above in connection the PSS processing circuit 304 of FIG. 3B. SSS detection may be completed with up to 336 SSS references, much more than 3 PSS references. The reason there are many SSS sequencies is that the SSS sequences are related to cells. Due to capacity, hundreds of cells could be provided for many users. However, a single PSS sequence can be shared by many users, and the PSS sequence is used for estimating coarse FO and TO, as well as detecting sector ID for cell detection by SSS detection.
  • SSS symbol 332 can be used for reliable measurement for signal quality and strength, in addition to carrying information associated with the cell ID.
  • SSS processing circuit 306 may compensate the SSS samples with the FO estimated in time domain before demodulation in frequency domain.
  • SSS processing circuit 306 may input information 307 associated with the cell ID and the estimated FO into PBCH processing circuit 308. Additional details of the operations performed by SSS processing circuit 306 are set forth below in connection with FIG. 4C.
  • PBCH processing circuit 308 may be configured to perform PBCH processing to assign a value to each of the raster frequencies, where the value indicating a probability of correctness with respect to the estimated frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • Information 309 associated with the value for each of the plurality of raster frequencies may be input into measurement circuit 310. Additional details associated with the operations performed by PBCH processing circuit 308 are set forth below in connection with FIG. 4D.
  • measurement circuit 310 may be configured to measure one or more of the SSS or PBCH to estimate one or more of a received signal strength indicator (RSSI), reference signal received power (RSRP), reference signal received quality (RSRQ), signal to interference and noise ratio (SINR), a fine timing offset (TO), or a fine FO for each of the plurality of raster frequencies.
  • Measurement circuit 310 may be further configured to send information 311 associated with one or more of the sector ID, symbol timing, cell ID, symbol index, RSRP, RSRQ, SINR, fine TO, fine FO, or coarse FO to a PHY layer controller 312 for cell selection.
  • PHY layer controller 312 may select a cell and the associated raster frequency for acquisition. By increasing the number of signal indicators and including a raster frequency score, PHY layer controller 312 may have an increased probability of selecting the appropriate cell for 5G NR communication.
  • FIG. 4A illustrates a flow chart of an exemplary method 400 for wireless communication, according to some embodiments of the present disclosure.
  • Examples of the apparatus that can perform operations of method 400 include, for example, apparatus 200, baseband chip 202 (see circuits in FIG. 3A), or node 500. It is understood that the operations shown in method 400 are not exhaustive and that other operations can be performed as well before, after, or between any of the illustrated operations. Further, some of the operations may be performed simultaneously, or in a different order than shown in FIG. 4A.
  • baseband chip 202 may be configured to receive a RF sample.
  • the receiver of baseband chip 202 in FIG. 2 may obtain a wideband RF sample 301 (hereinafter referred to as “RF sample 301”) that includes a plurality of RF signals each associated with a different narrowband frequency (also referred to as a “raster frequency”).
  • RF sample 301 a wideband RF sample 301
  • FSD circuit 302 may be configured to receive RF sample 301 as an input from the receiver (Rx) illustrated in FIG. 2.
  • baseband chip 202 e.g., FSD circuit 302
  • FSD circuit 302 may be configured to rotate the
  • FSD circuit 302 may be configured to rotate the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, each raster frequency in the plurality of raster frequencies being associated with a rotation by one of the fixed amounts.
  • FSD circuit 302 may rotate RF sample 301 to a desired raster frequency as the RF center frequency may be different from the SSB center frequency. By rotating RF sample 301 by fixed amounts with respect to the SSB center frequency, a plurality of raster frequencies may be obtained for processing by the other circuits of baseband chip 202.
  • baseband chip 202 may be configured to estimate a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • each IFO in the set of IFOs may be estimated for a different SCS step (e.g., 0.25 SCS, 0.5 SCS, etc.) across an SCS range (e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.).
  • baseband chip 202 may be configured to perform PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • FIG. 3B illustrates the two equivalent implementations for PSS correlation.
  • the upper branch that includes convolution circuit 314 e.g., a filter
  • the lower branch that includes FFT 316, correlation circuit 318, and IFFT 320 illustrates the frequency domain implementation, respectively, where outputl 313 and output2315 yield the same result.
  • Convolution circuit 314 in the time domain and correlation circuit 318 in the frequency domain may not have the same format but these two circuits may be associated.
