A time-frequency offset estimation method and device for LTE system

Abstract

The application provides a time-frequency offset estimation method and device of an LTE system, and relates to the technical field of communication. The method comprises the following steps: a plurality of decimal multiple frequency offsets are used to compensate the initial received signal to obtain a first target signal; after PSS detection and screening of the first target signal, the first m first correlation peak values in descending order, N-ID-2 corresponding to the first correlation peak values, the first timing position and the first frequency offset value are obtained; a plurality of integer multiple frequency offsets are preset and the second correlation peak values corresponding to each first correlation peak value are calculated; the time domain position of each second correlation peak value is located and frequency offset compensation is performed to obtain a second target signal; after SSS detection and screening of the second target signal, the first n second correlation peak values in descending order, N-ID-1 corresponding to the second correlation peak values, the second timing position and the second frequency offset value are obtained, and the cell ID is obtained by combining N-ID-1 and N-ID-2. The application separates the decimal multiple frequency estimation and the integer multiple frequency offset estimation, and the double frequency offset estimation improves the accuracy.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a time-frequency offset estimation method and apparatus for an LTE system. Background Technology

[0002] In wireless cellular communication systems, cell search is the core process for establishing a communication link between User Equipment (UE) and the base station. Its core functions include: quickly locking onto the target cell during initial UE access or cell handover, achieving downlink time and frequency synchronization, and reading cell broadcast information, such as Physical Cell Identifier (PCI) and system bandwidth, enabling the UE to complete normal camping.

[0003] Long Term Evolution (LTE) systems employ a hierarchical cell search mechanism, using a primary synchronization signal (PSS) and a secondary synchronization signal (SSS) to achieve timing synchronization, frequency synchronization, and cell identifier detection in stages. During the initial access phase, LTE systems require large frequency offset estimation, typically supporting estimations of frequency offsets greater than several integer multiples, such as ±15kHz or ±30kHz, to reduce residual frequency offsets in subsequent service phases and ensure communication link stability.

[0004] However, existing cell search methods in LTE systems have significant drawbacks: when the initial frequency offset exceeds half a subcarrier interval (e.g., in LTE with a subcarrier interval of 15kHz, the initial frequency offset > 7.5kHz), the performance of existing frequency offset estimation algorithms deteriorates sharply. Specifically:

[0005] 1) Problem of related peak confusion.

[0006] Frequency offset estimation based on PSS relies on the sliding correlation properties of the ZC (Zadoff-Chu) sequence. For ease of explanation, let's take an example... Figure 1 As shown, Figure 1 The horizontal axis represents the sequence index, and the vertical axis represents the correlation power. Assuming the sequence length Nzc = 63, the root index u = 25, N_ID_2 = 0, and the sampling rate is 1.92MHz, and assuming that the received signal frequency offset is 0Hz under the additive white Gaussian noise (AWGN) channel, it can be seen that regardless of the preset frequency offset assumptions of -30kHz, -15kHz, 0kHz, 15kHz, or 30kHz, the corresponding power peak is very close to the power peak of the correct frequency offset, which makes it impossible to effectively distinguish the power peak of the correct frequency offset in practical applications.

[0007] 2) Channel fading exacerbates frequency offset misjudgment.

[0008] In multipath or time-varying channel environments, the correlation peak fluctuations of different frequency offset assumptions overlap, further increasing the probability of frequency offset estimation errors, resulting in a large difference between the estimated value and the true value.

