Time-frequency offset estimation method and device of LTE (Long Term Evolution) system

Abstract

The invention provides a time frequency offset estimation method and device of an LTE system, and relates to the technical field of communication, and the method comprises the steps: employing a plurality of decimal frequency offsets to carry out the frequency offset compensation of an initial receiving signal, and obtaining a first target signal; performing PSS detection and screening on the first target signal to obtain first m first correlation peak values in descending order and N-ID-2, a first timing position and a first frequency offset value corresponding to the first correlation peak values; presetting a plurality of integer frequency offsets and calculating a second correlation peak value corresponding to each first correlation peak value; positioning the time domain position of each second correlation peak value and performing frequency offset compensation to obtain a second target signal; and performing SSS detection and screening on the second target signal to obtain first n second correlation peak values in descending order as well as N-ID-1, a second timing position and a second frequency offset value corresponding to the second correlation peak values, and combining N-ID-1 and N-ID-2 to obtain a cell ID. According to the method, decimal frequency multiplication estimation and integer frequency offset estimation are separated, and the accuracy is improved through double frequency offset estimation.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method and device for estimating time-frequency offset of an LTE system. Background Art

[0002] In wireless cellular communication systems, cell search is the core process for establishing a communication link between user equipment (UE) and a 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 the physical cell identifier (PCI) and system bandwidth, to enable the UE to successfully reside.

[0003] The Long Term Evolution (LTE) system uses a hierarchical cell search mechanism, implementing timing synchronization, frequency synchronization, and cell identity detection in stages through the Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS). During the initial access phase, the LTE system requires large frequency offset estimation, typically supporting estimates of frequency offsets greater than several integer multiples, such as ±15kHz or ±30kHz. This reduces residual frequency offset in subsequent service phases and ensures communication link stability.

[0004] However, the existing cell search method of the LTE system has significant defects: when the initial frequency offset exceeds half the subcarrier spacing, for example, when the LTE subcarrier spacing is 15kHz and the initial frequency offset is greater than 7.5kHz, the performance of the existing frequency offset estimation algorithm deteriorates sharply. Specifically,

[0005] 1) Correlation peak confusion problem.

[0006] Frequency offset estimation based on PSS relies on the sliding correlation characteristics of the ZC (Zadoff-Chu) sequence. For the sake of convenience, for example Figure 1 As shown, Figure 1 The horizontal axis is the sequence index, and the vertical axis is the correlation power. Assuming the sequence length Nzc = 63, the root index u = 25, N_ID_2 = 0, and the sampling rate is 1.92 MHz, and assuming that the received signal frequency deviation is equal to 0 Hz under the additive white Gaussian noise (AWGN) channel, it can be seen that regardless of the preset frequency deviation value of -30 kHz, -15 kHz, 0 kHz, 15 kHz, or 30 kHz, the corresponding power peak is relatively close to the power peak of the correct frequency deviation, resulting in the inability to effectively distinguish the power peak of the correct frequency deviation in practical applications.

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

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

[0009] Existing technologies attempt to mitigate this issue by optimizing ZC sequence design or introducing frequency offset compensation algorithms. However, due to the strong coupling between frequency offset and timing synchronization, and the ZC sequence's insensitivity to integer frequency offsets, these solutions still struggle to achieve robustness in scenarios with large frequency offsets. Therefore, a time-frequency offset estimation method is urgently needed that can effectively distinguish integer frequency offset hypotheses and reduce the probability of correlation peak confusion, thereby improving UE access success rates and communication quality in complex channel environments. Summary of the Invention

[0010] To address the above technical issues, the present application provides a method and apparatus for estimating time-frequency offsets in an LTE system. By separating fractional frequency offset estimation from integer frequency offset estimation, dual frequency offset estimation improves the accuracy of frequency offset estimation while avoiding the waste of computational resources caused by re-performing PSS detection for each integer frequency offset hypothesis. The technical solution is as follows:

[0011] In a first aspect, a time-frequency offset estimation method for an LTE system is provided, comprising:

[0012] Using a plurality of preset fractional frequency offsets, respectively performing fractional frequency offset compensation on the initial received signal to obtain a first target signal;

[0013] Performing PSS detection on the first target signal to obtain a first data set of a primary synchronization signal, the first data set comprising first m first correlation peaks sorted in descending order and an N-ID-2, a first timing position, and a first frequency offset value corresponding to each of the first correlation peaks;

[0014] Calculating a second correlation peak value corresponding to each of the first correlation peak values ​​according to the m first frequency offset values ​​and a plurality of preset integer multiples of the frequency offset value;

[0015] Locating the time domain position of each second correlation peak and performing frequency offset compensation to obtain a second target signal;

[0016] Performing SSS detection and screening on the second target signal to obtain the first n second correlation peaks sorted in descending order and the N-ID-1, the second timing position, and the second frequency offset value corresponding to each second correlation peak; wherein N-ID-1 and N-ID-2 are combined to obtain a cell ID;

[0017] The cell ID, the second timing position, and the second frequency offset value are output.