  • convolution circuit 314 e.g., a filter
  • correlation circuit 318 have a 1-to-l mapping. Therefore, because frequency-domain multiplication is equivalent to time-domain convolution, convolution circuit 314 may be a PSS reference filter defined in the time domain and convoluted with the streaming samples of raster frequency 303. In this way, convolution circuit 314 may obtain the equivalent PSS correlation result in the time domain as well as the sample index for PSS location, correspondingly.
  • estimating IFOs at different SCS steps across an SCS range may require multiplication for each sample prior to performing convolution in the time domain. On the other hand, multiplication may not be needed if correlation is considered in frequency domain with the help of subcarrier shifting.
  • PSS processing circuit 304 may be able to take advantage of correlation since, if the PSS sequence in the time domain and the PSS sequence in the frequency domain are similar, their normalized linear correlation coefficient may be relatively high.
  • the correlation result in the frequency domain (e.g., output2 315) may be defined by each of the three PSS references used to obtain a correlation peak in time domain, which may correspond to the PSS symbol starting timing.
  • baseband chip 202 may be configured to select a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies. For example, referring to FIG. 3A, baseband chip 202 may perform PSS correlation (for each narrowband raster frequency obtained from a wideband RF sample) using a set of IFOs estimated for each of the raster frequencies.
  • each IFO in the set of IFOs may be estimated for a different SCS step (e.g., 0.25 SCS, 0.5 SCS, etc.) across an SCS range (e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.).
  • SCS step e.g. 0.25 SCS, 0.5 SCS, etc.
  • SCS range e.g., -3 to + 3 SCS, -4 to + 4 SCS, etc.
  • PSS candidate with the largest correlation peak score may be selected for further processing.
  • baseband chip 202 e.g., PSS processing circuit 304 may be configured to process each PSS candidate to estimate a coarse FO, a sector identification (ID), and symbol timing for each of the plurality of raster frequencies.
  • PSS processing circuit 304 may be configured to determine information 305 that includes coarse FO estimate, symbol timing, and the sector ID for each PSS candidate. Additional details related to PSS processing by PSS processing circuit 304 are set forth below in connection with FIG. 4C.
  • baseband chip 202 may be configured to perform SSS processing to estimate a cell ID and frequency offset for each of the plurality of raster frequencies. SSS processing may be performed based at least in part on the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • PSS processing circuit 304 may be configured to input information 305 that includes coarse FO estimate, symbol timing, and the sector ID into SSS processing circuit 306.
  • SSS processing circuit 306 may determine SSS symbol timing correspondingly, and the SSS samples can be extracted, and, with the proper FO compensation, SSS detection can be done more accurately, using the same correlation approach as discussed above in connection the PSS processing circuit 304 of FIG. 3B.
  • SSS detection may be completed with up to 336 SSS references, much more than 3 PSS references.
  • the large number of SSS references not only provides more capability for service, but also reduces the chance of interference between cells or neighbor cells.
  • SSS symbol 332 can be used for reliable measurement for signal quality and strength, in addition to carrying information associated with the cell ID.
  • SSS processing circuit 306 may compensate the SSS samples with the FO estimated in time domain before demodulation in frequency domain. Additional details related to SSS processing by SSS processing circuit 306 are set forth below in connection with FIG. 4C.
  • baseband chip 202 may be configured to perform PBCH processing to assign a value to each of the raster frequencies, the value indicating a probability of correctness with respect to the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • PBCH processing circuit 308 may be configured to perform PBCH processing to assign a value to each of the raster frequencies, where the value indicating a probability of correctness with respect to the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies. Additional details associated with the operations performed by PBCH processing circuit 308 are set forth below in connection with FIG. 4D.
  • Information 309 ass associated with the value for each of the plurality of raster frequencies to a measurement circuit. Additional details associated with the operations performed by PBCH processing circuit 308 are described below in connection with FIG. 4D.
  • baseband chip 202 may be configured to inputting information associated with the value for each of the plurality of raster frequencies to a measurement circuit. For example, referring to FIG. 3A, Information 309 associated with the value for each of the plurality of raster frequencies may be input into measurement circuit 310.
  • baseband chip 202 e.g., measurement circuit 310) may be configured to measure one or more of the SSS or PBCH symbols to estimate one or more of a RSSI, RSRP, reference signal received quality (RSRQ), SINR, a fine TO, or a fine FO for each of the plurality of raster frequencies. For example, referring to FIG.
