Cell search method and device, chip, equipment, and storage medium

Abstract

The embodiment of the present application discloses a cell search method and apparatus, a chip, a device, and a storage medium; wherein the method comprises: performing a first correlation detection on a first received sequence to obtain at least one first starting position of a first synchronization sequence and a cell group identifier corresponding to the first starting position; expanding the first synchronization sequence to obtain at least one second starting position according to the first starting position; wherein the correlation peak value corresponding to the at least one second starting position satisfies a first condition; performing a second correlation detection on each of the first starting position and each of the second starting position to obtain a cell group identifier

Description

Technical Field

[0001] The embodiments of the present application relate to communication technology, and are related to but not limited to a cell search method and apparatus, a chip, a device, and a storage medium. Background Art

[0002] Compared with the Long Term Evolution (LTE) system, the 5th-Generation wireless communication technology (5G) New Radio (NR) system has developed new protocol standards and introduced a variety of key technologies. The 5G system with large bandwidth, large connections, low latency and high reliability will support the implementation of industries such as artificial intelligence, big data, and the Internet of Things, and build an intelligent world where everything is connected. Cell search is a key link in the downlink baseband signal processing of the 5G system, and its search accuracy affects the communication performance of the user equipment (UE). Summary of the invention

[0003] In view of this, the cell search method and apparatus, chip, device, and storage medium provided in the embodiments of the present application can improve the accuracy of cell search, thereby improving communication performance. The cell search method and apparatus, chip, device, and storage medium provided in the embodiments of the present application are implemented as follows:

[0004] The cell search method provided in the embodiment of the present application includes: performing a first correlation detection on a first received sequence to obtain at least one first starting position of a first synchronization sequence and an intra-cell identifier corresponding to the first starting position According to the first starting position, at least one second starting position of the first synchronization sequence is obtained by expansion; wherein the correlation peak corresponding to the at least one second starting position satisfies the first condition; and a second correlation detection is performed according to each of the first starting position and each of the second starting position to obtain a cell group identifier.

[0005] The cell search device provided in the embodiment of the present application includes: a first detection module, which is used to perform a first correlation detection on a first received sequence, and obtain at least one first starting position of a first synchronization sequence and a cell group identifier corresponding to the first starting position. an expansion module, configured to expand the first synchronization sequence according to the first starting position to obtain at least one second starting position; wherein the correlation peak corresponding to the at least one second starting position satisfies the first condition; and a second detection module, configured to perform a second correlation detection according to each of the first starting position and each of the second starting position to obtain a cell group identifier

[0006] The baseband chip provided in the embodiment of the present application includes: a correlation detection circuit, which is used to perform a first correlation detection on a first received sequence, and obtain at least one first starting position of a first synchronization sequence and an intra-cell group identifier corresponding to the first starting position. a processor, configured to obtain, based on the first starting position, at least one second starting position of the first synchronization sequence by expansion; wherein the correlation peak value corresponding to the at least one second starting position satisfies a first condition; and, performing a second correlation detection based on each of the first starting position and each of the second starting position to obtain a cell group identifier

[0007] The user equipment provided in the embodiment of the present application includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, the method described in the embodiment of the present application is implemented.

[0008] The computer-readable storage medium provided in the embodiment of the present application stores a computer program thereon, and when the computer program is executed by a processor, the method provided in the embodiment of the present application is implemented.

[0009] In the embodiment of the present application, a first correlation detection is performed on the first received sequence to obtain at least one first starting position of the first synchronization sequence and its corresponding cell group identifier. At this time, the second correlation detection is not performed only based on the first starting position, but the second starting position whose correlation peak meets the first condition is obtained by expanding the first starting position, so that the second correlation detection is performed based on each first starting position and each second starting position to obtain the cell group identifier. In this way, on the one hand, the accuracy of the cell search can be improved; on the other hand, under the premise of ensuring the accuracy of the cell search, it also provides conditions for using a smaller oversampling factor. That is to say, under the premise of ensuring the accuracy of the cell search by increasing the second starting position, a smaller oversampling factor (for example, an oversampling factor of 1) can be used to obtain the first received sequence, thereby greatly reducing the amount of calculation of the first correlation detection, thereby shortening the overall time of the cell search and improving the overall efficiency of the cell search. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and are used together with the specification to illustrate the technical solution of the present application.

[0011] Figure 1 A network architecture that may be applicable to the embodiments of the present application is shown;

[0012] Figure 2 The basic process of cell search is shown;

[0013] Figure 3 A schematic diagram of the implementation flow of the cell search method provided in the embodiment of the present application;

[0014] Figure 4 This is a schematic diagram of the implementation process of the cell search method in the embodiment of the present application;

[0015] Figure 5 This is a schematic diagram of the implementation process of the cell search method in the embodiment of the present application;

[0016] Figure 6 Indicates the Global Synchronization Channel Number (GSCN) included in the 4096 Fast Fourier Transform (FFT) points;

[0017] Figure 7 The relevant processing flow of a set of data in an embodiment of the present application is shown;

[0018] Figure 8 The operation process of the secondary synchronization signal (SSS) of an embodiment of the present application is shown;

[0019] Fig. 9 The conditions for extending the PssOut candidate value in the embodiment of the present application are shown;

[0020] Fig.10 This is a schematic diagram of the structure of a cell search device according to an embodiment of the present application;

[0021] Fig.11 This is a schematic diagram of the structure of the baseband chip in the embodiment of the present application;

[0022] Fig.12 A schematic diagram of the structure of a user device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the specific technical solution of the present application will be further described in detail below in conjunction with the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application, but are not used to limit the scope of the present application.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0025] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0026] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present application do not represent a specific ordering of objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.

