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WO2023200445A1 - Appareil et procédé de détection de cellule - Google Patents

Appareil et procédé de détection de cellule Download PDF

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Publication number
WO2023200445A1
WO2023200445A1 PCT/US2022/024871 US2022024871W WO2023200445A1 WO 2023200445 A1 WO2023200445 A1 WO 2023200445A1 US 2022024871 W US2022024871 W US 2022024871W WO 2023200445 A1 WO2023200445 A1 WO 2023200445A1
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WIPO (PCT)
Prior art keywords
sss
samples
pss
cell
candidate cell
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Ceased
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PCT/US2022/024871
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English (en)
Inventor
Ping Hou
Jian Gu
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Zeku Inc
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Zeku Inc
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Filing date
Publication date
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Priority to PCT/US2022/024871 priority Critical patent/WO2023200445A1/fr
Publication of WO2023200445A1 publication Critical patent/WO2023200445A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/16—Discovering, processing access restriction or access information
    • 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

Definitions

  • Embodiments of the present disclosure relate to apparatuses and methods for wireless communication.
  • Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasts.
  • wireless communication systems such as the 4th-generation (4G) Long Term Evolution (LTE) or the 5 th- generation (5G) New Radio (NR)
  • 4G Long Term Evolution
  • 5G 5 th- generation
  • UE user equipment
  • LTE Long Term Evolution
  • NR 5 th- generation
  • a user equipment acquires synchronization with a cell both in a time domain and in a frequency domain.
  • the UE of a wireless communication network may have possessed prior knowledge about one or more candidate cells, the information of which may help cell search.
  • the apparatus may include a processor and memory storing instructions that, when executed by the processor, may cause the processor to determine a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell.
  • a PSS processing for the candidate cell may be performed based on the PSS reference and samples to estimate a frequency offset (FO).
  • the samples may include samples collected in a time domain.
  • An SSS processing for the candidate cell may be performed based on the FO, the samples, and the SSS reference to obtain an SSS correlation score of the candidate cell.
  • the candidate cell In response to the SSS correlation score of the candidate cell being greater than a threshold, the candidate cell may be added to one or more qualified cells, and a physical broadcast channel (PBCH) processing may be performed based on the one or more qualified cells.
  • PBCH physical broadcast channel
  • the method may include determining a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell.
  • a PSS processing for the candidate cell may be performed based on the PSS reference and received samples to estimate a frequency offset (FO).
  • An SSS processing for the candidate cell may be performed based on the FO, the received samples, and the SSS reference to obtain an SSS correlation score of the candidate cell.
  • the candidate cell may be added to one or more qualified cells, and a physical broadcast channel (PBCH) processing may be performed based on the one or more qualified cells.
  • PBCH physical broadcast channel
  • the apparatus may include a processor and memory storing instructions that, when executed by the processor, cause the processor to determine a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell.
  • PSS samples and SSS samples may be extracted from received samples based on the PSS reference.
  • the PSS samples may be compensated based on the PSS reference to obtain compensated PSS samples
  • the SSS samples may be compensated based on the SSS reference to obtain compensated SSS samples.
  • Cell detection results corresponding to the candidate cell, may be determined based on the compensated PSS samples, the compensated SSS samples, the PSS reference, and the SSS reference.
  • PBCH processing may be performed based on the candidate cell.
  • FIG. 1 illustrates an exemplary wireless network, according to some embodiments of the present disclosure.
  • FIG. 2 illustrates a block diagram of an exemplary node, according to some embodiments of the present disclosure.
  • FIG. 3 illustrates a block diagram of an apparatus including a baseband chip, a radio frequency chip, and a host chip, according to some embodiments of the present disclosure.
  • FIG. 4 illustrates a block diagram of a synchronization signal block, according to some embodiments of the present disclosure.
  • FIG. 5 illustrates a block diagram of an expanded view of a portion of the baseband chip of FIG. 3, according to some embodiments of the present disclosure.
  • FIG. 6 illustrates a flow diagram of an exemplary method of cell detection, according to some embodiments of the present disclosure.
  • FIG. 7 illustrates a flow diagram of an exemplary method of primary synchronization signal (PSS) processing in cell detection, according to some embodiments of the present disclosure.
  • PSS primary synchronization signal
  • FIG. 8 illustrates a block diagram of an expanded view of a portion of a PSS processing module of FIG. 5, according to some embodiments of the present disclosure.
  • FIG. 9 illustrates a flow diagram of an exemplary method of secondary synchronization signal (SSS) processing in cell detection, according to some embodiments of the present disclosure.
  • SSS secondary synchronization signal
  • references in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” “some embodiments,” “certain embodiments,” “other embodiments,” “some instances,” “an instance,” 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.
  • terminology may be understood at least in part from usage in context.
  • 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 the 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.
  • Cell search is an initial process by which any available base station is identified by a user equipment (UE) that requests the communication. During the process, the UE acquires synchronization with the base station (a cell) in a time domain as well as in a frequency domain, and a cell identification (ID) of the cell is accordingly decoded. Synchronization, either in wired or wireless communication systems, plays a key role in communication networks. After the cell search procedure consisting of serial processes of synchronization, the UE obtains the precise timing of the symbols from the cell.
  • UE user equipment
  • the time used by the UE at weak signals to acquire a wireless network decides a UE experience.
  • the proper cell ID having good signal quality over a specific frequency, designated by the wireless network as a serving cell, may be connected for subsequent uplink and downlink communications.
  • the time and frequency domains are required to be aligned between the UE and the base station, for the synchronization purpose, to acquire signals simultaneously from the base station. Synchronization enables successful communications between nodes on the communication networks, particularly being vital for wireless communication.
  • a UE that wakes up from a discontinuous reception (DRX) mode may also require performing a cell search so as to maintain the time and frequency synchronization with a cell.
  • a UE may switch to the DRX mode when, e.g., the UE does not need to continuously monitor all possible paging or other channels if downlink data packets are only received intermittently.
  • the UE may allow itself to turn off the radio frequency (RF) chip during a predefined time period at a DRX mode. While the RF chip is switched off, however, the UE may lose the synchronization as established earlier. As a result, the UE may need to wake up earlier before the predefined time period in order to perform the synchronization again.
  • RF radio frequency
  • such synchronization is mainly performed using the synchronization signals that include the primary synchronization signals (PSSs) and the secondary synchronization signals (SSSs).
  • PSSs primary synchronization signals
  • SSSs secondary synchronization signals
  • the precise timing is crucial to, e.g., subsequent demodulation of downlink signals and transmission of uplink signals.
  • subsequent procedures e.g., the channel estimation and physical broadcast channel (PBCH) detection/decoding, may be accomplished and/or enhanced. Accordingly, the channel performance may be improved.