  • measurement circuit 310 may be configured to measure one or more of the SSS or PBCH to estimate one or more of a received signal strength indicator (RSSI), reference signal received power (RSRP), reference signal received quality (RSRQ), signal to interference and noise ratio (SINR), a fine timing offset (TO), or a fine FO for each of the plurality of raster frequencies.
  • RSSI received signal strength indicator
  • RSRP reference signal received power
  • RSSRQ reference signal received quality
  • SINR fine TO, fine FO, or coarse FO
  • measurement circuit 310 may be further configured to send information 311 associated with one or more of the sector ID, symbol timing, cell ID, symbol index RSRP, RSRQ, SINR, fine TO, fine FO, or coarse FO to a PHY layer controller 312 for cell selection.
  • PHY layer controller 312 may select a cell and the associated raster frequency for acquisition.
  • FIG. 4B illustrates a flow chart of a second exemplary method 401 for wireless communication of a PSS processing circuit, according to some embodiments of the present disclosure.
  • Examples of the apparatus that can perform operations of method 401 include, for example, apparatus 200, PSS processing circuit 304, or node 500. It is understood that the operations shown in method 400 are not exhaustive and that other operations can be performed as well before, after, or between any of the illustrated operations. Further, some of the operations may be performed simultaneously, or in a different order than shown in FIG. 4B.
  • FIG. 4C illustrates a flow chart of a third exemplary method 403 for wireless communication of a SSS processing circuit 306, according to some embodiments of the present disclosure.
  • FIG. 4D illustrates a flow chart of a fourth exemplary method 403 for wireless communication of a PBCH processing circuit 308, according to some embodiments of the present disclosure.
  • Examples of the apparatus that can perform operations of method 403 include, for example, apparatus 200, PBCH processing circuit 308, or node 500.
  • PSS processing circuit 304 may be configured to buffer a raster frequency 303 that has been frequency shifted and decimated by FSD circuit 302.
  • PSS processing circuit 304 may be configured to fetch one or more SSB samples from the buffer for further processing.
  • PSS processing circuit 304 may be configured to input the SSB sample(s) into an FFT.
  • FFT 316 and IFFT 320 the benefits of estimating a plurality of IFOs across an SCS range in the frequency domain is further enhanced with the use of FFT 316 and IFFT 320 because these two transforms reduce or eliminate multiplication, thereby reducing computational complexity and power consumption when estimating FO hypotheses, as compared to performing computations in the time domain.
  • PSS processing circuit 304 may be configured to perform PSS correlation of the samples that are output by an FFT. For example, referring to FIGs 3B and 3F, estimating IFOs at different SCS steps across an SCS range may require multiplication for each sample prior to performing convolution in the time domain. On the other hand, multiplication may not be needed if correlation is considered in frequency domain with the help of subcarrier shifting. The benefits of estimating a plurality of IFOs across an SCS range in the frequency domain is further enhanced with the use of FFT 316 and IFFT 320 because these two transforms reduce or eliminate multiplication, thereby reducing computational complexity and power consumption when estimating FO hypotheses in frequency domain, as compared to performing computations in the time domain.
  • the correlation result in the frequency domain may be defined by each of the three PSS references used to obtain a correlation peak in time domain, which may correspond to the PSS symbol starting timing.
  • FO is estimated to reduce and/or eliminate the signal disturbance caused by FO, since otherwise PSS correlation performance degrades as shown in FIG. 3F.
  • the FO of multiple SCSs can cause more than 20dB loss for PSS correlation performance in the presence of large FO. Therefore, estimating IFOs of different SCS may be of great benefit when estimating FO.
  • the SCS range across which the IFOs are estimated may be provided to PSS processing circuit 304 by the upper layer management, e.g., based upon the information from the largest possible FO in units of SCS.
  • a sweep across an SCS range of -4 to +4 with IFOs estimated for ⁇ -4, -3, -2, -1, 0, +1, +2, +3, +4 ⁇ with an SCS step of 1.
  • the SCS range is - 2 to +2, with IFOs estimated at ⁇ -2, -1, 0, +1, +2 ⁇ with a SCS step of 1.
  • the largest PSS peak may be correlated with the PSS reference and the corresponding rotated IFO rotated samples, which gives the estimated IFO for that SCS step.
  • the final error of FO should be no more than half of the step size.
  • the FO is further narrowed down in fine resolution (also referred to herein as “fine FO”) and the FO is estimated using an SCS step of 0.5 rather than 1.0, the residual FO may be no more than 0.25 SCS.