[0009] In existing technologies, although attempts have been made to alleviate the aforementioned problems by optimizing ZC sequence design or introducing frequency offset compensation algorithms, the strong coupling between frequency offset and timing synchronization, as well as the insensitivity of ZC sequences to integer multiples of frequency offset, mean that these solutions still struggle to improve robustness in scenarios with large frequency offsets. Therefore, there is an urgent need for a time-frequency offset estimation method that can effectively distinguish between integer multiples of frequency offset assumptions and reduce the probability of correlation peak confusion, in order to improve UE access success rate and communication quality in complex channel environments. Summary of the Invention

[0010] To address the aforementioned technical problems, this application provides a time-frequency offset estimation method and apparatus for an LTE system. By separating fractional frequency offset estimation from integer frequency offset estimation, the dual frequency offset estimation improves the accuracy of frequency offset estimation. Simultaneously, it avoids the waste of computational resources caused by re-performing PSS detection for each integer frequency offset assumption. The technical solution is as follows:

[0011] Firstly, a time-frequency offset estimation method for an LTE system is provided, including:

[0012] The first target signal is obtained by using multiple preset fractional frequency offsets to compensate the initial received signal for fractional frequency offsets.

[0013] The first dataset of the master synchronization signal is obtained by performing PSS detection on the first target signal. The first dataset includes the first m first correlation peaks sorted in descending order, as well as N-ID-2, first timing position and first frequency offset value corresponding to each first correlation peak.

[0014] Based on m first frequency offset values ​​and a plurality of preset integer multiple frequency offsets, a second correlation peak value corresponding to each of the first correlation peak values ​​is calculated;

[0015] The time-domain position of each of the second relevant peaks is located and frequency offset compensation is performed to obtain the second target signal;

[0016] The second target signal is subjected to SSS detection and filtering to obtain the top n second correlation peaks in descending order, as well as N-ID-1, second timing position and second frequency offset value corresponding to each second correlation peak; wherein, N-ID-1 and N-ID-2 are combined to obtain the cell ID;

[0017] Output the cell ID, the second timing position, and the second frequency offset value.

[0018] In one possible implementation, the method for obtaining the second timing position corresponding to each of the second related peaks includes:

[0019] Calculate the timing offset caused by the integer multiple frequency offset based on the sequence length, root index, subcarrier spacing, and sampling rate;

[0020] Obtain a preset timing advance offset, which is used to compensate for the timing lag of the second related peak.

[0021] The second timing position is calculated based on the first timing position, the timing offset, and the timing advance offset.

[0022] In one possible implementation, the timing offset is calculated using the following formula:

[0023]

[0024] Where, n offset This represents the timing offset. mod(.) represents the modulo operation function, round(.) represents rounding, and u is the root index. N represents the integer multiples of the normalized frequency offset. FFT N represents the number of points in the Fast Fourier Transform. FFT The product of the product with the subcarrier spacing is equal to the sampling rate, N zc This indicates the length of the sequence.

[0025] In one possible implementation, the method further includes:

[0026] A data table is established based on the calculation formula for the timing offset, and the data table stores the timing offset corresponding to each integer multiple of frequency offset;

[0027] The timing offset corresponding to the integer multiple frequency offset is obtained by matching the data table.

[0028] In one possible implementation, the second timing position is calculated using the following formula:

[0029]

[0030] in, N represents the second timing position. pos Indicates the first timing position, n offset Indicates the timing offset, n ta This indicates the timing advance offset.

[0031] In one possible implementation, the method for obtaining the second frequency offset value corresponding to each of the second correlation peaks includes:

[0032] Obtain the integer and fractional octave frequency offsets corresponding to each of the second relevant peak values;

[0033] Calculate the sum of the integer and fractional octaves of the frequency offset corresponding to each of the second related peaks to obtain the second frequency offset value corresponding to the second related peak.

[0034] In one possible implementation, the range of the fractional octet frequency offset is: to Where Δf represents the subcarrier spacing.

[0035] In one possible implementation, within the range of the fractional octave offset values, each fractional octave offset is distributed according to a predetermined interval step size, wherein the predetermined interval step size is either a fixed interval step size or a non-fixed interval step size.

[0036] In one possible implementation, the method further includes:

[0037] Set a threshold for decision;

[0038] The threshold decision is used to filter the top m first relevant peaks in descending order; and / or

[0039] The threshold decision is used to filter the top n second-related peaks in descending order.

[0040] In a second aspect, a time-frequency offset estimation apparatus for an LTE system is provided. The apparatus includes a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform a time-frequency offset estimation method for an LTE system as described in any of the preceding claims.