  • PBCH physical broadcast channel
  • a UE may be configured to scan the power on a given carrier frequency. If the detected power is strong enough, it is assumed that cell signals may be existent and that a PSS detection can be explored over the frequency. If a PSS detection result upon the PSS detection is at a high confidence level, the UE will perform an SSS detection to find more information about the cell. Further, if an SSS detection result is also reliable such that the cell acquired by both the PSS and SSS sequences is potentially a correct cell, in terms of probability levels, a next step (e.g., a PBCH detection) will be performed for confirming the overall cell detection, and the network information is accordingly obtained.
  • a next step e.g., a PBCH detection
  • the frequencies and cell IDs can be those that were either used or most frequently used in the past by the UE.
  • the history information may shorten a cell search. Nevertheless, in these approaches, an exhaustive search obviously ignores the history information, thereby resulting in unnecessary implementation complexity and consumption of time and hardware/software resources.
  • the present disclosure accordingly provides inventive approaches in regard to apparatuses and methods of cell detection.
  • the UE may have possessed prior knowledge about one or more candidate cells on specific frequencies and with cell IDs, the UE may be configured to first search with respect to a limited set of these cells having a higher confidence level, to accelerate the system acquisition and synchronization, thereby reducing the resource consumption and network complexity and improving the user experience.
  • a UE may be configured to utilize side information including, but not limited to, history information such as a carrier frequency, a cell ID, and location information, the like, or a combination thereof, to realize the proposed method of cell detection.
  • side information including, but not limited to, history information such as a carrier frequency, a cell ID, and location information, the like, or a combination thereof.
  • the UE can achieve a better sensitivity level and reduce the network acquisition time and complexity, thus improving the user experience.
  • the time-diversity combination (highly influenced by accurate estimation and compensation for the sample clock frequency offset, the estimation/compensation for the potential channel variation, and their associated effects) can be accordingly avoided.
  • 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
  • UE 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 Intemet-of-Things (loT) node.
  • V2X vehicle to everything
  • cluster network such as a cluster network, a smart grid node, or an Intemet-of-Things (loT) node.
  • UE 102 is illustrated as a mobile phone simply by way of illustration and not by way of limitation.
  • Access node 104 may be a device that communicates with UE 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 UE 102, a wireless connection to UE 102, or any combination thereof.
  • Access node 104 may be connected to UE 102 by multiple connections, and UE 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.
  • Core network element 106 may serve access node 104 and UE 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 108, or another Internet Protocol (IP) network, to communicate packet data over any distance.
  • a large network such as the Internet 108, or another Internet Protocol (IP) network
  • IP Internet Protocol
  • data from UE 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.
  • IP Internet Protocol
  • a generic example of a rack-mounted server is provided as an illustration of core network element 106.
  • database servers such as a database 116
  • 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 manage 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 manage 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 200 in FIG. 2.
  • Node 200 may be configured as UE 102, access node 104, or core network element 106 in FIG. 1.
  • node 200 may also be configured as computer 110, router 114, tablet 112, database 116, or authentication server 118 in FIG. 1.
  • node 200 may include a processor 202, a memory 204, and a transceiver 206. These components are shown as connected to one another by a bus, but other connection types are also permitted.
  • node 200 When node 200 is UE 102, additional components may also be included, such as a user interface (UI), sensors, and the like. Similarly, node 200 may be implemented as a blade in a server system when node 200 is configured as core network element 106. Other implementations are also possible.
  • UI user interface
  • sensors sensors
  • core network element 106 Other implementations are also possible.
  • Transceiver 206 may include any suitable device for sending and/or receiving data.
  • Node 200 may include one or more transceivers, although only one transceiver 206 is shown for simplicity of illustration.
  • An antenna 208 is shown as a possible communication mechanism for node 200. Multiple antennas and/or arrays of antennas may be utilized for receiving multiple spatially multiplex data streams.
  • examples of node 200 may communicate using wired techniques rather than (or in addition to) wireless techniques.
  • access node 104 may communicate wirelessly to UE 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 200 may include processor 202. Although only one processor is shown, it is understood that multiple processors can be included.
  • Processor 202 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 202 may be a hardware device having one or more processing cores.
  • Processor 202 may execute software.
  • node 200 may also include memory 204. Although only one memory is shown, it is understood that multiple memories can be included. Memory 204 can broadly include both memory and storage.
  • memory 204 may include random-access memory (RAM), read-only memory (ROM), static RAM (SRAM), dynamic RAM (DRAM), ferroelectric 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 202.
  • RAM random-access memory
  • ROM read-only memory
  • SRAM static RAM
  • DRAM dynamic RAM
  • FRAM ferroelectric RAM
  • EEPROM electrically erasable programmable ROM
  • CD-ROM compact disc-read only memory
  • HDD hard disk drive
  • flash drive such as magnetic disk storage or other magnetic storage devices
  • SSD solid-state drive
  • memory 204 may be embodied by any computer-readable medium, such as a non-transitory computer-readable medium.
  • Processor 202, memory 204, and transceiver 206 may be implemented in various forms in node 200 for performing wireless communication functions.
  • processor 202, memory 204, and transceiver 206 of node 200 may be implemented (e.g., integrated) on one or more system-on-chips (SoCs).
  • SoCs system-on-chips
  • processor 202 and memory 204 may be integrated on an application processor (AP) SoC (sometimes known as a “host,” referred to herein as a “host chip”) that manages application processing in an operating system (OS) environment, including generating raw data to be transmitted.
  • API SoC application processor
  • OS operating system
  • processor 202 and memory 204 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 run a real-time operating system (RTOS).
  • BP baseband processor
  • RTOS real-time operating system
  • processor 202 and transceiver 206 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 208.
  • 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 may implement the methods of cell detection, according to some embodiments of the present disclosure, in the baseband chip of the node.
  • the present disclosure enables a receiver (e.g., UE 102) to take advantage of the side information including, but not limited to, the history information to facilitate the cell search.
  • the receiver may only need to search a limited set of candidate cells to identify a correct cell so as to accelerate the system acquisition, thereby improving the user experience.
  • FIG. 3 illustrates a block diagram of an apparatus 300 according to some embodiments of the present disclosure.
  • Apparatus 300 may be an example of any suitable node of wireless network 100 in FIG. 1, such as UE 102 or access node 104.
  • apparatus 300 may include a baseband chip 302, an RF chip 304, a host chip 306, and one or more antennas 310.
  • baseband chip 302 may be implemented by processor 202 and memory 204
  • RF chip 304 may be implemented by processor 202, memory 204, and transceiver 206, as described above with respect to FIG. 2.
  • apparatus 300 may further include an external memory 308 (e.g., the system memory or main memory) that can be shared by each chip 302, 304, or 306 through the system/main bus.