  • FIG. 3F illustrates that the performance loss at 0.25 SCS is about 0.4768dB.
  • PSS processing circuit 304 estimates FO at the SCS step of 0.5, the performance degradation of PSS correlation, at worst case, will be decreased from 2dB to 0.4768dB as compared to using a SCS step of 1.0.
  • Another way in which PSS processing circuit 304 may reduce the error associated with FO estimation is to perform correlation in the frequency domain with a resolution of 1.0 SCS or fractional SCS such as 0.5 SCS or 0.25 SCS. After determining IFO, compensating the related PSS samples with the estimated IFO first, the compensated and oversampled PSS samples then may be used to estimate the residual FO. Using this solution of FO hypotheses plus residual FO estimation can reduce the number of IFFT iterations by half, and, in turn, increase processing speed and/or save power, but at the cost of performance sacrifice under condition of weak signal and severe fading.
  • PSS processing circuit 304 may be configured to determine whether IFO has been estimated for all SCS steps (also referred to as “SCS bins”) in the SCS range. When it is determined (at 438) that an IFO for all SCS steps has not been computed, the operation may return to 436 for subsequent IFO estimation for the subsequent SCS step. Otherwise, when it is determined (at 438) that an IFO for each of the SCS steps in the range has been estimated, the operations may move to 440.
  • PSS processing circuit 304 may be configured to input the IFOs through
  • the correlation result in the frequency domain may be defined by each of the three PSS references used to obtain a correlation peak in time domain, which may correspond to the PSS symbol starting timing.
  • FO is estimated and compensated to reduce and/or eliminate the signal disturbance caused by FO, since otherwise, PSS correlation performance degrades as shown in FIG. 3F.
  • PSS processing circuit 304 may be configured to calculate the sample signal power associated with the raster frequency being tested. Then, at 444, PSS processing circuit 304 may be configured to perform power normalization of the PSS correlation results (e.g., output2 315) based at least in part on the sample signal power.
  • PSS processing circuit 304 may be configured to determine whether all antennas have been tested for the received RF sample 301. When it is determined (at 446) that all of the antennas have not been tested, then the operation may return to 434, where a raster frequency associated with another antenna may be tested. Otherwise, when it is determined (at 446) that all of the antennas have been tested, then the operation may move to 448.
  • PSS processing circuit 304 may be configured to perform antenna combining to combine the information associated with PSS correlation from all the antennas for that particular raster frequency.
  • the result by PSS correlation from various antennas may be combined, that is, under the same conditions (e.g., raster frequency, offset from the raster frequency, PSS ID, sampling time, etc.), and the results from individual antenna (e.g., after power normalization) may be added together. Since this addition assigns the same weight to each of antennas, it is sometimes referred to as “equal-gain combining.” In turn, the final PSS correlation result may be achieved through equal-gain combining.
  • PSS processing circuit 304 may be configured to sort PSS correlation results and obtain PSS candidates for further processing. For example, referring to FIG. 3A, PSS processing circuit 304 may conclude the detection by selecting the final PSS candidates for detection based on the results of PSS correlation. By oversampling by 2 times the Nyquist sampling rate (as discussed above) and searching for a cell in the raster frequency with step of 0.5 SCS can substantially reduce the correlation performance loss, and hence, the probability of finding the correct raster frequency and cell ID may be increased.
  • PSS processing circuit 304 may maintain the finite number of correlation peaks and the associated SSB samples for additional measurement, which may increase the chance of correct cell selection and raster frequency. This finite number of winners will be updated by the efficient sorting scheme when the new PSS peaks are found through an optimization scheme.
  • a threshold can be defined adaptively, which can be filtered out many detected PSS scores so that search is more meaningful and power-saving.
  • a merge-and-prune scheme could be also applied.
  • PSS processing circuit 304 may be configured to determine a coarse FO for each of the PSS candidates.
  • PSS processing circuit 304 may be configured to determine information 305 that includes coarse FO estimate, symbol timing, and the sector ID for each PSS candidate.
  • SSS processing circuit 308 may be configured to buffer raster frequency samples after frequency shifting and decimation by FSD circuit 302.
  • SSS processing circuit may be configured to fetch SSS samples from the buffer for further processing. Processing of raster frequencies may be for the PSS candidates determined by PSS processing circuit 304. Information associated with the symbol timing of the candidate may be received from PSS processing circuit 304.
