Frequency offset estimation method and device based on statistical algorithm, equipment and medium

Abstract

The invention relates to a frequency offset estimation method and device based on a statistical algorithm, equipment and a medium, and the method comprises the steps: receiving an air interface analog signal, converting the air interface analog signal into I Q data, and obtaining initial I Q data; performing data capture based on the initial I Q data to obtain current I Q data; calculating the frequency offset at the current moment based on the current I Q data to obtain a current frequency offset result, and performing data statistics based on the current frequency offset result and a historical frequency offset result to determine a target frequency offset solution; and performing frequency offset correction processing on the initial IQ data based on the target frequency offset solution. The frequency offset estimation and correction precision is improved, and the frequency offset value is accurately deduced by analyzing the statistical magnitude of the signal, so that the accuracy of frequency offset estimation is improved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technologies, and particularly to a frequency offset estimation method, apparatus, device, and medium based on a statistical algorithm. Background Art

[0002] There is a crystal oscillator frequency deviation between the transmitting and receiving ends of wireless communication. For a receiver using coherent demodulation, the frequency deviation will have a negative impact on signal detection and analysis at the receiving end. The receiving end should estimate the frequency offset as accurately as possible and perform frequency compensation on the received signal.

[0003] Traditional frequency offset estimation algorithms include: algorithms based on cyclic prefix, algorithms based on symbol retransmission, algorithms based on pilot sequences, algorithms based on PN sequences, etc. However, limited by the length of the sequence, no matter which frequency offset estimation algorithm is used, in the presence of multipath effects, or in environments with low signal-to-noise ratio and high interference, it will have a great impact on the estimation result and accuracy. Even by methods such as increasing the sequence length, combining frequency domain estimation, and anti-multipath processing, although the accuracy of the frequency offset estimation result can be effectively improved, in a communication system, in the case of low signal-to-noise ratio and extreme conditions, even a few frequency offset estimation errors will lead to data errors, packet loss, etc., causing serious information loss. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to propose a frequency offset estimation method, apparatus, device, and medium based on a statistical algorithm to improve the accuracy of frequency offset estimation.

[0005] To solve the above technical problems, an embodiment of the present application provides a frequency offset estimation method based on a statistical algorithm, including:

[0006] Receiving a radio interface analog signal, and converting the radio interface analog signal into IQ data to obtain initial IQ data;

[0007] Performing data capture based on the initial IQ data to obtain current IQ data;

[0008] Calculating the frequency offset at the current moment based on the current IQ data to obtain a current frequency offset result, and performing data statistics based on the current frequency offset result and historical frequency offset results to determine a target frequency offset solution;

[0009] Performing frequency offset correction processing on the initial IQ data based on the target frequency offset solution.

[0010] To solve the above technical problems, an embodiment of the present application provides a frequency offset estimation apparatus based on a statistical algorithm, including:

[0011] An analog signal conversion module, configured to receive an air interface analog signal and convert the air interface analog signal into IQ data to obtain initial IQ data;

[0012] A data capture module, configured to perform data capture based on the initial IQ data to obtain current IQ data;

[0013] A frequency offset estimation module, configured to calculate the frequency offset at the current moment based on the current IQ data to obtain a current frequency offset result, and perform data statistics based on the current frequency offset result and a historical frequency offset result to determine a target frequency offset solution;

[0014] A frequency offset correction processing module, configured to perform frequency offset correction processing on the initial IQ data based on the target frequency offset solution.

[0015] To solve the above technical problems, a technical solution adopted by the present invention is: to provide a computer device, including one or more processors; a memory, configured to store one or more programs, so that the one or more processors implement the frequency offset estimation method based on a statistical algorithm described in any one of the above.

[0016] To solve the above technical problems, a technical solution adopted by the present invention is: a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the frequency offset estimation method based on a statistical algorithm described in any one of the above is implemented.

[0017] An embodiment of the present invention provides a frequency offset estimation method, apparatus, device and medium based on a statistical algorithm. Among them, the method includes: receiving an air interface analog signal and converting the air interface analog signal into IQ data to obtain initial IQ data; performing data capture based on the initial IQ data to obtain current IQ data; calculating the frequency offset at the current moment based on the current IQ data to obtain a current frequency offset result, and performing data statistics based on the current frequency offset result and a historical frequency offset result to determine a target frequency offset solution; performing frequency offset correction processing on the initial IQ data based on the target frequency offset solution. The embodiment of the present invention performs data capture on the converted IQ data, calculates the frequency offset result of the captured data, and then performs data statistics based on the current frequency offset result and the historical frequency offset result to determine the target frequency offset solution, so as to perform frequency offset correction processing on the initial IQ data with the target frequency offset solution, which is beneficial to improving the accuracy of frequency offset estimation and correction, and by analyzing the statistic of the signal, accurately deriving the frequency offset value, which is beneficial to improving the accuracy of frequency offset estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the solutions in this application, the following will give a brief introduction to the accompanying drawings required for the description of the embodiments of this application. Obviously, the accompanying drawings in the following description are some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a flowchart of the implementation of the frequency offset estimation method based on the statistical algorithm provided by the embodiments of this application;