  • external memory 308 e.g., the system memory or main memory
  • baseband chip 302 is illustrated as a standalone SoC in FIG.
  • baseband chip 302 and RF chip 304 may be integrated as one SoC; in another example, baseband chip 302 and host chip 306 may be integrated as one SoC; in still another example, baseband chip 302, RF chip 304, and host chip 306 may be integrated as one SoC, as described above.
  • host chip 306 may generate raw data and send it to baseband chip 302 for encoding, modulation, and mapping.
  • Baseband chip 302 may also access the raw data generated by host chip 306 and stored in external memory 308, for example, using direct memory access (DMA).
  • DMA direct memory access
  • Baseband chip 302 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 multiphase shift keying (MPSK) modulation or quadrature amplitude modulation (QAM).
  • MPSK multiphase shift keying
  • QAM quadrature amplitude modulation
  • Baseband chip 302 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 302 may send the modulated signal to RF chip 304.
  • RF chip 304 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 310 e.g., an antenna array
  • antenna 310 may receive RF signals and pass the RF signals to the receiver RX of RF chip 304.
  • RF chip 304 may perform any suitable front-end RF functions, such as filtering, direct current (DC) offset compensation, IQ imbalance compensation, downconversion, or sample-rate conversion, and convert the RF signals into low-frequency digital signals (baseband signals) that can be processed by baseband chip 302.
  • baseband chip 302 may demodulate and decode the baseband signals to extract raw data that can be processed by host chip 306.
  • Baseband chip 302 may perform additional functions, such as error checking, de-mapping, channel estimation, descrambling, etc.
  • the raw data provided by baseband chip 302 may be sent to host chip 306 directly or stored in external memory 308.
  • baseband chip 302 in FIG. 3 may implement the methods of cell detection using the history data and the synchronization signals including the PSS and the SSS.
  • Baseband chip 302 may include a cell detection unit 3022 that is configured to perform the cell detection according to some embodiments of the present disclosure. Consistent with the scope of the present disclosure, baseband chip 302 may also include a blind cell search unit 3024. In response that no cell, from the candidate cells, being detected at cell detection unit 3022, blind cell search unit 3024 of baseband chip 302 may start to perform a blind cell search.
  • baseband chip 302 may further include a local memory 3026 so as to avoid the communication overhead between baseband chip 302 and external memory 308.
  • blind cell search depending at least in part upon context, may be used to describe an exhaustive cell search on all of the possible PSS and SSS sequences.
  • history information and “history data” may be used interchangeably to describe the prior knowledge about the candidate cells that, e.g., were previously used or were used more frequently.
  • FIG. 3 illustrates cell detection unit 3022 and blind cell search unit 3024 as two standalone blocks in order to introduce their respective functions.
  • cell detection unit 3022 and blind cell search unit 3024 may be compatible with each other.
  • Each of cell detection unit 3022 and blind cell search unit 3024 can perform their intended function(s) under the existence of the other without any conflict.
  • Cell detection unit 3022 and blind cell search unit 3024 may include different modules to support their respective functions. In some embodiments, however, some elements (may include blocks, modules, components, circuits, steps, operations, processes, algorithms, and the like) in cell detection unit 3022 and blind cell search unit 3024 may be shared between these two units, such as those configured for the PSS detection.
  • FIG. 4 illustrates a block diagram of an SSB, according to some embodiments of the present disclosure.
  • SSB 400 in downlink may include one or more PSS symbols 402, one or more SSS symbols 404, and one or more PBCH symbols 406.
  • the binary phase shift keying (BPSK) modulation with m sequence is used to generate each PSS symbol 402 of length 127 in the frequency domain, while the BPSK modulation is used with gold sequence to generate each SSS symbol 404 of length 127 in the frequency domain.
  • the one or more PSS symbols 402 span over 127 active subcarriers, and the one or more SSS symbols 404 is also mapped to 127 subcarriers.
  • the one or more PSS symbols 402 and the one or more SSS symbols 404 can work together to realize the downlink synchronization.
  • the one or more PSS symbols 402 and the one or more SSS symbols 404 together can be used to indicate a total of 1008 different physicallayer cell identifies (PCIs.)
  • PCIs physicallayer cell identifies
  • the SSS symbols may be surrounded by the PBCH symbols.
  • OFDM orthogonal frequency division multiplexing
  • multiple SSBs are transmitted periodically (at 20ms intervals) in different beams each as a synchronization signal (SS) burst, and the PSS and SSS within each SSB are transmitted periodically to provide cell-specific timing information.
  • Each of the one or more PSS symbols 402 consists of three PSS sequences.
  • Each of the PSS sequences is orthogonal to any of the other two PSS sequences either in the time domain or the frequency domain. The orthogonality of the PSS can help the SSB find the symbol timing and perform the coarse FO.
  • a 5GNR synchronization raster indicates the frequency positions of the SSB that can be used by the UE.
  • the LTE communication systems in which “synchronization signal block” is termed instead of “SSB” may still apply the PSS and SSS in the reference signals to perform the cell detection according to some embodiments of the present disclosure.
  • FIG. 5 illustrates a block diagram of an expanded view of a portion of the baseband chip of FIG. 3, according to some embodiments of the present disclosure.
  • baseband chip 302 may include cell detection unit 3022 configured to perform a cell detection based on one or more candidate cells.
  • cell detection unit 3022 may include a plurality of functional blocks or modules that are configured to perform the cell search. These function blocks may be implemented using electronic hardware, firmware, computer software, or any combination thereof. Whether such elements are implemented as hardware, firmware, or software depends upon the particular application and design constraints imposed on the overall system.
  • FIG. 5 merely expends a portion of baseband chip 302 and shows cell detection unit 3022, according to some embodiments of the present disclosure.
  • baseband chip 302 may include one or more other functional blocks configured for other baseband operations, such as filtering, demodulation, decoding, up-conversion, and/or down-conversi on .
  • one or more modules of cell detection unit 3022 may be implemented as an integrated circuit (IC) dedicated to performing the functions disclosed herein, such as an ASIC.
  • one or more modules of cell detection unit 3022 may also be implemented as software modules executed by a processor to perform respective functions.
  • at least part of cell detection unit 3022 may be implemented by processor 202 and memory 204, as shown in FIG. 2.
  • Processor 202 may be a hardware device having one or more processing cores, or the processor may execute software stored in memory on the hardware device to control the hardware device, depending upon the particular application and design constraints imposed on the overall system.
  • baseband chip 302 may include a baseband processor (BP) executing instructions stored in memory, e.g., local memory 3026, to perform the disclosed methods.
  • the baseband processor may be a generic processor, such as a central processing unit or a DSP, not dedicated to the cell search. That is, the baseband processor may also be responsible for any other functions of baseband chip 302 and can be interrupted during the cell detection being performed due to another process with higher priority.