[0027] The network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. It is known to those skilled in the art that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0028] Figure 1 A network architecture that may be applicable to the embodiments of the present application is shown. Figure 1 As shown, the network architecture provided in this embodiment includes: network device 101 and user equipment (UE) 102. The user equipment involved in the embodiment of the present application may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, as well as various forms of user terminal devices (terminal devices) or mobile stations (Mobile Stations, MS), etc. The network device involved in the embodiment of the present application is a device deployed in a wireless access network to provide wireless communication functions for user equipment. In the embodiment of the present application, the network device can be, for example, Figure 1 The base station shown may include various forms of macro base stations, micro base stations, relay stations or access points, etc.

[0029] The cell search method of the embodiment of the present application can be applied to the fourth generation mobile communication system (4G), 5G NR system or future communication system, and can also be used in various other wireless communication systems.

[0030] Taking the 5G NR system as an example, Figure 2 The basic process of cell search is shown in FIG. Figure 2 As shown, first, symbol synchronization and intra-cell group identification are completed through PSS correlation detection (i.e., an example of the first correlation detection). Detection and frequency offset estimation; then, through SSS correlation detection (ie, an example of the second correlation detection), the cell group identifier is obtained Thus, according to the cell group identifier and the corresponding cell group identifier Determine the cell ID

[0031] For cell identification The determination method is not limited in the embodiments of the present application, and the determination methods corresponding to different communication systems may be different.

[0032] Taking the 5G system as an example, The cell ID can be calculated according to the following formula (1):

[0033]

[0034] Among them, the cell group identifier

[0035] It should be noted that this is just an example of a cell identification. Method for determining the cell group identifier and cell group identifier The specific number and quantity are not limited in the embodiments of the present application. With the evolution of network architecture and the emergence of new business scenarios, the cell group identifier and cell group identifier The numbers and quantities may change accordingly, but for similar technical problems, the technical solutions provided in the embodiments of the present application are also applicable.

[0036] The cell search method provided in the embodiment of the present application can be applied to user equipment. Figure 3 A schematic diagram of the implementation flow of the cell search method provided in the embodiment of the present application is shown in FIG. Figure 3 As shown, the method may include the following steps 301 to 303:

[0037] Step 301: Perform a first correlation detection on a first received sequence to obtain at least one first starting position of a first synchronization sequence and an intra-cell identifier corresponding to the first starting position.

[0038] The first received sequence used for the first correlation detection is usually a plurality of groups of sequences with a specific length. In some embodiments, step 301 can be implemented by steps 501 to 506 of the following embodiments. The first synchronization sequence can be various types of synchronization sequences. For different wireless communication systems, the types of the first synchronization sequences may be different, but the functions are usually similar. It is mainly used for cell search to obtain the cell group identifier. In the 5G NR system and in the LTE system, the first synchronization sequence is the primary synchronous signal (PSS).

[0039] It is understandable that different cell group identifiers The local sequence corresponding to the different first synchronization sequence, and the local sequence of the first synchronization sequence is used to perform a correlation operation with the first receiving sequence, and the user equipment can determine the first starting position of the first synchronization sequence based on the correlation result obtained by the correlation operation. Therefore, the cell group identifier corresponding to the first starting position Refers to the cell group identifier corresponding to the local sequence used to obtain the first synchronization sequence of the starting position

[0040] Step 302: Expand and obtain at least one second starting position of the first synchronization sequence according to the first starting position; wherein the correlation peak value corresponding to the at least one second starting position satisfies a first condition.

[0041] In the embodiments of the present application, the expansion method can be various, aiming to expand the second starting position where the correlation peak satisfies the first condition. For example, in some embodiments, a correlation peak equal to or second only to the correlation peak of the first starting position is searched from the correlation results used to obtain the first starting position, and the symbol positions corresponding to these or this correlation peaks are determined as the second starting position. For example, in some embodiments, the user equipment can also directly determine at least one symbol position that is an extension step away from the first starting position as the second starting position; wherein, the method for determining the extension step is as described in step 507 of the following embodiment.

[0042] In some embodiments, the first condition is less than or equal to the correlation peak value corresponding to the first starting position; thus, a more accurate cell group identifier can be obtained by performing a second correlation detection based on more starting positions. Thereby improving the accuracy of cell search.

[0043] Step 303: Perform a second correlation detection based on each of the first starting positions and each of the second starting positions to obtain a cell group identifier.

[0044] In the embodiment of the present application, a first correlation detection is performed on the first received sequence to obtain at least one first starting position of the first synchronization sequence and its corresponding cell group identifier. At this time, the second correlation detection is not performed only based on the first starting position, but the second starting position whose correlation peak meets the first condition is obtained by expanding the first starting position, so that the second correlation detection is performed based on each first starting position and each second starting position to obtain the cell group identifier. In this way, on the one hand, the accuracy of cell search can be improved; on the other hand, under the premise of ensuring the accuracy of cell search, it also provides conditions for using a smaller oversampling factor, that is, under the premise of ensuring the accuracy of cell search by increasing the second starting position, a smaller oversampling factor (for example, an oversampling factor of 1) can be used to obtain the first received sequence, thereby greatly reducing the amount of calculation of the first correlation detection, thereby shortening the overall time of the cell search, and improving the overall efficiency of the cell search.

[0045] The present application embodiment further provides a cell search method, Figure 4 Schematic diagram of the implementation process of the cell search method of the embodiment of the present application, such as Figure 4 As shown, the method includes steps 401 to 406:

[0046] Step 401: Perform a first correlation detection on a first received sequence to obtain at least one first starting position of a first synchronization sequence and an intra-cell identifier corresponding to the first starting position.