[0018] In a possible implementation, a method for obtaining a second timing position corresponding to each second correlation peak includes:

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

[0020] Obtaining a preset timing advance offset, where the timing advance offset is used to compensate for a timing lag of a second correlation peak;

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

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

[0023]

[0024] Among them, n offset represents the timing offset, mod(.) represents the modular operation function, round(.) represents rounding, u is the root index, Represents the normalized integer frequency deviation, N FFT Indicates the number of fast Fourier transform points, N FFT The product of the subcarrier spacing is equal to the sampling rate, N zc Indicates the length of the sequence.

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

[0026] Establishing a data table according to a calculation formula for calculating the timing offset, wherein the data table stores the timing offset corresponding to each of the integer multiple frequency offsets;

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

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

[0029]

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

[0031] In a possible implementation manner, a method for obtaining a second frequency offset value corresponding to each second correlation peak includes:

[0032] Obtaining an integer frequency offset and a fractional frequency offset corresponding to each of the second correlation peaks;

[0033] The sum of the integer multiple frequency offset and the fractional multiple frequency offset corresponding to each second correlation peak is calculated to obtain a second frequency offset value corresponding to the second correlation peak.

[0034] In a possible implementation, the value range of the fractional frequency offset is to Wherein, Δf represents the subcarrier spacing.

[0035] In a possible implementation, within the value range of the fractional frequency offset, each fractional frequency offset is distributed according to a predetermined interval step, and the predetermined interval step is any one of a fixed interval step and a non-fixed interval step.

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

[0037] Set threshold decision;

[0038] Filter the first m first correlation peaks in descending order by the threshold decision; and / or

[0039] The first n second correlation peaks sorted in descending order are screened by the threshold decision.

[0040] In a second aspect, a time-frequency offset estimation device for an LTE system is provided, the device comprising a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute any one of the time-frequency offset estimation methods for an LTE system described above.

[0041] The technical solutions provided in the embodiments of the present application can achieve the following technical effects:

[0042] (1) By separating the fractional frequency offset estimation from the integer frequency offset estimation, specifically, first using multiple fractional frequency offsets to compensate the frequency offset of the initial received signal, and then performing PSS detection and screening to obtain m first correlation peaks that meet the requirements, that is, solving the fractional frequency offset estimation problem through PSS detection. Then, based on the obtained m first correlation peaks, assume multiple integer frequency offsets and calculate the second correlation peak corresponding to the first correlation peak under each integer frequency offset assumption, determine the time domain position of the second correlation peak, and then perform frequency offset compensation, and finally perform SSS detection and screening to obtain n second correlation peaks that meet the requirements, that is, solving the integer frequency offset estimation problem through SSS detection. Therefore, the accuracy of the frequency offset estimation of the present application is improved by PSS detection and SSS detection respectively.

[0043] (2) By separating the fractional frequency offset estimation from the integer frequency offset estimation, the problem of wasting computing 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 the frequency offset estimation of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments of the present application. In the drawings:

[0045] Figure 1 This is an example diagram of the prior art in the background technology of this application that has the problem of correlation peak confusion;

[0046] Figure 2 This is a flow chart of a method for estimating time-frequency offset of an LTE system according to an embodiment of the present 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 the present application. DETAILED DESCRIPTION

[0048] The following describes exemplary embodiments of the present application in more detail with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0049] It should be noted that the terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that such usage is interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "including" and its variations are to 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, using a plurality of preset fractional frequency offsets to respectively perform fractional frequency offset compensation on an initial received signal to obtain a first target signal;

[0052] Step S2: Perform PSS detection on the first target signal to obtain a first data set of the primary synchronization signal, where the first data set includes the first m first correlation peaks sorted in descending order and the N-ID-2, the first timing position, and the first frequency offset value corresponding to each first correlation peak;