  • SSS processing circuit may be configured to perform coarse FO compensation based at least in part on the coarse FO and SCS step determined by PSS processing circuit 304 for that raster frequency candidate.
  • SSS processing may input the selected candidate through an FFT as described above in connection with the PSS processing circuit in FIG. 4B.
  • SSS processing circuit 306 may be configured to perform descrambling of the SSS samples based at least in part on the sector ID of that PSS candidate.
  • SSS processing circuit may be configured to calculate the SSS sample power.
  • SSS processing circuit 306 may be configured to perform SSS correlation and normalization.
  • SSS correlation may be performed using the same or similar techniques as PSS correlation described above in connection with FIGs. 3B, 3F, and 4B.
  • SSS normalization may be performed using the sample power calculated for the SSS sample.
  • SSS processing circuit 306 may be configured to determine whether all antennas have been tested for the SSS sample. When it is determined (at 474) that all the antennas have not been tested, then the operation may return to 460, where a raster frequency associated with another antenna may be tested. Otherwise, when it is determined (at 474) that all of the antennas have been tested, then the operation may move to 476.
  • SSS processing circuit 306 may be configured to perform antenna combining to combine the information associated with PSS correlation from all the antennas for that raster frequency.
  • SSS processing circuit 306 may be configured to perform SSS detection.
  • SSS processing circuit 306 may be configured to determine whether there are additional candidates from the PSS result in FIG. 4B for processing. When it is determined (at 480) that there are more additional candidates yet to be tested, the operation may return to 460 for selection of the subsequent candidate. Otherwise, when it is determined (at 480) that all candidates have been tested, the operation may move to 482.
  • SSS processing circuit 306 may be configured to rank each of the raster frequency candidates. For example, each SSS detection may provide the cell ID with its correlation result score (e.g., a positive number). As SSS detection is processed at the given frequency, measured by the raster frequency, the step of frequency offset (e.g., 0.25 SCS), and the coarse FO estimation, the SSS score may be associated with a specific frequency and at some sampling timing. The SSS score can be measured by antenna combining. For example, the SSS score may be sorted from large to small, and the relevant information, e.g., such as raster frequency, FO provided by PSS coarse FO estimation, sample index for sampling timing, and the measurement result such as RSSI may be recorded.
  • the relevant information e.g., such as raster frequency, FO provided by PSS coarse FO estimation, sample index for sampling timing, and the measurement result such as RSSI may be recorded.
  • the larger score means that more likely the SSS detection is correct, and hence, it may be assumed to be the correctly detected SSS ID. Since each PSS ID may correspond to many SSS IDs, it can be found that SSS detection (already applying PSS ID in SSS detection) and the associated SSS ID (and so cell ID, composed of PSS and SSS ID) may be more reliable.
  • the final score for the cell may include both the SSS and PSS score with different weights applied thereto. A large weight applied to the SSS score and a small weight applied to the PSS score may generate the corresponding cell score if PSS symbol has more receive power or assumed comparatively reliable, for instance, if the interference nearby is strong and SSS detection may be less reliable, but not limited.
  • SSS processing circuit 306 may be configured to perform fine FO estimation. For example, assuming PSS-based coarse FO estimation is successful, with the compensation by coarse FO estimation in the time domain, input data samples to SSS detection may have less FO as only the residual FO may remain with the input to SSS detection. This reduction of FO of input data samples may enhance the SSS detection and increase its accuracy.
  • the SSS ID also referred to as “group ID”
  • group ID the SSS ID
  • the SSS sequence in time domain may be generated, which may be chosen as the reference signal in comparison with the corresponding coarse-FO-compensated SSS input, to achieve FO estimation.
  • the current SSS-based FO estimation may provide an even smaller FO estimation, also referred to as the “fine FO.”
  • the sum of the coarse FO and the fine FO may be the amount of FO for this specific cell ID at this frequency and sampling timing.
  • SSS processing circuit 306 may be configured to perform a signal quality measurement to estimate RSRP, RSRQ, RSSI, etc. Information determined by SSS processing circuit 306 may be input into PBCH processing circuit 308 and/or measurement circuit 310.
  • An optimization scheme perhaps, by nonlinear filtering and adaptive filtering with information of RSRP, RSSI, FO estimated, could be applied to reduce the false-alarming rate of cell detection. By such optimization scheme, cell detection rate can be increased, and the subsequent processing will be more efficient.