[0047] Step 402, obtaining an oversampling factor of a local sequence of a first synchronization sequence;

[0048] Step 403 , determining whether the oversampling factor is less than or equal to a specific value; if so, executing step 404 ; otherwise, executing step 406 .

[0049] In the embodiment of the present application, the specific value can be any value and is not limited to this. For example, the specific value is 1. The amount of calculation of the first correlation detection in the scenario where the oversampling factor is equal to 2 is much greater than the amount of calculation of the first correlation detection in the scenario where the oversampling factor is equal to 1. Therefore, when the oversampling factor is less than or equal to the specific value, the accuracy of the second correlation detection can be improved by executing steps 404 and 405, thereby improving the cell search performance. From another perspective, in the second correlation detection stage, the second starting position is added, so that while ensuring the cell search performance, it provides favorable conditions for using a smaller oversampling factor. Using a smaller oversampling factor can greatly reduce the amount of calculation in the first correlation detection stage, thereby improving the overall efficiency of the cell search.

[0050] Step 404: Expand to obtain at least one second starting position of the first synchronization sequence according to the first starting position; wherein, the relevant peaks corresponding to the at least one second starting position satisfy the first condition.

[0051] Step 405: Perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain the cell group identifier.

[0052] Step 406: Perform a second correlation detection according to each of the first starting positions to obtain the cell group identifier.

[0053] It can be understood that if the oversampling factor is greater than a specific value, there is no need to increase the second starting position, and the second correlation detection can be directly performed according to the first starting position. Although the cell search implemented through Step 401 and Step 406 based on a larger oversampling factor and the cell search implemented through Step 401, Step 404, and Step 405 based on a smaller oversampling factor can both meet the requirements in terms of the accuracy of cell search, the computational complexity of the former is much greater than that of the latter, that is, the overall time of the cell search of the former is much longer than that of the latter.

[0054] In some embodiments, both Step 405 and Step 406 can be implemented as follows: Extract a second synchronization sequence from the corresponding first received sequence according to the l-th starting position and the length of the first synchronization sequence; where 0 < l ≤ L, and L is the total number of the first starting position and the second starting position, that is, the total number of the starting positions; For each cell group identifier Perform a correlation operation between the local sequence of the corresponding second synchronization sequence and the second synchronization sequence to obtain the corresponding second correlation result; Determine the cell group identifier according to the second correlation result corresponding to each starting position.

[0055] For different wireless communication systems, the definition of the second synchronization sequence may be different, but the functions are basically the same. Its main function is to perform cell search to obtain the cell group identifier. For example, in the 5G NR system and in the LTE system, the second synchronization sequence is the Secondary Synchronization Signal (SSS).

[0056] Understandably, the processing efficiency of the second correlation detection is much higher than that of the first correlation detection. The reasons are as follows: First, the object processed by the second correlation detection is the second synchronization sequence, while the object processed by the first correlation detection is the first received sequence to which the second synchronization sequence belongs. Since the second synchronization sequence intercepts part of the data of the first received sequence, the computational amount of the second correlation detection is much smaller than that of the first correlation detection; Second, in practical applications, the first correlation detection is mainly implemented by hardware, while the second correlation detection is mainly implemented by software, and the computational efficiency of the latter is higher than that of the former; Third, compared with the first correlation detection algorithm, the second correlation detection algorithm has lower complexity.

[0057] For the above three reasons, the time complexity of the second correlation detection is much smaller than that of the first correlation detection. Therefore, even if the second starting position is increased in the second correlation detection stage, the time consumed is very small compared with the computational time saved by reducing the oversampling factor in the first correlation detection stage. That is to say, when the oversampling factor is equal to a specific value (such as the specific value is equal to 1) or less than a specific value (such as the specific value is equal to 3), by increasing the second starting position, not only can the search performance meet the requirements, but also the cell search time can be greatly saved, thereby effectively improving the cell search efficiency. In short, by the method of increasing the second starting position in the second correlation detection stage, without sacrificing the search performance, a smaller oversampling factor can be allowed, thereby greatly reducing the computational amount of the first correlation detection, and further improving the overall efficiency of cell search.

[0058] Another embodiment of the present application provides a cell search method. Figure 5 It is a schematic flowchart of the implementation process of the cell search method of the embodiment of the present application, as Figure 5 shown, the method includes steps 501 to step 509:

[0059] Step 501, perform a Fast Fourier Transform (FFT) on the i-th group of first received sequences to obtain a second received sequence; where 0 < i ≤ I, and I is the total number of the first received sequences;

[0060] Step 502, perform a correlation operation on the second received sequence according to the local sequence of the first synchronization sequence corresponding to the k-th cell group identifier and the j-th frequency offset hypothesis to obtain a second correlation result; where 0 < k ≤ K, K is the total number of cell group identifiers and 0 < j ≤ J, J is the total number of frequency offset hypotheses;

[0061] Step 503, intercept the second correlation result according to the intercept length to obtain a second correlation sub-result.

[0062] It is understandable that the intercept length is related to the hardware processing capability of the inverse fast Fourier transformer, and the intercept length is less than or equal to the maximum number of points that the inverse fast Fourier transformer can process. The maximum number of points that the inverse fast Fourier transformer can process is known, and accordingly, the intercept length is also known. For example, the intercept length is equal to the maximum number of points.

[0063] Step 504, performing an inverse fast Fourier transform (IFFT) on the second correlation sub-result to obtain a first correlation sub-result;

[0064] Step 505, concatenating each first related sub-result corresponding to the second related result into a first related result;

[0065] Step 506: Determine at least one first starting position of the first synchronization sequence and an intra-cell identifier corresponding to the first starting position according to the obtained I×K×J group of the first correlation results.