[0020] Figure 2 It is a schematic diagram of the overall architecture provided by the embodiments of this application;

[0021] Figure 3 It is a schematic diagram of the statistical frequency offset estimation value provided by the embodiments of this application;

[0022] Figure 4 It is a flowchart of the implementation of the first sub - process in the frequency offset estimation method based on the statistical algorithm provided by the embodiments of this application;

[0023] Figure 5 It is a flowchart of the implementation of the second sub - process in the frequency offset estimation method based on the statistical algorithm provided by the embodiments of this application;

[0024] Figure 6 It is a flowchart of the implementation of the third sub - process in the frequency offset estimation method based on the statistical algorithm provided by the embodiments of this application;

[0025] Figure 7 It is a flowchart of the implementation of the frequency offset estimation method based on the statistical algorithm provided by another embodiment of this application;

[0026] Figure 8 It is a schematic diagram of the frequency offset estimation accuracy provided by the embodiments of this application;

[0027] Figure 9 It is a schematic diagram of the frequency offset estimation device based on the statistical algorithm provided by the embodiments of this application;

[0028] Figure 10 It is a schematic diagram of the computer device provided by the embodiments of this application. Detailed implementation manners

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.

[0030] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0031] In order to enable those skilled in the technical field to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0032] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0033] Please refer to Figures 1 to 4 , Figure 1 which shows a specific implementation of the frequency offset estimation method based on statistical algorithms, Figure 2 is a schematic diagram of the overall architecture provided by the embodiments of this application, Figure 3 and is a schematic diagram of the statistical frequency offset estimation value provided by the embodiments of this application.

[0034] It should be noted that if there are substantially the same results, the method of the present invention is not limited to Figure 1 the process sequence shown, and the method includes the following steps:

[0035] S1: Receive the air interface analog signal and convert the air interface analog signal into IQ data to obtain initial IQ data.

[0036] The frequency offset estimation method based on statistical algorithms provided by the embodiments of this application is applied to a wireless communication device and can be applied to a receiver in a coherent demodulation mode. Its purpose is to accurately generate a frequency offset estimation value to compensate for the frequency offset value and reduce the negative impact of the frequency deviation on the signal detection and analysis at the receiving end, ensuring the quality of signal reception.

[0037] Specifically, the receiving end receives the air interface analog signal from the transmitting end, and then converts the air interface analog signal into IQ data through analog-to-digital conversion (ADC) and digital down-conversion (DDC) to obtain the initial IQ data.

[0038] Among them, the air interface analog signal refers to the radio frequency analog signal transmitted through the wireless channel. The IQ data is the quadrature baseband signal, which includes the in-phase component (I) and the quadrature component (Q), and is used to represent the modulated complex signal.

[0039] S2: Perform data capture based on the initial IQ data to obtain the current IQ data.

[0040] Specifically, the effective signal segment is extracted from the initial IQ data through the timing synchronization algorithm, and the noise and invalid signals are removed to obtain the current IQ data. In a specific embodiment, the signal start position is determined by using the preamble or sync head matching, and data capture is performed according to the signal start position to obtain the current IQ data.

[0041] S3: Calculate the frequency offset at the current moment based on the current IQ data to obtain the current frequency offset result, and perform data statistics based on the current frequency offset result and the historical frequency offset result to determine the target frequency offset solution.

[0042] Specifically, the frequency offset at the current moment is calculated according to the current IQ data, and then the current frequency offset result and the historical frequency offset result are statistically trained and converged to seek the optimal frequency offset solution to obtain the target frequency offset solution. Among them, the frequency offset is the carrier frequency deviation caused by the difference between the crystal oscillator frequencies of the transmitting end and the receiving end.

[0043] In a specific embodiment, before step S3, it further includes: dividing the interval based on the preset frequency offset estimation range and the preset adjustable interval width by using a preset formula to obtain the initial interval.

[0044] Specifically, according to the actual situation, it is set that the frequency offset estimation range can at most reach ±f max Hz, so the interval range is set as: R = (-f max , f max ), unit Hz; then an adjustable threshold is set, that is, the interval width is set as N Hz, and the interval is divided into l = R / N equal parts, that is, a total of l initial intervals are corresponding, and each initial interval is calculated through the preset formula.