  • cell detection unit 3022 may include, e.g., a PSS processing module 502 configured for the PSS processing, an SSS processing module 504 configured for the SSS processing, and a PBCH processing module 508 configured for the PBCH processing.
  • cell detection unit 3022 may further include a SSS score checking module 506.
  • SSS score checking module 506 is shown as a standalone module separated from SSS processing module 504 and PBCH processing module 508, in some embodiments, SSS score checking module 506 may be integrated with, e.g., SSS processing module 504 or PBCH processing module 508, to which the present disclosure does not place limitation.
  • FIG. 6 illustrates a flow diagram of an exemplary method 600 of a cell detection, according to some embodiments of the present disclosure. With reference to FIGs. 5 and 6, certain embodiments of the present disclosure are disclosed below.
  • a UE may have possessed prior knowledge or history data about one or more candidate cells that, e.g., were previously used or most used.
  • the history information may include different frequencies and cell IDs of the one or more candidate cells.
  • the history data may be acquired according to the side information associated with, e.g., an event, a time duration, a location, or a history activity. The history data may be considered so as to avoid an exhaustive search on all the cells over different frequencies.
  • the history data may be stored in, e.g., local memory 3026 upon each use and can be retrieved in advance of the cell detection.
  • the most probable cells may be further selected from the one or more candidate cells for the cell detection. Still consistent with the scope of the present disclosure, depending on the system capability, multiple candidates can be processed either sequentially or in parallel to identify the correct cell.
  • PSS processing module 502 may receive data including, e.g., samples and history data.
  • samples herein may be used to describe time-domain raw sampling data of the synchronization signals in the downlink.
  • the samples may include the PSS samples, the SSS samples, and the PBCH samples, as shown in FIG. 4.
  • the history data may include information about one or more candidate cells.
  • the history data may include different carrier frequencies and cell IDs in regard to the one or more candidate cells. A cell ID may be chosen, and a carrier frequency may be given from the history data.
  • the chosen cell ID and the given carrier frequency may be jointed to form a specific data format, such as (carrier frequency 1, cell ID 1), (carrier frequency 1, cell ID 2), or (carrier frequency 2, cell ID 3).
  • the history data of all the candidate cells may be integrated to form a candidate cell array for the cell detection, each array element corresponding to a cell ID.
  • an applied frequency (as associated with the received samples) and a given frequency under test (obtained from the history data) may have an offset.
  • the received samples may require a frequency shifting from the applied frequency to the given frequency prior to the PSS and SSS detections to align the data for accurate PSS and SSS detections.
  • the information regarding the given frequency and cell ID may enable the modulation of the received samples to the given carrier frequency. Consequently, at 602, modulated samples can be obtained.
  • the term “received samples” may refer to the raw samples as received while the term “modulated samples” may refer to the modulated samples whose frequencies align with the tested carrier frequency.
  • FIG. 7 illustrates a flow diagram of an exemplary method of the PSS processing in the cell detection, performed by PSS processing module 502, according to some embodiments of the present disclosure.
  • FIG. 7 may provide detailed operations in regard to the PSS processing.
  • a corresponding PSS reference may be determined at 702 based on the modulated samples.
  • the determined PSS reference may be a PSS sequence having no phase and timing distortion.
  • the terms “PSS reference” and “PSS reference sequence” may be used interchangeably to refer to the PSS sequence determined according to the given cell ID, the PSS reference may be applied as a reference in the subsequent processes.
  • the method may proceed to 704, where the modulated samples may be processed with respect to the PSS reference to obtain a symbol boundary that includes a PSS symbol boundary.
  • the symbol boundary e.g., a starting sample and an ending sample of an OFDM symbol
  • PSS processing module 502 may further process the extracted PSS samples to determine a frequency offset (FO) and a timing offset (TO) associated with the cell, including an estimation of a coarse FO and a fractional FO based on the coarse FO and a fractional time delay.
  • FO frequency offset
  • TO timing offset
  • PSS processing module 502 may perform a PSS correlation between the PSS reference and the modulated samples to determine the PSS symbol boundary at 704.
  • the PSS reference, and the modulated samples may be fed into respective Fast Fourier Transform (FFT) operators, and the correlation may be performed based on an FFT of the modulated samples and an FFT of the PSS reference.
  • FFT Fast Fourier Transform
  • the PSS reference may be originally defined in the frequency domain so that the FFT of the PSS reference may not be required. For that reason, the PSS reference in the frequency domain may be directly used for the correlation and can be repeatedly used other than being calculated each time when it is needed.
  • a PSS correlation score corresponding to each candidate cell may be calculated and stored in local memory 3026 to assist subsequent evaluation.
  • the coarse timing corresponding to a PSS correlation peak in the frequency domain, can be regarded as the PSS symbol boundary.
  • the PSS symbol boundary obtained here may include coarse PSS symbol timing for a coarse FO estimation.
  • the method may proceed to 706 in FIG. 7.
  • the PSS samples may be extracted, and the coarse FO can be estimated through evaluating various hypotheses of the frequency errors.
  • the estimation of the coarse FO can be performed in the time domain or frequency domain, to which the present disclosure does not limit.
  • a matched-filter estimation may be applied to estimate the coarse FO.
  • certain other approaches may also be applied to estimate the coarse FO, to which the present disclosure does not limit.
  • the coarse PSS symbol timing and the integer-bin-based FO may be acquired, where each bin may be associated with a pre-determined spacing within the given frequency.
  • the above FFT approach applies the property that an impact of the subcarrier spacing (SCS)-based frequency offset on time-domain samples is equivalent to an SCS-shifting of the FFT of the time-domain samples.
  • SCS subcarrier spacing
  • the coarse PSS reference-related timing i.e., the PSS symbol boundary
  • the coarse FO can be obtained.
  • these data may not be accurate so as to meet the requirement for estimation accuracy. Accordingly, the same PSS reference may be applied again to enhance the estimation.
  • the PSS samples may be calculated and compensated with the known coarse FO at 708.
  • the FO-compensated PSS samples can be further compensated with the fractional timing offset in the time domain at 712. Overall, the PSS samples may be compensated both over the time and frequency domains.
  • fractional may be used to represent that associated offsets are between -p and p sample period in a time domain at the PSS sampling rate and between -q and q SCS in a frequency domain for SCS of the PSS, where p and q are numbers between 0 and 1. Therefore, the term “fractional” offsets may be given. In some examples, the fractional offset may be between -U and U sample period in the time domain at the PSS sampling rate, and between -U and Yi SCS in the frequency domain for SCS of the PSS.
  • one or more samples right ahead of or after the determined PSS symbol boundary can be added into the PSS samples for enhancing the coarse FO compensation. Consequently, the added samples can provide more flexibility/robustness to validate the estimated timing and thus enhance the FO estimation and compensation.