  • PBCH processing circuit 308 may be configured to buffer raster frequencies that have been frequency shifted and decimated by FSD circuit 302.
  • PBCH processing circuit 308 may be configured to fetch PBCH samples from the buffer. The PBCH samples may be fetched based at least in part on the symbol timing determined by PSS processing circuit 304.
  • PBCH processing circuit 308 may be configured to perform FO compensation of the PBCH samples based at least in part on the coarse FO and fine FO estimated by PSS processing circuit 304 and SSS processing circuit 306.
  • PBCH processing circuit 308 may be configured to pass the FO compensated PBCH samples through an FFT as described above in connection with FIGs. 3B and 4B.
  • PBCH processing circuit 308 may be configured to perform channel estimation, noise estimation, equalization and DMRS detection of the PBCH samples based at least in part on the cell ID determined by SSS processing circuit 306 to estimate an SSB index and timing.
  • PBCH processing circuit 308 may be configured to perform PBCH decoding to decode master information block that includes SCS and subframe number (SFN).
  • PBCH processing circuit 308 may be configured to estimate and measure PBCH symbols to obtain a more accurate FO, TO, and RSRP. The information generated and/or obtained by PBCH processing circuit 308 may be input into measurement circuit 310 in FIG. 3B.
  • the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or encoded as instructions or code on a non-transitory computer-readable medium.
  • Computer-readable media includes computer storage media. Storage media may be any available media that can be accessed by a computing device, such as node 500 in FIG. 5.
  • such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, HDD, such as magnetic disk storage or other magnetic storage devices, Flash drive, SSD, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a processing system, such as a mobile device or a computer.
  • Disk and disc includes CD, laser disc, optical disc, DVD, and floppy disk where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
  • a baseband chip may include a frequency shifting/decimation circuit configured to receive a RF sample. Frequency shifting/decimation circuit may be further configured to rotate the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, where each raster frequency in the plurality of raster frequencies may be associated with a rotation by one of the fixed amounts.
  • the baseband chip may further include a PSS processing circuit configured to estimate a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • the PSS processing circuit may be further configured to perform PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the PSS processing circuit may be also configured to select a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate is selected for use in SSB detection.
  • the PSS processing circuit is further configured to process each PSS candidate to estimate a coarse FO, a sector ID, and symbol timing for each of the plurality of raster frequencies.
  • the baseband chip may further include a SSS processing circuit configured to perform SSS processing to estimate a cell ID and residual FO for each of the plurality of raster frequencies, where the SSS processing may be performed based at least in part on the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the baseband chip may further include a PBCH processing circuit configured to perform PBCH processing to assign a value to each of the raster frequencies, the value indicating a probability of correctness with respect to the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the PBCH processing circuit may be further configured to inputting information associated with the value for each of the plurality of raster frequencies to a measurement circuit.
  • the baseband chip may further include a measurement circuit is configured to measure one or more of the SSS or PBCH to estimate one or more of a RSSI, RSRP, RSRQ, SINR, a TO, or a fine FO for each of the plurality of raster frequencies.
  • the measurement circuit may be further configured to send information associated with one or more of the sector ID, symbol timing, cell ID, SSB index, RSSI, RSRP, RSRQ, SINR, fine TO, fine FO, or coarse FO to a PHY layer controller for cell selection.
  • the frequency shifting/decimation circuit may be further configured to decimate each of the plurality of raster frequencies obtained from the RF sample.
  • an apparatus is disclosed.
  • the apparatus may include a receiver configured to receive an RF sample.
  • the apparatus may also include a baseband chip.
  • the baseband chip may include a frequency shifting/decimation circuit configured to receive a RF sample. Frequency shifting/decimation circuit may be further configured to rotate the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, where each raster frequency in the plurality of raster frequencies may be associated with a rotation by one of the fixed amounts.
  • the baseband chip may further include a PSS processing circuit configured to estimate a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • the PSS processing circuit may be further configured to perform PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the PSS processing circuit may be also configured to select a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate is selected for use in SSB detection.
  • the PSS processing circuit is further configured to process each PSS candidate to estimate a coarse FO, a sector ID, and symbol timing for each of the plurality of raster frequencies.
  • the baseband chip may further include a SSS processing circuit configured to perform SSS processing to estimate a cell ID and fine FO for each of the plurality of raster frequencies, where the SSS processing may be performed based at least in part on the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the baseband chip may further include a PBCH processing circuit configured to perform PBCH processing to assign a value to each of the raster frequencies, the value indicating a probability of correctness with respect to the frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the PBCH processing circuit may be further configured to inputting information associated with the value for each of the plurality of raster frequencies to a measurement circuit.