[0045] Among them, the preset formula is:

[0046] R j = (-f max + N * (j - 1), -f max + j * l], j = (1, 2, 3,..., l);

[0047] Among them, R j is the initial interval, f max is the upper limit value of the preset frequency offset estimation, l is the number of the initial intervals, N is the preset adjustable interval width, and j is the serial number of the current initial interval.

[0048] In a specific embodiment, the set frequency offset estimation range is R = (-1000, 1000), and the preset adjustable interval width is 10 Hz.

[0049] Please refer to Figure 4 , Figure 4 which shows a specific implementation manner of step S3, described in detail as follows:

[0050] S31: Calculate the frequency offset at the current moment based on the current IQ data to obtain the current frequency offset result.

[0051] Specifically, after each signal is captured, the frequency offset at the current moment is calculated according to the current IQ data to obtain the current frequency offset result, and the current frequency offset result is denoted as f i , i = (1, 2, 3…n).

[0052] S32: Match the interval corresponding to the current frequency offset result from multiple pre-constructed initial intervals to obtain the basic interval.

[0053] S33: Cache the current frequency offset result into the basic interval, and perform data averaging on the historical frequency offset result and the current frequency offset result in the basic interval to generate a new historical frequency offset result in the basic interval.

[0054] Specifically, match the interval corresponding to the current frequency offset result f i from multiple pre-constructed initial intervals to obtain the basic interval, then cache the current frequency offset result into the basic interval, count the counter of the basic interval, and then perform data averaging based on the current frequency offset result and the historical frequency offset to generate a new historical frequency offset result in the basic interval.

[0055] Please refer to Figure 5 , Figure 5 which shows a specific implementation manner of step S33, described in detail as follows:

[0056] S331: Increment the counter of the basic interval by 1, and latch and mark the value of the counter of the basic interval.

[0057] S332: Cache the current frequency offset result into the array of the basic interval.

[0058] S333: Sum the historical frequency offset results and the current frequency offset results in the base interval and then perform an averaging process to generate a new historical frequency offset result in the base interval.

[0059] Specifically, increment the counter of the base interval by 1, i.e., cnt j = cnt j + 1, j = (1, 2, 3, … l); then latch the counter value corresponding to the base interval at this time and record the counter value as Num j . Cache the current frequency offset result f i into the array Data of the base interval j . At this time, record the current frequency offset result f i as

[0060] It should be noted that in each interval, when storing the current frequency offset result into the interval, sum and then average the current frequency offset result and the historical frequency offset result of the interval to obtain a new historical frequency offset result. Therefore, there is always a historical frequency offset result in the interval. So in the embodiments of the present application, after the current frequency offset result is cached into the array of the base interval, sum and then average the current frequency offset result and the historical frequency offset result of the base interval to generate a new historical frequency offset result in the base interval.

[0061] S34: Traverse the multiple initial intervals and the base interval to determine the target interval, and determine the target frequency offset solution based on the target interval.

[0062] In a specific embodiment, step S34 includes: traversing all the initial intervals and the base interval to select the interval with the largest counter value as the target interval; using the historical frequency offset result in the target interval as the target frequency offset solution.

[0063] S4: Perform frequency offset correction processing on the initial IQ data based on the target frequency offset solution.

[0064] Please refer to Figure 6 , Figure 6 which shows a specific implementation manner of step S4, described in detail as follows:

[0065] S41: Generate a carrier wave based on the target frequency offset solution.

[0066] S42: Multiply the carrier wave by the initial IQ data to perform frequency offset correction processing on the initial IQ data.

[0067] Specifically, a carrier is generated based on the target frequency offset solution, and the carrier is multiplied by the initial IQ data to perform frequency offset correction on the initial IQ data. A complex exponential signal is generated according to the optimal frequency offset Δfavgz, that is, a carrier is generated, and then the carrier is multiplied by the initial IQ data point by point to achieve frequency offset compensation.