[0041] The technical solutions provided in this application can achieve the following technical effects:

[0042] (1) By separating fractional frequency offset estimation from integer frequency offset estimation, specifically, multiple fractional frequency offsets are first used to compensate for the frequency offset of the initial received signal. Then, PSS detection and filtering are performed to obtain m first correlation peaks that meet the requirements, i.e., the fractional frequency offset estimation problem is solved by PSS detection. Then, based on the obtained m first correlation peaks, multiple integer frequency offsets are assumed, and the second correlation peaks corresponding to the first correlation peaks are calculated under each integer frequency offset assumption. After determining the time domain position of the second correlation peaks, frequency offset compensation is performed again. Finally, SSS detection and filtering are performed to obtain n second correlation peaks that meet the requirements, i.e., the integer frequency offset estimation problem is solved by SSS detection. Therefore, by using PSS detection and SSS detection respectively, the accuracy of frequency offset estimation in this application is improved.

[0043] (2) By separating the fractional frequency offset estimation and the integer frequency offset estimation, the problem of wasting computational resources caused by repeatedly performing PSS detection on the initial received signal when performing integer frequency offset estimation is avoided, thereby improving the efficiency of frequency offset estimation in this application. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. In the drawings:

[0045] Figure 1 This is an example diagram illustrating the related peak confusion problem in the prior art described in the background section of this application;

[0046] Figure 2 This is a flowchart of a time-frequency offset estimation method for an LTE system according to an embodiment of this application;

[0047] Figure 3 This is a structural diagram of a time-frequency offset estimation device for an LTE system according to an embodiment of this application. Detailed Implementation

[0048] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0049] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such use can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the term "comprising" and its variations should be interpreted as open-ended terms meaning "including but not limited to."

[0050] This application provides a time-frequency offset estimation method for an LTE system, such as... Figure 2 As shown, the method may include the following steps S1 to S6:

[0051] Step S1: The initial received signal is compensated for by multiple preset fractional frequency offsets to obtain the first target signal.

[0052] Step S2: Perform PSS detection on the first target signal to obtain the first dataset of the main synchronization signal. The first dataset includes the first m first correlation peaks sorted in descending order, as well as N-ID-2, first timing position and first frequency offset value corresponding to each first correlation peak.

[0053] Step S3: Based on the m first frequency offset values ​​and a plurality of preset integer multiple frequency offsets, calculate the second correlation peak value corresponding to each first correlation peak value;

[0054] Step S4: Locate the time domain position of each second correlation peak and perform frequency offset compensation to obtain the second target signal;

[0055] Step S5: Perform SSS detection and filtering on the second target signal to obtain the top n second correlation peaks in descending order, as well as N-ID-1, second timing position, and second frequency offset value corresponding to each second correlation peak; wherein, N-ID-1 and N-ID-2 are combined to obtain the cell ID;

[0056] Step S6: Output the cell ID, the second timing position, and the second frequency offset value.

[0057] Specifically, multiple decimal frequency offsets are preset, and the range of values ​​for these multiple decimal frequency offsets is as follows: to Δf represents the subcarrier spacing. In this embodiment, among the multiple fractional frequency offsets, each fractional frequency offset is distributed according to a predetermined interval step size. The predetermined interval step size can be a fixed interval step size or a non-fixed interval step size. The specific interval step size can be set according to actual needs. For example, the higher the required accuracy of the fractional frequency offset estimation, the smaller the interval step size; otherwise, the interval step size is larger. Of course, the computing power of the device performing the frequency offset estimation method also needs to be considered. If the computing power of the device is greater, it can support higher-precision frequency offset estimation. In a specific example, the configuration of the fractional frequency offset is as follows:

[0058] Configuration 1: The interval step size is

[0059] Configuration 2: The interval step size is

[0060] In the two configurations mentioned above, since the interval step size of configuration 1 is smaller than that of configuration 2, and the value range of configuration 1 is larger than that of configuration 2, the number of fractional frequency offsets contained in configuration 1 is greater than that contained in configuration 2. Therefore, when performing frequency offset estimation for the same signal, configuration 1 can analyze more data. So, for scenarios with high accuracy requirements, the configuration 1 scheme can be selected.