[0066] It should be noted that the execution of steps 507 to 509 may be conditional or unconditional. The so-called conditional means, for example, that when the oversampling factor is less than or equal to a specific value, steps 507 to 509 are executed; otherwise, a second correlation detection is performed according to each of the first starting positions to determine the cell group identifier. The so-called unconditional means that after executing step 506 , the user equipment directly executes steps 507 to 509 .

[0067] Step 507, determining a ratio of the length of the first received sequence where the first starting position is located to the intercepted length;

[0068] Step 508: Use the ratio as an extension step length, and determine at least one symbol position that is at least 1 times the extension step length away from the first starting position as a second starting position.

[0069] In the embodiment of the present application, there is no limitation on how many symbol positions are taken as the second starting position, nor is there any limitation on the direction of the symbol position of the first starting position as the second starting position, nor is there any limitation on how many times the expansion step length is taken as the second starting position. For example, two symbol positions to the left and right of the first starting position with an expansion step length of 1 times, and / or two symbol positions to the left and right of the first starting position with an expansion step length of 2 times, etc. can be taken as the second starting position.

[0070] It can be understood that compared to searching for the correlation peak that meets the first condition from the first correlation result and then determining the symbol position corresponding to the correlation peak, in step 508, the second starting position can be expanded directly according to the extension step size and the first starting position; in this way, the expansion complexity can be reduced, thereby saving calculation amount, thereby shortening the overall search time of the cell search and improving the cell search efficiency.

[0071] Step 509: Perform a second correlation detection based on each of the first starting positions and each of the second starting positions to obtain a cell group identifier.

[0072] The following describes an exemplary application of the embodiments of the present application in a practical application scenario.

[0073] In the embodiments of the present application, it is intended to provide a solution for efficiently completing a cell search in the initial stage of a cell search.

[0074] When the UE fails to search for a specified frequency, cell, or alternate frequency or cell, or when such information does not exist, the UE performs a full-band scan to search for all cells within the frequency band supported by the UE capability.

[0075] In the NR system, due to the increase in bandwidth, the 100Hz grid previously used in the LTE system cannot be directly applied in the NR system. Therefore, the concept of synchronization grid is proposed to effectively reduce the UE calculation complexity. Here, the step size of the synchronization grid is no longer 100KHz, but a longer frequency interval. Different parameter sets (numerology) correspond to synchronization grids of different step sizes. For example: the subcarrier spacing (SCS) is 15KHz, and the corresponding synchronization grid compensation is 1.2MHz. In addition, for different frequency bands, there are different numbers of GSCNs on each synchronization grid, which may be 3 GSCNs or 1 GSCN. For most bands, there are usually 3 GSCNs on each synchronization grid. For other bands, there is usually 1 GSCN on each synchronization grid.

[0076] The purpose of cell search is to find the most likely GSCN. When the UE uses the GSCN found in the cell search phase to search for a cell at a given frequency, it can find the cell ID information with the greatest probability and even successfully complete the subsequent reading of the Main Information Block (MIB). It can be seen that cell search is a very critical step. If the search fails to find a suitable GSCN, it will directly affect the cell search time and performance.

[0077] For different purposes, the UE may use different crystal oscillators. Then, the selection of different crystal oscillators will cause different frequency deviations before the UE synchronizes with the network, and this deviation may be in a typical range of 1 to 20 ppm. In the embodiment of the present application, the influence of different crystal oscillator schemes and the cell search scheme affected by the aging of the crystal oscillator over time are considered, and the frequency domain search is effectively completed while taking into account the performance.

[0078] In the initial stage of cell search, the goal is to search for valid frequencies as quickly as possible. This solution includes as many GSCNs as possible in a high sampling rate manner on a given UE's radio frequency resources.

[0079] When the received high sampling rate time domain data is available, the frequency domain transform data of the high sampling rate time domain data is obtained by using FFT, and then the frequency domain correlation is completed respectively according to the possible different GSCN points and considering the influence of different frequency offsets, and then converted to the time domain through IFFT to complete the PSS correlation detection.

[0080] If the PSS correlation result of the corresponding center frequency exceeds the first threshold, the SSS correlation detection is performed using the relevant information to directly obtain the cell-level information, and the process can be terminated; wherein the cell-level information, for example, includes at least one of the following: PID, frequency deviation, time domain position of the synchronization signal, and GSCN;

[0081] If the PSS correlation result of the corresponding center frequency point does not exceed the first threshold, the maximum PSS correlation value corresponding to the center frequency point is reported.

[0082] After all center frequency points are scanned, the maximum PSS correlation values ​​reported by the center frequency points can be sorted to find the most likely GSCN and complete the cell search.

[0083] Specifically, the following steps 1 to 4 are included, the purpose of which is to include as many GSCNs as possible while ensuring relevant performance:

[0084] Step 1: When the received high-sampling rate time domain data is available, the frequency domain transform data of these high-sampling data is obtained by using FFT, and then the frequency domain correlation is completed separately according to the possible different GSCN points and considering the influence of different frequency offsets. Then, it is converted to the time domain through IFFT to complete the PSS correlation detection.

[0085] Among them, PSS related detection needs to consider two factors: sampling rate and determination of GSCN point, among which:

[0086] Regarding the sampling rate, in order to save the complexity of correlation calculation, the UE's PSS correlation detection uses the following characteristics: (1) The FFT method is used to complete the linear correlation operation between a long sequence and a local short sequence. (2) The FFT characteristic is used: the integer multiple (subcarrier) frequency deviation in the time domain is equivalent to a circular shift in the frequency domain. The effect of the frequency deviation on the PSS correlation determines the size of the subcarrier spacing, and the size of the FFT determines the sampling rate of the input data.