  • FIG. 8 illustrates a block diagram of an expanded view of a portion of PSS processing module 502 of FIG. 5, according to some embodiments of the present disclosure. Operations of the PSS processing will be described with reference to FIGs. 7 and 8.
  • the method may proceed to 708 in FIG. 7, where the estimated PSS samples may be compensated, in the time domain, with currently estimated coarse FO to obtain FO-compensated PSS samples.
  • the term “currently” estimated coarse FO may be used to describe a coarse FO that is estimated under the current PSS processing, corresponding to one candidate cell.
  • x has only the fractional timing offset Tj and the fractional frequency offset fj to be estimated and compensated in the given frequency or the currently evaluated carrier frequency.
  • the term “currently evaluated carrier frequency” is used to refer to the given frequency that is the currently tested frequency selected from the history data.
  • x may be received as input and compensated with the current coarse FO to generate an FO- compensated output , through functional block 802 as shown in FIG. 8.
  • the FO-compensated PSS samples ⁇ may be correlated with 2 m oversampled time-domain PSS banks (or termed “2 m filter banks”) to determine timing information for the FO- compensated PSS samples y, where m is a positive integer.
  • the timing information may include the fractional time delay corresponding to the candidate cell.
  • the 2 m filter banks may be configured to establish timing relations between timing offsets and sampling periods of the PSS reference based on the 2 m TO hypotheses. Based on the 2 m filter banks, to align with the PSS reference for the modulated samples, timing offsets can be estimated.
  • the coarse FO-compensated PSS samples y may be correlated with the 2 m oversampled time-domain PSS banks to find PSS timing for , e.g., through functional block 804, as shown in FIG. 8, based on 2 n FO hypotheses.
  • functional block 804 may process the correlation between y (the FO-compensated PSS samples) and the 2 m oversampled time-domain PSS banks to obtain the fine timing associated with the PSS samples.
  • the terms “fractional time delay,” “fractional timing offset,” “fine timing,” and “timing offset” may be used to describe the timing information obtained according to the FO-compensated PSS samples and may be used interchangeably.
  • the 2 m oversampled time-domain PSS banks may be prepared and stored in, e.g., local memory 3026 as shown in FIG. 3, in advance of the cell detection.
  • the 2 m oversampled time-domain PSS banks may be online calculated. For example, a PSS reference sequence in the frequency domain at IX PSS sampling rate may be appended by zeros with a size of (2 m -1) x Z, where L is a length of the PSS sequence in the time domain.
  • PSS appended The PSS reference sequence with the appended zeros may be denoted as “PSS appended.”
  • An inverse Fast Fourier Transform (IFFT) of the PSS appended may be taken at a size of 2 m x Z, and a time-domain output may be denoted as “PSS TD over sampled.”
  • the 2 m time-domain PSS banks where each of the time-domain PSS banks may have a length of Z (corresponding to timing offsets at the grid of l/2 m PSS sampling period after properly normalization with respect to ni) may be obtained from the PSS_TD_oversampled(0 : 2"'- l , 0 : Z-l ) by decimation at a factor of 2 m .
  • the two-dimensional PSS_TD_oversampled(0 : 2"'- l , 0 : Z-l) may represent 2"' PSS banks in the first dimension, ranging from index 0 to index 2 m -l, and the second dimension (0 : Z-l) in the PSS_TD_oversampled(0 : 2"'- l , 0 : L-l ) may represent that each PSS bank may have L PSS samples in the time-domain, ranging from index 0 to index L-l.
  • the FO-compensated PSS samples y may be correlated with the 2"' oversampled time-domain PSS banks to determine the timing information for the FO-compensated PSS samples y.
  • each of the 2"' PSS banks having L samples may be correlated with the FO-compensated PSS samples y, and the best result of the correlation may be obtained to determine the timing information associated with the samples y.
  • the PSS correlation is monotonically decreasing as the timing offset increases. Therefore, to determine the fractional timing offset, a binary search with the 2 m filter banks may be employed, and the correlation may be performed over the PSS samples compensated with the FO, other than traversing all 2 m filter banks. Through this manner and/or with other efficient search methods, the workload can be significantly reduced if m is relatively large.
  • the maximum FFT size is 4096
  • the result can assure the timing accuracy of up to 1/64 sampling period for the NR online processing.
  • the method may proceed to 712 in FIG. 7, where a time-domain interpolation may be applied toy (the coarse FO-compensated PSS samples) according to the fractional time delay.
  • the time-domain interpolation may be applied to y based on the fractional time delay further to obtain z, where z is an output sequence having both the FO and TO compensation.
  • z, compensated in the time and frequency domains may be used to estimate an updated coarse FO.
  • the time-domain interpolation may be performed through functional block 806 as shown in FIG. 8, where based on the fine timing, the coarse FO-compensated PSS samples, y, may be compensated in the time domain to generate z.
  • a fractional delay filter may be employed for compensating the timing offset in order to obtain sequence z.
  • Such a filter ideally, requires free of drooping for the PSS signals and for the same fractional delay, has a constant phase delay over a PSS signal band. This requirement cannot be met generally with the fractional delay filter design unless the PSS signals are oversampled; otherwise, the fractional delay filter may introduce additional droop distortion to the PSS samples when the timing offset is compensated.
  • the PSS occupies only a narrow band in the frequency domain, the performance of the cell detection will not be significantly impacted by a slight drooping.
  • only a finite number of fixed fractional delay filters with a constant delay of a l/2 m sampling period may be needed for the timing compensation instead of a complicated variable fractional delay filter.
  • PSS sequences have good localization. More specifically, any PSS sequence is orthogonal to the other two PSS sequences without a timing error, and a PSS sequence is nearly orthogonal to its own timing-shifting version before a timing offset becomes relatively larger in the unit of integer sampling periods. In other words, PSS sequences have satisfactory properties of both cross-correlation and auto-correlation, the features of which are widely used in synchronization, estimation, and detection.
  • timing offset when the timing offset is large, the cross-correlation value becomes larger than the auto-correlation value for the PSS detection. This means, in the presence of large timing offset close to 1 period at the PSS sampling rate, the filter banks with the PSS sequences cannot yield a correct detection result. This situation occurs even in the absence of other impacts, such as interference, noise, channel impairment, etc. Therefore, to assure the autocorrelation has enough gain over the cross-correlation for the PSS detection, a timing offset may need to be relatively small.
  • the timing offset may be no more than ⁇ 0.25 period at IX PSS sampling rate to assure the auto-correlation-based detection performance can have 12dB gain over cross-correlation performance between two different PSS sampling sequences, which can reduce a false alarm rate for the PSS detection.
  • the PSS sequences also have good localization.
  • the PSS sequences are orthogonal to each other without inter-carrier-interference (ICI), and any PSS sequence is orthogonal to its own frequency-shifting version if the frequency offset is at a multiple of the SCS.