[0061] It should be noted that the above configurations 1 and 2 are merely example configurations and are not intended to limit multiple fractional frequency offsets in this embodiment.

[0062] Based on multiple preset fractional frequency offsets, after receiving the initial received signal, frequency offset compensation is performed on the initial received signal using these preset fractional frequency offsets respectively. The frequency offset-compensated initial received signal is referred to as the first target signal. Specifically, the initial received signal is a time-domain signal, assuming the initial received signal is {x(n)}, and the fractional frequency offset is... Related to Δf, the first target signal {r(n)} is:

[0063]

[0064] in, F s The sampling rate is used to acquire the initial received signal, and n represents the number of the nth time-domain sampled signal.

[0065] Then, PSS detection is performed on the first target signal. This embodiment can be combined with any existing PSS detection method. For ease of explanation, one PSS detection method is used as an example below:

[0066] The local PSS sequence p(k) is obtained and used to perform correlation detection with the primary synchronization signal (PSS) in the first target signal {r(n)}, thereby realizing time synchronization, frequency synchronization and physical layer cell identifier (N-ID-2) identification.

[0067] First, perform a sliding correlation operation between the first target signal {r(n)} and the local PSS sequence p(k) to obtain: Where L is the sequence length of the local PSS sequence, and m is the sliding window index. Then, the correlation peak is calculated, which refers to the power peak, specifically: P(m) = |R(m)| 2 .

[0068] In addition, methods for calculating relevant peak values ​​also include: Where α is the adjustment factor, which is a non-negative number.

[0069] Typical methods for calculating correlation peaks also include: β is the adjustment factor, which is also a non-negative number.

[0070] In practical applications, any PSS detection method or other PSS detection methods can be selected as needed; this embodiment does not impose any restrictions.

[0071] Based on the calculated correlation peaks, a pre-set threshold decision can be used for filtering, or a pre-trained deep neural network model can be used. Ultimately, the top m correlation peaks that exceed the first threshold and have the largest correlation are selected. For example, multiple correlation peaks can be sorted in descending order, and the top m are selected. In this embodiment, the correlation peaks that meet the filtering criteria are called the first correlation peaks. Furthermore, the timing position of each first correlation peak is called the first timing position, and the corresponding frequency offset is called the first frequency offset value.

[0072] The first target signal carries the actual N-ID-2 of the cell, so this N-ID-2 is also used as the N-ID-2 corresponding to the first correlation peak. N-ID-2 has three values: 0, 1, and 2. In the LTE system, the typical values ​​are: when N-ID-2 = 0, the corresponding root index u = 25; when N-ID-2 = 1, the corresponding root index u = 29; and when N-ID-2 = 2, the corresponding root index u = 34.

[0073] In summary, by performing fractional frequency offset compensation on the initial received signal and then performing PSS detection on the frequency offset compensated signal, m first correlation peaks that meet the requirements are obtained, as well as N-ID-2, first timing position and first frequency offset corresponding to each first correlation peak. In this embodiment, the obtained multiple data are also output as the first dataset of the master synchronization signal.

[0074] In step S3, N integer multiples of frequency offset are first preset. Based on the m first related peaks selected above, N integer multiples of frequency offset are assumed for each first related peak. When each first related peak is combined with the preset N frequency offsets, N corresponding second related peaks are generated (i.e., each first peak is expanded into a 1×N peak array). Finally, the combination of m first related peaks and N frequency offsets will jointly generate N×m second related peaks. In this embodiment, since one first related peak corresponds to one first frequency offset value, this application describes obtaining the second related peaks corresponding to each first related peak under m first frequency offset values ​​and N integer multiples of frequency offset, that is, a total of N×m second related peaks are obtained. Of course, in practical application scenarios, in order to reduce the computational complexity in the subsequent integer multiples of frequency offset estimation process, a preliminary screening can be performed from the N×m second related peaks to select P second related peaks, P <N×m。

[0075] Based on the P second correlation peaks obtained in step S3, the temporal location of each second correlation peak is first determined:

[0076]

[0077] in, This indicates the time-domain location corresponding to the second correlation peak, also known as the second timing position, to facilitate the distinction between the time-domain locations corresponding to the first and second correlation peaks. N pos Indicates the first timing position, n offset Indicates the timing offset, n ta This indicates the timing advance offset.