  • the baseband chip may further include a measurement circuit which is configured to measure one or more of the SSS or PBCH to estimate one or more of a RSSI, RSRP, RSRQ, SINR, a TO, or a fine FO for each of the plurality of raster frequencies.
  • the measurement circuit may be further configured to send information associated with one or more of the sector ID, symbol timing, cell ID, symbol index, RSRP, RSRQ, SINR, fine TO, fine FO, or coarse FO to a PHY layer controller for cell selection.
  • the frequency shifting/decimation circuit may be further configured to decimate each of the plurality of raster frequencies obtained from the RF sample.
  • a method may include receiving, by a receiver, a RF sample.
  • the method may further include rotating, by a frequency shifting/decimation circuit, the RF sample by fixed amounts with respect to a SSB center frequency to obtain a plurality of raster frequencies, each raster frequency in the plurality of raster frequencies being associated with a rotation by one of the fixed amounts.
  • the method may also include estimating, by a PSS processing circuit, a set of IFOs for each raster frequency in the plurality of raster frequencies, where each IFO in the set of IFOs may be estimated for a different SCS step across an SCS range.
  • the method may also include performing, by the PSS processing circuit, PSS correlation for each IFO in the set of IFOs associated with each of the plurality of raster frequencies.
  • the method may also include selecting, by the PSS processing circuit, a PSS candidate for each raster frequency based at least in part on the PSS correlation performed for each of the plurality of raster frequencies, where the PSS candidate may be selected for use in SSB detection.
  • the method may further include processing, by the PSS processing circuit, each
  • PSS candidate to estimate a coarse FO, a sector ID, and symbol timing for each of the plurality of raster frequencies.
  • the method may also include performing, by a SSS processing circuit, SSS processing to estimate a cell ID and symbol index for each of the plurality of raster frequencies, the SSS processing being performed based at least in part on the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the method may further include performing, by a PBCH processing circuit, PBCH processing to assign a value to each of the raster frequencies, the value indicating a probability of correctness with respect to the coarse frequency offset, sector ID, and the symbol timing estimated for each of the plurality of raster frequencies.
  • the method may also include inputting, by the PBCH processing circuit, information associated with the value for each of the plurality of raster frequencies to a measurement circuit.
  • the method may further include measuring, by the measurement circuit, one or more of the SSS or PBCH to estimate one or more of a RSSI, RSRP, RSRQ, SINR, a fine TO, or a fine FO for each of the plurality of raster frequencies.
  • the method may also include sending, for each of the plurality of raster frequencies, information associated with one or more of the sector ID, symbol timing, cell ID, SSB index, RSSI, RSRP, RSRQ, SINR, fine TO, fine FO, or coarse FO to a PHY layer controller for cell selection.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Manipulation Of Pulses (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

L'invention concerne une puce de bande de base qui peut comprendre un circuit de décalage/décimation de fréquence (FSD) conçu pour recevoir un échantillon de radiofréquence (RF). Le circuit FSD peut faire tourner l'échantillon RF par des quantités fixes par rapport à une fréquence centrale de bloc de signal de synchronisation (SSB) pour obtenir une pluralité de fréquences de trame. La puce de bande de base peut en outre comprendre un circuit de traitement de signal de synchronisation primaire (PSS) qui peut estimer un ensemble de décalages de fréquence entiers (IFO) pour chaque fréquence de trame dans la pluralité de fréquences de trame, chaque IFO pouvant être estimé pour une étape SCS différente dans une plage de SCS. Le circuit de traitement PSS peut effectuer une corrélation PSS pour chaque IFO. Le circuit de traitement PSS peut sélectionner un candidat PSS pour chaque fréquence de trame sur la base, au moins en partie, de la corrélation PSS effectuée pour chacune des fréquences de trame.
PCT/US2021/022634 2020-03-19 2021-03-16 Appareil et procédé de sélection de cellule flexible WO2021113883A2 (fr)

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WO2023140852A1 (fr) * 2022-01-20 2023-07-27 Zeku, Inc. Appareil et procédé mettant en œuvre une estimation de décalage de fréquence
WO2023200445A1 (fr) * 2022-04-14 2023-10-19 Zeku, Inc. Appareil et procédé de détection de cellule

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