  • ICI inter-carrier-interference
  • the PSS auto-correlation performance degrades with an increase of the frequency offset.
  • the ICI degrades the auto-correlation performance. Therefore, by having a smaller FO, a false alarm rate for detecting an incorrect PSS sequence can be reduced.
  • the other approach is to use a sophisticated approach, such as an MRC -based ML estimator, to estimate the fractional frequency offsets.
  • a sophisticated approach such as an MRC -based ML estimator
  • the approach may be performed in the time domain, it may not be required to consider the ICI as compared with the estimations performed over the frequency domain.
  • This approach can relatively accurately estimate the fine frequency offset within the subcarrier spacing (SCS) defined by the orthogonal PSS sequence, and hence it can work with a comparatively larger frequency offset (up to /i SCS).
  • SCS subcarrier spacing
  • the frequency offset bin size is not required to be exceedingly small, so the processing time by sweeping the multiple frequency offset hypotheses will be significantly decreased. This can translate the processing time to shorter time demanded for establishing a link to cells and improve user experience.
  • the method may proceed to 714, wherein another coarse FO may be estimated with the latest TO-compensated PSS sample in the current iteration.
  • the coarse FO may be updated with the latest TO-compensated PSS sample in one iteration, and based on the updated coarse FO, it can be determined whether a next iteration for forwarding back the processes is necessary at 716 and 178.
  • the method may proceed to 716 in FIG. 7, where the variation of the fraction time delay and variation of the fractional FO may be checked to determine whether these offsets are small enough to presume that the obtained PSS ID may be correct.
  • the samples z can be obtained. Based on the z sequence, in view of the variation of the time-domain offset and the frequency-domain offset with respect to the PSS reference, it can be determined whether the z sequence is associated with the PSS ID corresponding to the PSS reference.
  • the timing offset may need to be small. Further, by having a smaller frequency offset, a false alarm rate for an incorrect PSS can be reduced.
  • the variations of the fractional FO and TO may reflect whether the PSS correlation results between the PSS samples (e.g., z) and the PSS reference are satisfactory. Therefore, by comparing the variation of the fractional FO and the variation of the fractional time delay with respective thresholds, tl and Z2, it can be determined whether the PSS ID is correct. If the correct PSS ID is obtained, the PSS processing can be terminated, and the fractional timing offset Tj and the fractional frequency offset fj stored in, e.g., local memory 3026, may be forwarded for the SSS processing.
  • the fractional timing offset Tj and the fractional frequency offset fj may be updated.
  • the z sequence may be fed back to the PSS processing and be treated as a new input for another iteration. In the iteration, z may be compensated again with the current coarse FO.
  • the iterations may not be required.
  • the fractional FO and the fractional TO may not be updated.
  • the information about the coarse FO and an optimal fractional timing offset may be forwarded for the subsequent SSS processing.
  • the error ranges of the PSS-based TO and FO may need to meet certain requirements for performing the SSS detection.
  • some ideal conditions for evaluating the SSS correlation with respect to the TO and FO may provide a baseline of the minimum requirement of the TO and FO for the SSS detection.
  • FIG. 9 illustrates a flow diagram of an exemplary method of the SSS processing of the cell detection, according to some embodiments of the present disclosure. With reference to FIG. 9, operations of the SSS processing are described.
  • the method may proceed to 902, where the SSS samples may be compensated with the FO, either based on the coarse FO or the fractional FO.
  • the SSS samples can be correctly identified.
  • the obtained SSS samples may be compensated with the coarse FO.
  • the SSS samples can be compensated with either the coarse FO or the fractional FO, depending on application requirements for performance and accuracy.
  • a fractional delay filter may be applied in a time-domain interpolation for a timing adjustment based on the fractional timing offset Tj, and thus the FO-compensated SSS samples may be compensated with the TO. Consequently, the FO-compensated and TO- compensated SSS samples may be generated before running the correlation with a cell ID-related correlator based on the SSS reference at 906.
  • SSS processing module 504 in FIG. 5 may be configured to perform FFT operations on the SSS reference and the FO-compensated and TO-compensated SSS samples to obtain an FFT of the SSS reference and an FFT of the FO-compensated and TO- compensated SSS samples.
  • the SSS correlation may be performed based on the FFT of the SSS reference and the FFT of the FO-compensated and TO- compensated SSS samples, thereby taking advantages of the FFT to reduce the calculation and implementation complexity.
  • the SSS reference may be originally defined in the frequency domain so that the FFT of the SSS reference may not be required. For that reason, the SSS reference in the frequency domain may be directly used for the correlation and can be reused when needed.
  • the SSS correlation may be performed without the timing compensation to SSS samples, and step 904 in FIG. 9 can be skipped.
  • the FO- compensated SSS samples may not need to be compensated with the fractional timing offset r 7 .
  • a correlation between the FO-compensated SSS samples obtained at 902 and a fractional timing-shifted SSS reference can be performed.
  • the fractional timing-shifted SSS reference may be obtained by applying timing compensation to the SSS reference with the fractional timing offset tj-
  • outputs of the PSS processing and the SSS processing may be stored in, e.g., local memory 3026.
  • Output data may include the PSS symbol timing, the timing offset, and the frequency offset.
  • a log array in local memory 3026 may be configured to store the output data corresponding to the candidate cell.
  • the method may proceed to 908, an SSS correlation score corresponding to the candidate cell may be calculated.
  • all the SSS correlation scores may be stored in a log array, each array element of the log array corresponding to each candidate cell and carrier frequency as well as the associated symbol boundary, TO and FO.
  • the candidate cell array for the cell detection, for storing the history data may be used as or merged with the log array.
  • the method may proceed to 608.
  • the SSS correlation score corresponding to one candidate cell may be compared with a pre-determined threshold, t3.
  • SSS score checking module 506 in cell detection unit 3022 may be configured to perform the comparison of the SSS correlation score with the threshold t3.
  • SSS score checking module 506 is depicted as a standalone module, in other embodiments, it may be integrated with other modules in cell detection unit 3022 to simplify the implementation.
  • the SSS detection will be regarded as a successful SSS detection, and at 610, the SSS correlation core will be stored in the log array with the output data (such as the PSS symbol timing, the timing offset, and the frequency offset) corresponding to the detected cell having the tested carrier frequency. If the SSS correlation score is less than or equal to the threshold G, upon confirming that there are one or more untested candidate cells at 612, the process may go back to 602. At 602 again, another candidate cell will be evaluated with the PSS processing, the SSS processing, and other procedures of the method.
  • the method may proceed to 616, where a blind cell search is performed. That is, the previous PSS processing and SSS processing for all the candidate cells do not successfully determine a qualified cell from the one or more candidate cells.