[0078] The timing offset n mentioned above offset There are two data source methods. Data source method 1 is real-time calculation, and the specific calculation formula is as follows:

[0079]

[0080] in, mod(.) represents the modulo operation function, round(.) represents rounding, and u represents the root index. N represents the integer multiples of the normalized frequency offset. FFT N represents the number of points in the Fast Fourier Transform. FFT The product of the product with the subcarrier spacing is equal to the sampling rate, i.e., F. s =N FFT Δf, N zc Indicates the sequence length.

[0081] Source method 2 involves establishing a data table using the aforementioned calculation formula. This table stores the timing offset corresponding to each integer multiple of the frequency offset. Once the integer multiple of the frequency offset is obtained, the corresponding timing offset can be found using this data table. For clarity, an example is shown in Table 1 below: Assume N... FFT =128, i.e., F s =1.92MHz, N zc =63, Δf=15kHz, and the range of integer multiples of frequency offset is [-60kHz, +60kHz]. Substituting these values ​​into the above calculation formula yields the following data table:

[0082] Integer frequency offset -4Δf -3Δf -2Δf -1Δf 0 1Δf 2Δf 3Δf 4Δf N_ID = 0 -53 24 -26 51 0 -51 26 -24 53 N_ID = 1 -20 49 -10 59 0 -59 10 -49 20 N_ID = 2 20 -49 10 -59 0 59 -10 49 -20

[0083] Table 1

[0084] As shown in Table 1, when the integer multiple frequency offset is -4Δf(-60kHz) and 4Δf(+60kHz) and N-ID-2=0, the timing offsets obtained by searching are -53 and 53, respectively.

[0085] In addition, as shown in Table 1, since the data table uses the column where the frequency offset is 0 as an integer multiple as the axis of symmetry, the data on both sides are symmetrical when both are taken as absolute values. Therefore, in practical applications, the data table can store only half of the data, which can save storage costs and improve search efficiency.

[0086] The aforementioned timing advance offset is preset and is set to compensate for the timing lag of the second related peak.

[0087] After locating the second timing position of each second correlation peak, it is also necessary to calculate the second frequency offset value corresponding to that second timing position. Specifically: first, obtain the integer and fractional frequency offsets corresponding to each second correlation peak, and then add the integer and fractional frequency offsets corresponding to that second correlation peak to obtain the second frequency offset value. in, Indicates an integer multiple of frequency offset. This indicates the decimal multiple of the frequency offset.

[0088] Then, based on the second timing position of the second correlation peak, the second frequency offset value is used to compensate for the frequency offset, and the frequency offset compensated signal is used as the second target signal.

[0089] Therefore, this embodiment performs hypothesis testing on the m selected first correlation peaks for integer multiple residual frequency offsets, and calculates the corresponding second timing position and accurate second frequency offset value under different integer multiple residual frequency offset assumptions, so as to facilitate frequency offset correction in practical applications. In existing frequency offset compensation, PSS detection is often performed separately for each frequency offset hypothesis, regardless of whether the difference between multiple frequency offset values ​​is close to an integer multiple of the frequency offset. Each PSS detection consumes a large amount of computing resources and processing time, resulting in low efficiency of frequency offset estimation.

[0090] In step S5, based on the second target signal obtained after integer multiple frequency offset compensation, SSS detection of the second target signal is also required. Similarly, this embodiment can be combined with any existing SSS detection method. For ease of explanation, the following uses one SSS detection method as an example, mainly including the following steps;

[0091] 1) Sequence generation:

[0092] The secondary synchronization signal (SSS) consists of two interleaved binary sequences of length 31, and is scrambled by a scrambling sequence provided by the primary synchronization signal (PSS).