[0087] The determination of GSCN points depends on two factors, such as FFT capability and the choice of crystal oscillator, because it is necessary to include as many GSCN points as possible while ensuring the relevant detection performance; among them:

[0088] For the FFT that the UE can provide: a high sampling rate means a large channel bandwidth, which is equivalent to more GSCN points according to the distribution of GSCN points in NR mentioned above. Then, more tasks will be completed in one search cycle (NR cell search cycle is 20ms). Considering the currently available FFT capabilities, the total number of GSCN points that the UE can process in one search cycle will be limited.

[0089] Regarding frequency deviation: Another factor is related to the current crystal oscillator solution. For PSS-based cell search, in order to ensure the accuracy of cell search, the total number of frequency deviation assumptions will be determined by combining the minimum frequency assumption that meets performance requirements with the ppm of different crystal oscillators. The increase in the number of frequency deviation assumptions means an increase in calculation complexity, which will also affect the determination of GSCN.

[0090] Based on the above considerations, the computational complexity analysis of PSS correlation detection is given below, and the parameter list is shown in Table 1:

[0091] Table 1

[0092]

[0093] The amount of FFT and IFFT calculations required to complete a set of correlations is as follows:

[0094] IFFT:(2*Ceil(F*p / x)+1)*(GSCN_num*3)+FFT:1Formula (2);

[0095] Among them, 2 means considering the direction of frequency deviation; Ceil is a function of rounding up; GSCN_num means the number of GSCN; 3 means 3 GSCNs for each synchronization grid, and the FFT points generally choose a large FFT, such as 4096. FFT: 1 means from 4096, 4095, 4094 to 1. The choice of IFFT points depends on x; for NR system: PSS_N_baseIFFT = 128; N_IFFT = PSS_N_baseIFFT*ovsampleRate / (x / scs)

[0096] In addition, assuming that the overlap factor is: o; where the overlap factor refers to the ratio of the overlapped part when the correlation is calculated by the FFT method, then the total number of groups that complete the correlation in a 20 ms period is expressed as follows:

[0097] G=sampleNum / N / (1-o) formula (3);

[0098] Based on the above formulas (2) and (3), the final calculation complexity is calculated as shown in formula (4):

[0099] C=[sampleNum / N / (1-o)]*[IFFT:(2*ceiling(F*p / x)+1)*(GSCN_num*3)+FFT:1]Formula (4);

[0100] Let C = C1 + C2, then:

[0101] C1=[sampleNum / N / (1-o)], the number of FFT operations;

[0102] C2 = [sampleNum / N / (1-o)]*[(2*ceiling(F*p / x)+1)*(GSCN_num*3)], the number of IFFT operations.

[0103] The selection of sampling frequency and FFT points needs to be based on the evaluation of the above computational effort.

[0104] In some scenarios, the value of the parameter ovsampleRate is 1. In this case, the amount of computation for PSS-related detection is significantly reduced compared to when ovsampleRate=2.

[0105] Taking the NR system as an example, ssb scs = 15KHz, F = 3GHz, p = 15ppm, x = 3.75Khz, ceiling (F*p / x) = 12, GSCN_num = 1:

[0106] When the ovsampleRate value is 1, PSS_N = 4096, x = 3.75Khz, PSS_N_IFFT = 512, o = 0.25, sampleNum = 307200; accordingly,

[0107] The computational complexity of PSS correlation detection is:

[0108] C1 =

[100] , FFT num;

[0109] C2=

[100] *[(2*12+1)*(1*3)], IFFT num;

[0110] The total amount of computation for PSS correlation detection is: c1*PSS_N+c2*PSS_N_IFFT=4249600mips;

[0111] When the ovsampleRate value is 2, PSS_N = 4096, x = 3.75Khz, PSS_N_IFFT = 1024, o = 0.125; accordingly,

[0112] The computational complexity of PSS correlation detection is:

[0113] C1 =

[100] , FFT num (i.e., the number of FFT operations);

[0114] C2 =

[100] * [(2 * 12 + 1) * (1 * 3)], IFFT num (i.e., the number of IFFT operations);

[0115] The total amount of computation for PSS correlation detection is: c1*PSS_N+c2*PSS_N_IFFT=8089600mips;

[0116] It is obvious that the amount of computation when ovsampleRate=2 is much greater than that when ovsampleRate=1.

[0117] After determining the parameters, such as Figure 6 As shown, it indicates the GSCN points included in the 4096 FFT (for example, 3GSCN / synchronous grid), and the frequency domain points of the received oversampled data corresponding to a single GSCN point (for example, the middle GSCN of Group 3).

[0118] After obtaining the data of the frequency domain points, it is necessary to complete the IFFT and overlap operations to obtain the time domain related data, wherein each GSCN point completes the IFFT and overlap operations respectively, thus completing the operation of a group. Afterwards, the same operation is completed in the total number of groups G (in a 20ms period) mentioned above, and all the time domain related values ​​of each GSCN point in the 20ms period will be obtained. Then, the correlation values ​​are sorted, and the peak values ​​greater than the first threshold are selected as candidate values, and enter the subsequent SSS correlation detection. If the value is less than the first threshold, proceed to step 4.