[0068] Such as Figure 7 , Figure 7 is the implementation flowchart of the frequency offset estimation method based on the statistical algorithm provided by another embodiment of the present application; in the embodiment of the present application, according to the frequency offset estimation range of the actual communication system, it is set that the frequency offset estimation range can reach at most ±1000Hz. At this time, the frequency offset estimation range is set as R = (-1000, 1000), unit Hz; then an adjustable threshold is set, that is, the interval width NHz, set as 10Hz, and the interval is divided into l = R / N, a total of 200 equal parts, that is, a total of 200 initial intervals are corresponding. Each interval corresponds to a counter index, that is: cnt = {cnt1, cnt2, cnt3,..., cnt200}; after each capture of the target signal, the frequency offset estimation result is calculated, and the current frequency offset result obtained is denoted as fi, i = (1, 2, 3... n); then it is judged which interval the current frequency offset result f i falls into, and this interval is used as the basic interval, and the cnt counter of the interval corresponding to the basic interval is incremented by 1, that is, cnt j = cnt j +1, j = (1, 2, 3,..., l). The counter value corresponding to the current moment is latched and denoted as Num j , and the current frequency offset result f i is cached into the array Data j of the basic interval, denoted as In the embodiment of the present application, after the current frequency offset result f i is cached into the array of the basic interval, the current frequency offset result f i and the historical frequency offset results of the basic interval are summed and averaged to generate a new historical frequency offset result in this basic interval. Then all the initial intervals and the basic intervals are traversed to select the interval with the largest counter value as the target interval; finally, the historical frequency offset result in the target interval is used as the target frequency offset.

[0069] Such as Figure 8 shown, Figure 8 is the frequency offset estimation accuracy schematic diagram provided by the embodiment of the present application. In the embodiment of the present application, the given signal-to-noise ratios are 8, 10, 12, 8dB respectively. When the signal-to-noise ratio is [8, 10, 12dB] (red), the frequency offset estimation error gradually decreases; after 12dB, when the signal-to-noise ratio of 8dB is given again, the frequency offset estimation is about 2Hz, reaching the frequency offset estimation performance at a signal-to-noise ratio of 12dB. The trend of [12, 8dB] is shown in the blue graph.

[0070] In the embodiment of the present application, an air interface analog signal is received, and the air interface analog signal is converted into IQ data to obtain initial IQ data; data capture is performed based on the initial IQ data to obtain current IQ data; the frequency offset at the current moment is calculated based on the current IQ data to obtain a current frequency offset result, and data statistics are performed based on the current frequency offset result and the historical frequency offset result to determine a target frequency offset solution; frequency offset correction processing is performed on the initial IQ data based on the target frequency offset solution. In the embodiment of the present invention, the converted IQ data is subjected to data capture, and the frequency offset result of the captured data is calculated. Then, data statistics are performed based on the current frequency offset result and the historical frequency offset result to determine the target frequency offset solution, so as to perform frequency offset correction processing on the initial IQ data with the target frequency offset solution, which is beneficial to improving the accuracy of frequency offset estimation and correction. Moreover, by analyzing the statistics of the signal, the frequency offset value can be accurately deduced, which is beneficial to improving the accuracy of frequency offset estimation. In the embodiment of the present application, by statistically analyzing the frequency offset data, the ability to capture signal characteristics is enhanced, and the estimation error is reduced. In addition, the embodiment of the present application saves the historical frequency offset estimation for each time, not limited to the number of frames, and makes full use of the historical frequency offset estimation data. The more times, the more accurate the frequency offset estimation. In the embodiment of the present application, after introducing a new value each time in each interval, the values in the interval are summed and averaged and latched. The resources considered are only the counter corresponding to the "number of intervals" and the data cache resources, and it is possible to perform the maximum number of frequency offset statistics with extremely few resources.

[0071] Please refer to Figure 9 , as an implementation of the above Figure 1 shown method, an embodiment of a frequency offset estimation device based on a statistical algorithm is provided in the present application. This device embodiment corresponds to the Figure 1 shown method embodiment, and this device can be specifically applied to various communication devices.

[0072] As Figure 9 shown, the frequency offset estimation device based on the statistical algorithm in this embodiment includes: an analog signal conversion module 51, a data capture module 52, a frequency offset estimation module 53, and a frequency offset correction processing module 54, where:

[0073] The analog signal conversion module 51 is configured to receive an air interface analog signal and convert the air interface analog signal into IQ data to obtain initial IQ data;

[0074] The data capture module 52 is configured to perform data capture based on the initial IQ data to obtain current IQ data;

[0075] The frequency offset estimation module 53 is configured to calculate the frequency offset at the current moment based on the current IQ data, obtain the current frequency offset result, and perform data statistics based on the current frequency offset result and the historical frequency offset result to determine the target frequency offset solution;

[0076] The frequency offset correction processing module 54 is configured to perform frequency offset correction processing on the initial IQ data based on the target frequency offset solution.