[0093] The two binary sequences are generated based on different cyclic shifts of the m-sequence. The specific shift value is determined by the physical layer cell identifier group, i.e., the cell ID. The root index u determines this.

[0094] Sequence generation depends on initial conditions and polynomial definition, and candidate sequences need to be generated locally for matching.

[0095] 2) Community identifier group mapping:

[0096] The secondary synchronization signal and the primary synchronization signal jointly determine the PCI: PSS identifies the ID within the group. Also represented by N-ID-2, SSS identifier group ID It is also represented by N-ID-1. During detection, it is necessary to use the ID within the received PSS identifier group. and SSS identifier group ID Index lookup table, as shown in Table 2:

[0097]

[0098] Table 2

[0099] The physical layer cell identifier group is determined based on the mapping in Table 2, and finally the complete PCI is obtained by combining it with the primary synchronization signal.

[0100] 3) Scrambling code dependent on the master synchronization signal:

[0101] The generation of the auxiliary synchronization signal depends on the scrambling sequence of the primary synchronization signal. Therefore, PSS detection must be completed before detecting the primary synchronization signal, and the auxiliary synchronization signal can be obtained by descrambling the primary synchronization signal.

[0102] 4) Anti-interference and synchronization:

[0103] The auxiliary synchronization signal design enhances anti-interference capability through interleaving and scrambling, while working in conjunction with the primary synchronization signal to achieve time-frequency synchronization, ensuring the robustness of cell search.

[0104] As shown in step S3, N×m second correlation peaks will be generated. After filtering these N×m second correlation peaks, P second correlation peaks are obtained, and these P second correlation peaks are used for subsequent integer multiple frequency offset hypothesis verification. Therefore, after performing integer multiple frequency offset compensation and SSS detection on the initial received signal, multiple second correlation peaks that are integer multiples of P will be obtained. These multiple second correlation peaks need to be filtered again. Filtering can be done using a pre-set threshold decision or a pre-trained deep neural network model. Finally, the top n second correlation peaks that exceed the second threshold and have the largest correlation peaks are selected.

[0105] In step S6, N-ID-1 and N-ID-2 are first combined to obtain the cell ID, and then the cell ID, the n second correlation peaks that meet the requirements, and the second timing position and the second frequency offset value corresponding to each second correlation peak are output. This makes it easier to search for the required cell network through the cell ID, and to perform frequency offset compensation on the searched signal through the second timing position and the second frequency offset value, thereby establishing a stable communication connection with the cell network.

[0106] It should be noted that the sequence numbers of the steps in the above embodiments do not imply the order of execution. 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 embodiments of this application. In practical applications, all the above possible implementation methods can be arbitrarily combined in a combined manner to form possible embodiments of this application, which will not be described in detail here.

[0107] Based on the same inventive concept, this application also provides a time-frequency offset estimation device for an LTE system. The device includes a processor and a memory, the memory storing a computer program, and the processor being configured to run the computer program to execute the time-frequency offset estimation method for the LTE system of any of the above embodiments.

[0108] In an exemplary embodiment, a time-frequency offset estimation device for an LTE system is provided, such as... Figure 3 As shown, Figure 3The illustrated device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of the device 300 does not constitute a limitation on the embodiments of this application.

[0109] Processor 301 may be a CPU (Central Processing Unit), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0110] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0111] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0112] The memory 303 stores computer program code that executes the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the computer program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0113] The devices include, but are not limited to: mobile terminals such as mobile phones, smartwatches, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (such as in-vehicle navigation terminals), Internet of Things terminals, etc., as well as fixed terminals such as digital TVs, desktop computers, water meters, electricity meters, gas meters, etc. Figure 3 The apparatus shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0114] Based on the same inventive concept, this application also provides a storage medium storing a computer program, wherein the computer program is configured to execute the time-frequency offset estimation method of the LTE system of any of the above embodiments at runtime.