[0053] Step S3, calculating a second correlation peak value corresponding to each first correlation peak value based on the m first frequency offset values ​​and a plurality of preset integer multiples of the frequency offset value;

[0054] Step S4, locating the time domain position of each second correlation peak and performing frequency offset compensation to obtain a second target signal;

[0055] Step S5: Perform SSS detection and screening on the second target signal to obtain the first n second correlation peaks sorted in descending order and 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;

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

[0057] Specifically, multiple fractional frequency offsets are preset in advance, and the value range of the multiple fractional frequency offsets is to Δf represents the subcarrier spacing. Among the multiple fractional frequency offsets in this embodiment, 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 requirement for the fractional frequency offset estimation accuracy, the smaller the interval step size, otherwise the interval step size is larger. Of course, the computing power of the device that executes the frequency offset estimation method also needs to be considered. The greater the computing power of the device, the more it can support high-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 above two configurations, because 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, configuration 1 contains more fractional frequency offsets than configuration 2. Therefore, when estimating the frequency offset of the same signal, configuration 1 can analyze more data. Therefore, configuration 1 is the solution for scenarios with high accuracy requirements.

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

[0062] Based on the preset multiple fractional frequency offsets, after receiving the initial received signal, the preset multiple fractional frequency offsets are used to compensate the frequency offset of the initial received signal. The initial received signal after frequency offset compensation is called the first target signal. Specifically, the initial received signal is a time domain signal. Assuming that the initial received signal is {x(n)}, the fractional frequency offset is Related to Δf, the first target signal {r(n)} is:

[0063]

[0064] in, F s is the sampling rate when acquiring the initial received signal, and n is the number of the nth time domain sampling 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 of the PSS detection methods is used as an example below:

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

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

[0068] In addition, the method for calculating the correlation peak value also includes: 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 actual application, any PSS detection method or other PSS detection methods can be selected as needed, and this embodiment does not limit it.

[0071] Based on the calculated correlation peaks, screening can be performed using a pre-set threshold decision or a pre-trained deep neural network model. Ultimately, the top m correlation peaks that exceed the first threshold and have the largest correlation peaks are selected. For example, multiple correlation peaks are sorted in descending order, and the top m correlation peaks are selected. In this embodiment, the correlation peaks that meet the screening criteria are referred to as first correlation peaks. Furthermore, the timing position of each first correlation peak is referred to as a first timing position, and the corresponding frequency deviation is referred to as a first frequency deviation 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, 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] To sum up, 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 and the N-ID-2, first timing position and first frequency offset corresponding to each first correlation peak are obtained. This embodiment also outputs the obtained multiple data as the first data set of the main synchronization signal.

[0074] In step S3, N integer multiple frequency offsets are first preset, and based on the m first correlation peaks screened out above, N integer multiple frequency offset assumptions are made for each first correlation peak. When each first correlation peak is combined with the preset N frequency offsets, corresponding N second correlation peaks will be generated (that is, each first peak is expanded to a 1×N peak array). Ultimately, the combination of m first correlation peaks and N frequency offsets will jointly produce N×m second correlation peaks. In this embodiment, because one first correlation peak corresponds to one first frequency offset value, this application is described as obtaining a second correlation peak corresponding to each first correlation peak under m first frequency offset values ​​and N integer multiple frequency offsets, that is, a total of N×m second correlation peaks are obtained. Of course, in actual application scenarios, in order to reduce the complexity of calculations in the subsequent integer multiple frequency offset estimation process, preliminary screening can also be performed from the N×m second correlation peaks to select P second correlation peaks, P <N×m。

[0075] Based on the P second correlation peaks obtained in step S3, the time domain position of each second correlation peak is first located:

[0076]

[0077] in, Indicates the time domain position corresponding to the second correlation peak, also called the second timing position, so as to distinguish the time domain positions corresponding to the first correlation peak and the second correlation peak. pos Indicates the first timing position, n offset Indicates the timing offset, n ta Indicates the timing advance offset.

[0078] The above timing offset n offset There are two source methods. Source method 1 is real-time calculation. The specific calculation formula is:

[0079]

[0080] in, mod(.) represents the modulus operation function, round(.) represents rounding, and u represents the root index. Represents the normalized integer frequency deviation, N FFT Indicates the number of fast Fourier transform points, N FFT The product of the subcarrier spacing is equal to the sampling rate, that is, F s =N FFT Δf, N zc Indicates the sequence length.