[0119] like Figure 7 As shown, it shows the correlation processing flow for a group of data, assuming that the length of the sampled data (i.e., the first received sequence) is 4096, the sequence is subjected to FFT processing to obtain the first frequency domain data, and then, according to different frequency offset assumptions, the first frequency domain data is cyclically shifted to obtain the second frequency domain data; the local sequence 1 of PSS, the local sequence 2 of PSS, and the local sequence 3 of PSS are respectively correlated with the second frequency domain data, and the obtained correlation operation results are subjected to nIFFT to obtain the third correlation result; then, on the other hand, the second frequency domain data is subjected to nIFFT to obtain the second time domain data; the energy value of the second time domain data is calculated; and the third correlation result is normalized using the energy value to obtain the fourth correlation result (i.e., an example of the first correlation result).

[0120] Step 2: If the PSS correlation result of the corresponding center frequency exceeds the first threshold, proceed to step 3; if the PSS correlation result does not exceed the first threshold, output the maximum PSS correlation result corresponding to the center frequency, and after all center frequencies are completed, proceed to step 4;

[0121] The related cell search technology only performs PSS processing and generally selects the information corresponding to the largest PSS correlation peak (such as frequency, wait).

[0122] In the embodiment of the present application, the PSS related values ​​are divided into the following two cases:

[0123] One is that if the PSS correlation value of the corresponding center frequency point is greater than the first threshold, the information corresponding to the correlation value (including frequency deviation, position, and numlogy, etc.) directly perform SSS correlation detection with the received data. If a cell can be detected, the cell-level information can be directly obtained.

[0124] One is that none of the PSS correlation values ​​of the corresponding center frequency point is greater than the first threshold, then the information of the maximum PSS correlation value corresponding to the center frequency point is output.

[0125] Step 3: Use the information obtained from PSS correlation to directly perform SSS correlation detection to obtain cell-level information (such as PID, frequency offset and time domain position of synchronization signal). If cell-level information cannot be obtained, the information of the maximum PSS correlation value corresponding to the center frequency point is output.

[0126] According to step 2, there will be multiple candidate values ​​in the PSS correlation value that are greater than the first threshold value. For each PSS candidate value, SSS correlation detection can be performed, and finally the SSS correlation values ​​corresponding to all PSS candidate values ​​will be obtained; then, the SSS correlation values ​​are sorted, and if there is an SSS correlation value greater than the first threshold value, the corresponding cell-level information is output. If a cell is found in some processing flow, the flow ends automatically.

[0127] If the cell-level information cannot be obtained, the information of the maximum value of the PSS corresponding to the central frequency point is output.

[0128] The SSS related detection process corresponding to each PSS candidate value is as follows: Figure 8 As shown (taking the NR system as an example), the following steps 801 to 806 are included:

[0129] Among them, the following information is obtained according to the PSS candidate value: initial sampling rate f s _ini, the frequency deviation information △f carried by the current candidate value, the number of SSS time-frequency conversion FFT points N_sssFFT, and the starting position startPos of the SSS data corresponding to the PSS candidate value; here △f is a unitless quantity, indicating the number of times the SCS interval.

[0130] Step 801, data extraction: time domain SSS data can be extracted according to startPos and N_sssFFT;

[0131] Step 802, frequency offset correction: According to △f and f s _ini performs frequency offset correction (i.e. frequency offset compensation) on the data;

[0132] Step 803, FFT: performing FFT on the frequency offset corrected data;

[0133] Step 804, select effective subcarrier: select frequency domain SSS data;

[0134] Step 805, descrambling m0: descramble the frequency domain SSS data and remove the cell group identifier The impact of

[0135] Step 806: Cell group identification Related: Different cell group identifiers The corresponding sequences are correlated;

[0136] Understandably, the following conclusion is drawn in step 1: the amount of computation of PSS correlation detection when ovsampleRate=2 is much greater than that when ovsampleRate=1, but when ovsampleRate=1, the performance of step 2 is significantly reduced according to the above processing.

[0137] Based on this, in the embodiment of the present application, an improved SSS related detection processing flow is provided, which can use the parameter ovsampleRate=1 in step 1 and ensure that the cell search performance is not greatly reduced. Fig. 9 As shown, based on each PssOut candidate value (including at least the first starting position and the corresponding cell group identifier ) Before performing SSS related detection processing, the following steps 901 to 902 are performed:

[0138] Step 901, determine whether ovsampleRate is equal to 1; if yes, execute step 902; otherwise, end;

[0139] Step 902, expand the PssOut candidate value; wherein the PssOut candidate value includes at least the following information: the starting position of the SSS data corresponding to the PssOut candidate value: startPos.

[0140] In some embodiments, the expansion method is as follows: take at least one point on the left and right of startPos, with a step size of PSS_N / PSS_N_IFFT.

[0141] After this operation, each PSS candidate value will become at least three PSS candidate values, and the corresponding starting positions of the SSS data are startPos-PSS_N / N_IFFT, startPos, and startPos+PSS_N / N_IFFT respectively.

[0142] Step 4: After all center frequency points are scanned, the maximum PSS correlation values ​​reported by the center frequency points can be sorted to find the most likely GSCN and complete the cell search.

[0143] If no suitable cell-level information is found or further searching for a cell is performed, the maximum value of the PSS-related value reported by each central frequency point can help the UE further search for a cell.

[0144] In an embodiment of the present application, a method based on related cell search is provided. Through this method, the method solves the problem of how to effectively utilize the current UE resources while taking into account the search performance and the frequency deviation changes caused by different crystal oscillator schemes and aging, and also achieves the purpose of saving power consumption.

[0145] It can be understood that in the cell search stage, the PSS-related detection stage is allowed to output multiple candidate values ​​to the SSS-related detection module for processing; however, in the SSS-related detection stage, each PssOut candidate value is expanded to multiple candidate values. In this way, for the processing of ovsampleRate=1 in step 1, the system performance loss is not large, but the system's computational complexity can be halved.