  • the SSS detection will be regarded as a successful SSS detection, and at 610, the SSS correlation core will be stored in the log array with the output data (such as the PSS symbol timing, the timing offset, and the frequency offset) corresponding to the detected cell having the tested carrier frequency. If the SSS correlation score is less than or equal to the threshold G, upon confirming that there are one or more untested candidate cells at 612, the process may go back to 602. At 602 again, another candidate cell will be evaluated with the PSS processing, the SSS processing, and other procedures of the method.
  • the method may proceed to 616, where a blind cell search is performed subsequently. That is, the previous PSS processing and SSS processing for all the candidate cells do not successfully determine a qualified cell from the one or more candidate cells.
  • all the SSS correlation scores may be stored in the log array, each array element of the log array corresponding to each candidate cell (and the associated information about carrier frequency, timing/frequency offset). Therefore, in some embodiments at 614, in response to all the candidate cells being evaluated at 612, it can be further determined based on the log array to see whether at least one cell of all the tested candidate cells was previously qualified and is ready for the next step.
  • blind cell search may be used to describe an exhaustive cell search on all of the possible PSS and SSS sequences over all the possible carrier frequencies. That is, for example, all 1008 cells for the 5 GNR. network or 504 cells for the 4G LTE network.
  • Blind cell search unit 3024 shown in FIG. 3 may be configured to perform the blind cell search.
  • blind cell search may also refer to cell searches based on certain potential carrier frequencies and cell IDs.
  • the log array that stores the previous SSS correlation scores may be searched to determine whether there is at least one qualified cell. If all the candidate cells are evaluated (Yes at 618 or Yes at 612), and at least one SSS correlation score is greater than the threshold G, the method may proceed to 620, where the SSS correlation scores of the one or more qualified cells that have the SSS correlation scores greater than the threshold t3 may be sorted. In some embodiments, the SSS correlation scores may be sorted according to values of the SSS correlation scores. For example, the SSS correlation scores may be sorted according to a descending order of the values of the SSS correlation scores. At 622, one or more optimal cells may be selected from the sorting result of the one or more qualified cells.
  • the PBCH processing (e.g., the PBCH detection and decoding) may be performed according to the one or more optimal cells.
  • PBCH processing module 508 shown in FIG. 8 may be configured to perform the PBCH processing.
  • the PSS and SSS are physical signals with specific structures, while the PBCH is a physical channel that carries system information for the UE requiring to access the network.
  • the PBCH is configured to carry the master information block (MIB), and the MIB contains information that the UE requires to enable the acquisition of the remaining system information broadcast by the network.
  • MIB master information block
  • a cyclic redundancy check passes in the PBCH decoding, the overall cell detection may be regarded as successful acquisition, and the overall processes may be terminated. Otherwise, if no valid cell candidates are detected over the selected frequencies, frequencies within a broad range, instead of the limited set of the candidate cells, may be scanned, and the blind cell search may be performed.
  • the SSS correlation scores it can be determined which cells may be considered for the PBCH processing.
  • certain scenarios may occur. For example, if the SSS correlation scores are all different, the qualified cells corresponding to higher SSS correlation scores may be selected.
  • a selection rule may be established. For example, the selection may be random or based on a priority of FO and TO estimated.
  • both the SSS and PSS correlation scores may be considered for evaluating the one or more candidate cells.
  • the PSS sequence has better auto-correlation property as compared to the SSS sequence, and the SSS sequence is uniquely defined by the cell ID but multiple cells share the same PSS sequence, a smaller weight may be given to the PSS correlation score and a larger weight may be given to the associated SSS correlation score to obtain a weighted sum of the SSS and PSS correlation scores for the sorting.
  • one cell to be detected may be a “ghost cell,” which means the detected cell ID is not a valid ID.
  • a result may show an invalid FO that is larger than usual or than expected.
  • sorting the valid cells with the combination of the PSS and SSS correlation results may be beneficial in order to reduce the cell detection missing rates.
  • there may be one or more cells with a higher probability to be detected. Without scanning all of the possible frequencies and the cell IDs, the present disclosure accelerates the acquisition dramatically and improves the user experience. With the proper estimation and compensation of the timing and frequency offsets, a weak signal can be correctly detected at higher probability, and thus the false alarm rates can be substantially reduced.
  • a UE can achieve a better sensitivity level and reduce the network acquisition time and complexity, thus improving the user experience. Furthermore, the time-diversity combination (highly influenced by accurate estimation and compensation for the sample clock frequency offset, the estimation/compensation for the potential channel variation, and their associated effects) can be accordingly avoided.
  • the apparatus may include a processor and memory storing instructions that, when executed by the processor, may cause the processor to determine a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell.
  • PSS primary synchronization signal
  • SSS secondary synchronization signal
  • a PSS processing for the candidate cell may be performed based on the PSS reference and samples to estimate a frequency offset (FO). The samples may be collected in a time domain.
  • An SSS processing for the candidate cell may be performed based on the FO, the samples, and the SSS reference to obtain an SSS correlation score of the candidate cell.
  • the candidate cell may be added to one or more qualified cells, and a physical broadcast channel (PBCH) processing may be performed based on the one or more qualified cells.
  • PBCH physical broadcast channel
  • the candidate cell may be a first candidate cell
  • the PSS reference may be a first PSS reference
  • the SSS correlation score may be a first SSS correlation score
  • the FO may be a first FO.
  • the instructions may further cause the processor to determine a second PSS reference based on a cell identity (ID) and a carrier frequency associated with a second candidate cell.
  • a second FO may be estimated based on the second PSS reference and the samples.
  • An SSS processing for the second candidate cell may be performed to obtain a second SSS correlation score of the second candidate cell based on the second FO.
  • the second candidate cell may be added to the one or more qualified cells.
  • the instructions may further cause the processor to correlate the samples with the PSS reference to determine a symbol boundary.
  • the samples may include a frequency aligned with the carrier frequency.
  • PSS samples may be obtained based on the symbol boundary and the samples.
  • a coarse FO may be estimated based on the PSS samples and the PSS reference.
  • the FO may include the coarse FO.
  • the instructions may further cause the processor to compensate the PSS samples with the coarse FO to obtain FO-compensated PSS samples.
  • a fractional time delay may be determined based on the FO-compensated PSS samples.
  • the SSS processing for the candidate cell may be performed based on the fractional time delay, the coarse FO, the samples, and the SSS reference to obtain the SSS correlation score of the candidate cell.
  • the instructions may further cause the processor to correlate the FO-compensated PSS samples with filter banks to determine the fractional time delay for the candidate cell.
  • the filter banks may be configured to store relations between timing offsets and sampling periods associated with the PSS reference.
  • the instructions further cause the processor to determine SSS samples based on the symbol boundary.