[0081] Source method 2 is to create a data table using the above calculation formula. The data table stores the timing offset corresponding to each integer frequency offset. After obtaining the integer frequency offset, the corresponding timing offset is found through the data table. For ease of explanation, an example is shown in Table 1 below: Assume that N FFT =128, that is, F s =1.92MHz, N zc =63, Δf=15kHz, and the integer frequency deviation range is [-60kHz, +60kHz]. Substituting this into the above calculation formula yields the following data table:

[0082] Integer frequency deviation -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 frequency offset is -4Δf (-60 kHz), 4Δf (+60 kHz) and N-ID-2=0, the timing offsets obtained by searching are -53 and 53 respectively.

[0085] In addition, as can be seen from Table 1, since the data table uses the column where the integer frequency deviation is 0 as the symmetry axis, if the data on both sides are symmetrical when taking absolute values, in actual application, the data table can only store half of the data, which can save storage costs and improve search efficiency.

[0086] The above-mentioned timing advance offset is preset in advance and is set to compensate for the second correlation peak timing lag.

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

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

[0089] As can be seen, this embodiment performs a hypothesis test of integer multiple residual frequency offset on the m selected first correlation peaks, and calculates the corresponding second timing position and accurate second frequency offset value under different integer multiple residual frequency offset hypotheses, 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 frequency offset. Each PSS detection consumes a large amount of computing resources and processing time, resulting in low efficiency in frequency offset estimation.

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

[0091] 1) Sequence generation:

[0092] The Secondary Synchronization Signal (SSS) consists of two binary sequences of length 31 interleaved and scrambled by the 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 identification group, i.e., the cell ID and root index u.

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

[0095] 2) Cell ID group mapping:

[0096] The secondary synchronization signal and the primary synchronization signal jointly determine the PCI:PSS identification group ID Also represented by N-ID-2, SSS identifies the group ID Also expressed as N-ID-1. During detection, the received PSS identification group ID is required. and SSS identification group ID Index lookup table, as shown in Table 2:

[0097]

[0098] Table 2

[0099] Determine the physical layer cell identification group according to the mapping in Table 2, and finally obtain the complete PCI by combining the primary synchronization signal.

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

[0101] The generation of the secondary synchronization signal depends on the scrambling sequence of the primary synchronization signal. Therefore, before detecting the primary synchronization signal, PSS detection must be completed first, and the primary synchronization signal must be descrambled to obtain the secondary synchronization signal.

[0102] 4) Anti-interference and synchronization:

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

[0104] As can be seen from step S3, N×m second correlation peaks will be generated. After screening these N×m second correlation peaks, P second correlation peaks are obtained, and these P second correlation peaks are used for subsequent integer frequency offset hypothesis verification. Therefore, after performing integer frequency offset compensation and SSS detection on the initial received signal, multiple second correlation peaks of integer multiples of P will be obtained. Therefore, these multiple second correlation peaks need to be screened again. This screening can also be performed using a pre-set threshold judgment or a pre-trained deep neural network model. Ultimately, the first 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, n second correlation peaks that meet the requirements, and the second timing position and second frequency deviation value corresponding to each second correlation peak are output, so as to facilitate the subsequent search for the required cell network through the cell ID, and the frequency deviation of the searched signal is compensated through the second timing position and second frequency deviation value, thereby establishing a stable communication connection with the cell network.

[0106] It should be noted that the order of execution of the steps in the above embodiments does not necessarily imply a specific order of execution. The order of execution of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. In practical applications, all possible implementation methods described above can be combined in any manner to form possible embodiments of the present application, and will not be described in detail here.

[0107] Based on the same inventive concept, an embodiment of the present application also provides a time-frequency offset estimation device for an LTE system, which includes a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the time-frequency offset estimation method for an 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 device 300 shown 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 further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the device 300 does not constitute a limitation on the embodiments of the present application.

[0109] Processor 301 may be a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may 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 computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0110] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, 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 that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0112] The memory 303 is used to store computer program codes for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the computer program codes stored in the memory 303 to implement the contents shown in the above method embodiment.

[0113] Among them, the devices include but are not limited to: mobile terminals such as mobile phones, phone watches, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), Internet of Things terminals, etc., and fixed terminals such as digital TVs, desktop computers, water meters, electricity meters, gas meters, etc. Figure 3 The device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application.