[0146] The above method can not only be applied to the NR system, but can also be flexibly applied to the cell search phase of other wireless access technologies. It only needs to replace different synchronization signals. This is because the definition of synchronization channels is different in different wireless access technologies.

[0147] Based on the foregoing embodiments, an embodiment of the present application provides a cell search device, which includes the modules included and the units included in the modules, which can be implemented by a processor; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP) or a field programmable gate array (FPGA), etc.

[0148] Fig.10 Schematic diagram of the structure of the cell search device according to the embodiment of the present application. Fig.10 As shown, the cell search device 100 includes:

[0149] The first detection module 1001 is used to perform a first correlation detection on the first received sequence to obtain at least one first starting position of the first synchronization sequence and an intra-cell identifier corresponding to the first starting position.

[0150]

[0151] An expansion module 1002 is configured to expand the first synchronization sequence according to the first starting position to obtain at least one second starting position; wherein the correlation peak value corresponding to the at least one second starting position satisfies a first condition;

[0152] The second detection module 1003 is used to perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier

[0153] In some embodiments, the cell search device 100 further includes a control module, and the control module is configured to: obtain the oversampling factor of the local sequence of the first synchronization sequence; if the oversampling factor is less than or equal to a specific value, trigger the extension module 1002 to extend at least one second starting position of the first synchronization sequence according to the first starting position; if the oversampling factor is greater than the specific value, the division second detection module 1003 performs a second correlation detection according to each of the first starting positions to obtain the cell group identifier

[0154] In some embodiments, the specific value is 1.

[0155] In some embodiments, the first condition is less than or equal to the correlation peak corresponding to the correlation peak of the first starting position.

[0156] In some embodiments, the first detection module 1001 is configured to: perform a fast Fourier transform on the i-th group of the first received sequences to obtain a second received sequence; where 0 < i1 ≤ I, and I is the total number of the first received sequences; perform a correlation operation on the second received sequence according to the local sequence of the first synchronization sequence corresponding to the k-th cell group internal identifier and the j-th frequency offset hypothesis to obtain a second correlation result; where 0 < k ≤ K, K is the total number of cell group internal identifiers, 0 < j ≤ J, and J is the total number of frequency offset hypotheses; intercept the second correlation result according to the intercept length to obtain a second correlation sub-result; perform an inverse fast Fourier transform on the second correlation sub-result to obtain a first correlation sub-result; splice each first correlation sub-result corresponding to the second correlation result into a first correlation result; determine at least one first starting position of the first synchronization sequence and the cell group internal identifier corresponding to the first starting position according to the obtained I × K × J groups of the first correlation results corresponding to the local sequence of the first synchronization sequence and the j-th frequency offset hypothesis, perform a correlation operation on the second received sequence to obtain a second correlation result; where 0 < k ≤ K, K is the total number of cell group internal identifiers, 0 < j ≤ J, and J is the total number of frequency offset hypotheses of the total number, 0 < j ≤ J, J is the total number of frequency offset hypotheses; intercept the second correlation result according to the intercept length to obtain a second correlation sub-result; perform an inverse fast Fourier transform on the second correlation sub-result to obtain a first correlation sub-result; splice each first correlation sub-result corresponding to the second correlation result into a first correlation result; determine at least one first starting position of the first synchronization sequence and the cell group internal identifier corresponding to the first starting position according to the obtained I × K × J groups of the first correlation results

[0157] In some embodiments, the extension module 1002 is configured to: determine the ratio of the length of the first received sequence where the first starting position is located to the intercept length; use the ratio as the extension step size, and determine at least one symbol position that is the extension step size away from the first starting position as the second starting position.

[0158] In some embodiments, the second detection module 1003 is configured to: extract a second synchronization sequence from the corresponding first received sequence according to the l-th starting position and the length of the first synchronization sequence; where 0 < l ≤ L, and L is the total number of the first starting position and the second starting position; each cell group identifier The local sequence of the corresponding second synchronization sequence is respectively correlated with the second synchronization sequence to obtain a corresponding second correlation result; and the cell group identifier is determined according to the second correlation result corresponding to each of the starting positions.

[0159] The description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0160] It should be noted that the division of modules in the cell search device in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit. It may also be implemented in the form of a combination of software and hardware.

[0161] It should be noted that in the embodiment of the present application, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions to enable the user device to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0162] Accordingly, an embodiment of the present application provides a baseband chip. Fig.11 Schematic diagram of the structure of the baseband chip of the embodiment of the present application, such as Fig.11 As shown, the baseband chip 110 includes:

[0163] The correlation detection circuit 1101 is used to perform a first correlation detection on the first received sequence to obtain at least one first starting position of the first synchronization sequence and an intra-cell group identifier corresponding to the first starting position.

[0164]

[0165] The first processor 1102 is configured to obtain, by extension according to the first starting position, at least one second starting position of the first synchronization sequence; wherein a correlation peak value corresponding to the at least one second starting position satisfies a first condition;

[0166] The second processor 1103 is configured to perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier.

[0167] It should be noted that, in the embodiment of the present application, the first processor 1102 and the second processor 1103 may be the same processor or different processors.

[0168] The description of the above chip embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the chip embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0169] This embodiment of the application provides a user equipment, Fig.12 A schematic diagram of the hardware entity of the user equipment according to an embodiment of the present application is shown in FIG. Fig.12 As shown, the user equipment 120 includes a memory 121 and a processor 122, wherein the memory 121 stores a computer program that can be run on the processor 122, and the processor 122 implements the steps in the method provided in the above embodiment when executing the program.