[0115] Those skilled in the art will clearly understand that the specific working process of the systems, devices, and modules described above can be referred to the corresponding process in the foregoing method embodiments. For the sake of brevity, it will not be repeated here.

[0116] Those skilled in the art will understand that the technical solution of this application, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several program instructions to cause an electronic device (e.g., a personal computer, server, or network device) to execute all or part of the steps of the methods described in the embodiments of this application when running the program instructions. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0117] Alternatively, all or part of the steps of the foregoing method embodiments can be implemented by hardware (such as electronic devices like personal computers, servers, or network devices) associated with program instructions. The program instructions can be stored in a computer-readable storage medium. When the program instructions are executed by the processor of the electronic device, the electronic device executes all or part of the steps of the methods described in the embodiments of this application.

[0118] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that within the spirit and principles of this application, modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the corresponding technical solutions to leave the protection scope of this application.

Claims

1. A time-frequency offset estimation method for an LTE system, characterized in that, include: The first target signal is obtained by using multiple preset fractional frequency offsets to compensate the initial received signal for fractional frequency offsets. The first dataset of the master synchronization signal is obtained by performing PSS detection on the first target signal. The first dataset includes the first m first correlation peaks sorted in descending order, as well as N-ID-2, first timing position and first frequency offset value corresponding to each first correlation peak. Based on m first frequency offset values ​​and a plurality of preset integer multiple frequency offsets, a second correlation peak value corresponding to each of the first correlation peak values ​​is calculated; The time-domain position of each of the second relevant peaks is located and frequency offset compensation is performed to obtain the second target signal; The second target signal is subjected to SSS detection and filtering to obtain the top n second correlation peaks in descending order, as well as the N-ID-1, second timing position, and second frequency offset value corresponding to each second correlation peak; wherein, N-ID-1 and N-ID-2 are combined to obtain the cell ID; wherein, the method for obtaining the second timing position corresponding to each second correlation peak includes: Based on the sequence length, root index, subcarrier spacing, and sampling rate, the timing offset caused by the integer multiple frequency offset is calculated using the following formula: ， in, This represents the timing offset. mod(.) represents the modulo operation function, round(.) represents rounding, and u is the root index. Represents the normalized integer multiples of frequency offset. This indicates the number of points in the Fast Fourier Transform. The product of the product with the subcarrier spacing is equal to the sampling rate. Indicates the length of the sequence; Obtain a preset timing advance offset, which is used to compensate for the timing lag of the second related peak. The second timing position is calculated based on the first timing position, the timing offset, and the timing advance offset, using the following formula: ， in, Indicates the second timing position. Indicates the first timing position. This represents the timing offset. This indicates the timing advance offset; Output the cell ID, the second timing position, and the second frequency offset value.

2. The method according to claim 1, characterized in that, The method further includes: A data table is established based on the calculation formula for the timing offset, and the data table stores the timing offset corresponding to each integer multiple of frequency offset; The timing offset corresponding to the integer multiple frequency offset is obtained by matching the data table.

3. The method according to claim 1, characterized in that, The method for obtaining the second frequency offset value corresponding to each of the second correlation peaks includes: Obtain the integer and fractional octave frequency offsets corresponding to each of the second relevant peak values; Calculate the sum of the integer and fractional octaves of the frequency offset corresponding to each of the second related peaks to obtain the second frequency offset value corresponding to the second related peak.

4. The method according to claim 1, characterized in that, The range of values ​​for the fractional octet frequency offset is: to ,in, This indicates the subcarrier spacing.

5. The method according to claim 4, characterized in that, Within the range of the fractional octave frequency offset, each fractional octave frequency offset is distributed according to a predetermined interval step size, which can be either a fixed interval step size or a non-fixed interval step size.

6. The method according to claim 1, characterized in that, The method further includes: Set a threshold for decision; The threshold decision is used to filter the top m first relevant peaks in descending order; and / or The threshold decision is used to filter the top n second-related peaks in descending order.

7. An apparatus, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform the time-frequency offset estimation method for the LTE system according to any one of claims 1 to 6.

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