  • the SSS processing for the candidate cell may be performed based on the coarse FO, the SSS samples, the SSS reference, and the fractional time delay to obtain the SSS correlation score of the candidate cell.
  • the instructions may further cause the processor to compensate the SSS samples with the coarse FO to obtain FO-compensated SSS samples.
  • a timedomain interpolation to the FO-compensated SSS samples may be performed with the fractional time delay to obtain FO-compensated and TO-compensated SSS samples.
  • the FO-compensated and TO-compensated SSS samples may be correlated with the SSS reference to obtain the SSS correlation score for the candidate cell.
  • the threshold may be a first threshold.
  • the instructions may further cause the processor to, in response to a variation of the fractional time delay for the candidate cell being less than a second threshold, the PSS processing for the candidate cell may be terminated, and the SSS processing for the candidate cell may start to perform based on the fractional time delay, the coarse FO, the samples, and the SSS reference to obtain the SSS correlation score of the candidate cell.
  • the instructions may further cause the processor to perform a time-domain interpolation to the FO-compensated PSS samples to obtain an FO-compensated and timing offset (TO)-compensated PSS samples.
  • TO timing offset
  • the instructions may further cause the processor to, in response to the variation of the fractional time delay for the candidate cell being greater than or equal to the second threshold, compensation to the FO-compensated and TO-compensated PSS samples may be performed with the coarse FO to obtain updated PSS samples.
  • An updated fractional time delay may be determined based on the updated PSS samples.
  • the candidate cell may be a first candidate cell
  • the SSS correlation score may be a first SSS correlation score.
  • the instructions may further cause the processor to perform an SSS processing for a second candidate cell to obtain a second SSS correlation score based on a carrier frequency and a cell ID associated with the second candidate cell.
  • the second candidate cell may be added to the one or more qualified cells, and one or more optimal cells may be selected from the one or more qualified cells.
  • the PBCH processing may be performed based on the one or more optimal cells.
  • a candidate cell array may include one or more candidate cells.
  • the instructions may further cause the processor to perform an SSS processing for each of the one or more candidate cells to obtain SSS correlation scores corresponding to the one or more candidate cells.
  • a blind cell search may be performed.
  • the instructions may further cause the processor to sort the SSS correlation scores based on values of the SSS correlation scores to obtain a sorting result.
  • One or more optimal cells may be selected based on the sorting result.
  • the PBCH processing may be performed based on the one or more optimal cells.
  • a Fast Fourier Transform (FFT) of the samples may be obtained.
  • the samples may include a frequency aligned with the carrier frequency.
  • the PSS reference in a frequency domain may be obtained.
  • the FFT of the samples and the PSS reference in the frequency domain may be correlated to determine a symbol boundary.
  • the method may include determining a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell.
  • a PSS processing for the candidate cell may be performed based on the PSS reference and samples to estimate a frequency offset (FO). The samples may include a frequency aligned with the carrier frequency.
  • An SSS processing for the candidate cell may be performed based on the FO, the samples, and the SSS reference to obtain an SSS correlation score of the candidate cell.
  • the candidate cell may be added to one or more qualified cells, and a physical broadcast channel (PBCH) processing may be performed based on the one or more qualified cells.
  • PBCH physical broadcast channel
  • performing the PSS processing may include correlating the samples with the PSS reference to determine a symbol boundary.
  • the samples may include a frequency aligned with the carrier frequency.
  • PSS samples may be obtained based on the symbol boundary and the samples.
  • a coarse FO may be estimated based on the PSS samples and the PSS reference.
  • the FO may include the coarse FO.
  • the PSS samples may be compensated with the coarse FO to obtain FO-compensated PSS samples.
  • a fractional time delay may be determined based on the FO-compensated PSS samples.
  • performing the SSS processing for the candidate cell may include compensating SSS samples with the coarse FO to obtain FO-compensated SSS samples, the SSS samples may be obtained based on the symbol boundary and the samples.
  • a time-domain interpolation to the FO-compensated SSS samples may be performed with the fractional time delay to obtain FO-compensated and TO-compensated SSS samples.
  • the FO-compensated and TO- compensated SSS samples may be correlated with the SSS reference to obtain the SSS correlation score of the candidate cell.
  • the candidate cell may be a first candidate cell
  • the SSS correlation score may be a first SSS correlation score.
  • the method may further include performing an SSS processing for a second candidate cell to obtain a second SSS correlation score based on a carrier frequency and a cell ID associated with the second candidate cell.
  • the second candidate cell may be added to the one or more qualified cells, and one or more optimal cells may be selected from the one or more qualified cells.
  • the PBCH processing may be performed based on the one or more optimal cells.
  • a candidate cell array may include one or more candidate cells.
  • the method further may include performing an SSS processing for each of the one or more candidate cells to obtain SSS correlation scores corresponding to the one or more candidate cells.
  • a blind cell search may be performed.
  • the apparatus may include a processor and memory storing instructions that, when executed by the processor, cause the processor to determine a primary synchronization signal (PSS) reference and a secondary synchronization signal (SSS) reference based on a cell identity (ID) and a carrier frequency associated with a candidate cell. PSS samples and SSS samples may be extracted from samples based on the PSS reference.
  • PSS primary synchronization signal
  • SSS secondary synchronization signal
  • the samples may be collected in a time domain and may include a frequency aligned with the carrier frequency.
  • the PSS samples may be compensated based on the PSS reference to obtain compensated PSS samples
  • the SSS samples may be compensated based on the SSS reference to obtain compensated SSS samples.
  • Cell detection results, corresponding to the candidate cell may be determined based on the compensated PSS samples, the compensated SSS samples, the PSS reference, and the SSS reference.
  • a PBCH processing may be performed based on the candidate cell.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Certains modes de réalisation concernent des appareils et des procédés de détection de cellule. L'appareil comprend un processeur configuré pour déterminer une référence de signal de synchronisation primaire (PSS) et une référence de signal de synchronisation secondaire (SSS) sur la base d'une identité (ID) de cellule et d'une fréquence porteuse associée à une cellule candidate. Un traitement PSS pour la cellule candidate est effectué sur la base de la référence PSS et d'échantillons afin d'estimer un décalage de fréquence (TO). Un traitement SSS pour la cellule candidate est effectué sur la base du TO, des échantillons, et de la référence SSS afin d'obtenir un score de corrélation SSS de la cellule candidate. En réponse au fait que le score de corrélation SSS de la cellule candidate est supérieur à un seuil, la cellule candidate est ajoutée à une ou plusieurs cellules qualifiées, et un traitement de canal de diffusion physique (PBCH) est effectué sur la base de la ou des cellules qualifiées.
PCT/US2022/024871 2022-04-14 2022-04-14 Appareil et procédé de détection de cellule Ceased WO2023200445A1 (fr)

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