[0170] It should be noted that the memory 121 is configured to store instructions and applications executable by the processor 122, and can also cache data to be processed or processed by various modules in the processor 122 and the user device 120 (for example, image data, audio data, voice communication data, and video communication data), which can be implemented through flash memory (FLASH) or random access memory (Random Access Memory, RAM).

[0171] An embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the method provided in the above embodiment are implemented.

[0172] An embodiment of the present application provides a computer program product including instructions, which, when executed on a computer, enables the computer to execute the steps of the method provided in the above method embodiment.

[0173] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium, storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0174] It should be understood that "one embodiment" or "an embodiment" or "some embodiments" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in one embodiment" or "in some embodiments" appearing throughout the specification may not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments. The above description of each embodiment tends to emphasize the differences between the various embodiments, and the same or similar aspects can be referenced to each other. For the sake of brevity, this article will not repeat them.

[0175] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, object A and / or object B can represent three situations: object A exists alone, object A and object B exist at the same time, and object B exists alone.

[0176] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0177] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as: multiple modules or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or modules can be electrical, mechanical or other forms.

[0178] The modules described above as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules; they may be located in one place or distributed on multiple network units; some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0179] In addition, all functional modules in the embodiments of the present application may be integrated into one processing unit, or each module may be a separate unit, or two or more modules may be integrated into one unit; the above-mentioned integrated modules may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0180] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, etc., various media that can store program codes.

[0181] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling the user device to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0182] The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0183] The features disclosed in several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0184] The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0185] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A cell search method, characterized in that: The method includes: Perform a first correlation detection on the first received sequence to obtain at least one first starting position of the first synchronization sequence and an intra-cell group identifier corresponding to the first starting position Expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence; wherein, the correlation peaks corresponding to the at least one second starting position satisfy a first condition; wherein, the first condition is less than or equal to the correlation peak corresponding to the first starting position; Perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier Wherein, the expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence includes: Determining a ratio of the length of the first received sequence where the first starting position is located to the intercepted length; Using the ratio as an expansion step size, and determining at least one symbol position that is at least 1 times the expansion step size away from the first starting position as the second starting position.

2. The method according to claim 1, characterized in that Before the expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence, the method further includes: Obtaining an oversampling factor of the local sequence of the first synchronization sequence; If the oversampling factor is less than or equal to a specific value, performing the step of expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence; If the oversampling factor is greater than the specific value, a second correlation detection is performed according to each of the first starting positions to obtain a cell group identifier.

3. The method according to claim 2, characterized in that The specific value is 1.

4. The method according to any one of claims 1 to 3, characterized in that: The first correlation detection is performed on the first received sequence to obtain at least one first starting position of the first synchronization sequence and an intra-cell group identifier corresponding to the first starting position. include: Performing a fast Fourier transform on the i-th group of the first received sequences to obtain a second received sequence; wherein, 0 < i1 ≤ I, and I is the total number of the first received sequences; According to the identifier within the k-th cell group perform a correlation operation on the second received sequence based on the local sequence of the first synchronization sequence corresponding thereto and the j-th frequency offset hypothesis, to obtain a second correlation result; where 0 < k ≤ K, K is the total number of identifiers within the cell group and 0 < j ≤ J, J is the total number of frequency offset hypotheses; Intercepting the second correlation result according to the intercepted length to obtain a second correlation sub-result; Performing an inverse fast Fourier transform on the second correlation sub-result to obtain a first correlation sub-result; Concatenating each first correlation sub-result corresponding to the second correlation result into a first correlation result; Determine at least one first starting position of the first synchronization sequence and an intra-cell identifier corresponding to the first starting position according to the obtained I×K×J groups of the first correlation results.

5. The method according to claim 1, characterized in that performing a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier include: Extracting a second synchronization sequence from the corresponding first received sequence according to the l-th starting position and the length of the first synchronization sequence; wherein, 0 < l ≤ L, and L is the total number of the first starting position and the second starting position; Each cell group is identified The local sequences of the corresponding second synchronization sequence are respectively correlated with the second synchronization sequence to obtain corresponding second correlation results; Determine the cell group identifier according to the second correlation result corresponding to each of the starting positions 6. A cell search device, characterized in that: Includes: A first detection module is configured to perform a first correlation detection on a first received sequence to obtain at least one first starting position of a first synchronization sequence and an intra-cell group identifier corresponding to the first starting position. An expansion module, configured to expand, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence; wherein, the correlation peaks corresponding to the at least one second starting position satisfy a first condition; wherein, the first condition is less than or equal to the correlation peak corresponding to the first starting position; A second detection module is used to perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier Wherein, the expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence includes: Determining a ratio of the length of the first received sequence where the first starting position is located to the intercepted length; Using the ratio as an expansion step size, and determining at least one symbol position that is at least 1 times the expansion step size away from the first starting position as the second starting position.

7. A baseband chip, characterized in that: Includes: A correlation detection circuit is used to perform a first correlation detection on the first received sequence to obtain at least one first starting position of the first synchronization sequence and an intra-cell group identifier corresponding to the first starting position. A first processor, configured to expand, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence; wherein, the correlation peaks corresponding to the at least one second starting position satisfy a first condition; wherein, the first condition is less than or equal to the correlation peak corresponding to the first starting position; a second processor, configured to perform a second correlation detection according to each of the first starting positions and each of the second starting positions to obtain a cell group identifier Wherein, the expanding, according to the first starting position, to obtain at least one second starting position of the first synchronization sequence includes: Determine a ratio of a length of a first received sequence where the first starting position is located to a truncated length; The ratio is used as an extension step length, and at least one symbol position that is at least 1 times the extension step length away from the first starting position is determined as the second starting position.

8. A user equipment, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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