[0114] Based on the same inventive concept, an embodiment of the present application further provides a storage medium storing a computer program, wherein the computer program is configured to execute the time-frequency offset estimation method for the LTE system of any one of the above embodiments when running.

[0115] Those skilled in the art will clearly understand that the specific working processes of the systems, devices, and modules described above can refer to the corresponding processes in the aforementioned method embodiments, and for the sake of brevity, they will not be further described here.

[0116] Those skilled in the art will appreciate that the technical solution of the present 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 a number of program instructions for causing an electronic device (e.g., a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application when the program instructions are executed. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0117] Alternatively, all or part of the steps of implementing the aforementioned method embodiments may be accomplished by hardware related to program instructions (such as electronic devices such as personal computers, servers, or network devices), and the program instructions may be stored in a computer-readable storage medium. When the program instructions are executed by a processor of an electronic device, the electronic device executes all or part of the steps of the methods described in the various embodiments of the present application.

[0118] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that, within the spirit and principles of the present application, they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate from the protection scope of the present application.

Claims

1. A time-frequency offset estimation method for an LTE system, characterized in that: include: Using a plurality of preset fractional frequency offsets, respectively performing fractional frequency offset compensation on the initial received signal to obtain a first target signal; Performing PSS detection on the first target signal to obtain a first data set of a primary synchronization signal, the first data set comprising first m first correlation peaks sorted in descending order and an N-ID-2, a first timing position, and a first frequency offset value corresponding to each of the first correlation peaks; Calculating a second correlation peak value corresponding to each of the first correlation peak values ​​according to the m first frequency offset values ​​and a plurality of preset integer multiples of the frequency offset value; Locating the time domain position of each second correlation peak and performing frequency offset compensation to obtain a second target signal; Performing SSS detection and screening on the second target signal to obtain the first n second correlation peaks sorted in descending order and the N-ID-1, the second timing position, and the second frequency offset value corresponding to each second correlation peak; wherein N-ID-1 and N-ID-2 are combined to obtain a cell ID; The cell ID, the second timing position, and the second frequency offset value are output.

2. The method according to claim 1, characterized in that The method for obtaining a second timing position corresponding to each second correlation peak includes: Calculating a timing offset caused by the integer frequency offset based on the sequence length, the root index, the subcarrier spacing, and the sampling rate; Obtaining a preset timing advance offset, where the timing advance offset is used to compensate for a timing lag of a second correlation peak; The second timing position is calculated based on the first timing position, the timing offset, and the timing advance offset.

3. The method according to claim 2, characterized in that The timing offset is calculated using the following formula: Among them, n offset represents the timing offset, mod(.) represents the modular operation function, round(.) represents rounding, u is the root index, Represents the normalized integer frequency deviation, N FFT Indicates the number of fast Fourier transform points, N FFT The product of the subcarrier spacing is equal to the sampling rate, N zc Indicates the length of the sequence.

4. The method according to claim 3, characterized in that The method further comprises: Establishing a data table according to a calculation formula for calculating the timing offset, wherein the data table stores the timing offset corresponding to each of the integer multiple frequency offsets; A timing offset corresponding to the integer frequency offset is obtained by matching from the data table.

5. The method according to claim 2, characterized in that The second timing position is calculated by the following formula: in, represents the second timing position, N pos represents the first timing position, n offset represents the timing offset, n ta Indicates the timing advance offset.

6. The method according to claim 1, characterized in that The method for obtaining the second frequency offset value corresponding to each second correlation peak includes: Obtaining an integer frequency offset and a fractional frequency offset corresponding to each of the second correlation peaks; The sum of the integer multiple frequency offset and the fractional multiple frequency offset corresponding to each second correlation peak is calculated to obtain a second frequency offset value corresponding to the second correlation peak.

7. The method according to claim 1, characterized in that The value range of the fractional frequency deviation is to Wherein, Δf represents the subcarrier spacing.

8. The method according to claim 7, characterized in that Within the value range of the fractional frequency offset, each fractional frequency offset is distributed according to a predetermined interval step, and the predetermined interval step is any one of a fixed interval step and a non-fixed interval step.

9. The method according to claim 1, characterized in that The method further comprises: Set threshold decision; Filter the first m first correlation peaks in descending order by the threshold decision; and / or The first n second correlation peaks sorted in descending order are screened by the threshold decision.

10. A device, characterized in that: The system comprises a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the time-frequency offset estimation method for the LTE system according to any one of claims 1 to 9.

Images