[0077] Further, the frequency offset estimation module 53 includes:

[0078] The frequency offset calculation unit is configured to calculate the frequency offset at the current moment based on the current IQ data, and obtain the current frequency offset result;

[0079] The basic interval matching unit is configured to match the interval corresponding to the current frequency offset result from multiple pre-constructed initial intervals to obtain the basic interval;

[0080] The new historical frequency offset result generation unit is configured to cache the current frequency offset result into the basic interval, and perform data averaging on the historical frequency offset result and the current frequency offset result in the basic interval to generate a new historical frequency offset result in the basic interval;

[0081] The target interval confirmation unit is configured to traverse the multiple initial intervals and the basic interval to determine the target interval, and determine the target frequency offset solution based on the target interval.

[0082] Further, the new historical frequency offset result generation unit includes:

[0083] The counter calculation unit is configured to increment the counter of the basic interval by 1, and latch and mark the counter value of the basic interval;

[0084] The frequency offset caching unit is configured to cache the current frequency offset result into the array of the basic interval;

[0085] The data processing unit is configured to sum the historical frequency offset result and the current frequency offset result in the basic interval and then perform averaging processing to generate a new historical frequency offset result in the basic interval.

[0086] Further, the target interval confirmation unit includes:

[0087] The target interval selection unit is configured to traverse all the initial intervals and the basic interval to select the interval with the largest counter value as the target interval;

[0088] The target frequency offset solution confirmation unit is configured to use the historical frequency offset result in the target interval as the target frequency offset solution.

[0089] Further, the frequency offset estimation module 53 further includes:

[0090] An initial interval division unit, configured to divide an interval based on a preset formula according to the preset frequency offset estimation range and the preset adjustable interval width, to obtain the initial interval.

[0091] Further, the preset formula is:

[0092] R j = (-f max + N * (j - 1), -f max + j * l], j = (1, 2, 3,..., l);

[0093] wherein, R j is the initial interval, f max is the preset upper limit value of frequency offset estimation, l is the number of the initial intervals, and N is the preset adjustable interval width.

[0094] Further, the frequency offset correction processing module 54 includes:

[0095] A carrier generation unit, configured to generate a carrier based on the target frequency offset solution;

[0096] A multiplication unit, configured to multiply the carrier by the initial IQ data to perform frequency offset correction processing on the initial IQ data.

[0097] In the embodiment of the present application, a radio access network (RAN) air interface analog signal is received, and the RAN air interface analog signal is converted into IQ data to obtain initial IQ data; data capture is performed based on the initial IQ data to obtain current IQ data; the frequency offset at the current moment is calculated based on the current IQ data to obtain a current frequency offset result, and data statistics are performed based on the current frequency offset result and a historical frequency offset result to determine a target frequency offset solution; frequency offset correction processing is performed on the initial IQ data based on the target frequency offset solution. In the embodiment of the present invention, the converted IQ data is subjected to data capture, and the frequency offset result of the captured data is calculated, and then data statistics are performed based on the current frequency offset result and the historical frequency offset result to determine the target frequency offset solution, so as to perform frequency offset correction processing on the initial IQ data using the target frequency offset solution, which is beneficial to improving the accuracy of frequency offset estimation and correction, and by analyzing the statistic of the signal, the frequency offset value is accurately deduced, which is beneficial to improving the accuracy of frequency offset estimation.

[0098] To solve the above technical problems, the embodiment of the present application further provides a computer device. Specifically, please refer to Figure 10 , Figure 10 which is the basic structural block diagram of the computer device in this embodiment.

[0099] The computer device 6 includes a memory 61, a processor 62, and a network interface 63 that communicate with each other via a system bus. It should be noted that Figure 10 only the computer device 6 with three components, namely the memory 61, the processor 62, and the network interface 63, is shown. However, it should be understood that it is not necessary to implement all the shown components, and more or fewer components can be implemented alternatively. Among them, those skilled in the art of this technology can understand that a computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc. The computer device can be a receiving end device of any form of wireless communication.

[0100] The memory 61 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 61 can be an internal storage unit of the computer device 6, such as the hard disk or memory of the computer device 6. In other embodiments, the memory 61 can also be an external storage device of the computer device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 6. Of course, the memory 61 can also include both the internal storage unit and the external storage device of the computer device 6. In this embodiment, the memory 61 is generally used to store the operating system and various application software installed on the computer device 6, such as the program code of the frequency offset estimation method based on statistical algorithms. In addition, the memory 61 can also be used to temporarily store various data that have been output or will be output.

[0101] The processor 62 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 62 is generally used to control the overall operation of the computer device 6. In this embodiment, the processor 62 is used to run the program code stored in the memory 61 or process data, such as running the program code of the above frequency offset estimation method based on statistical algorithms to implement various embodiments of the frequency offset estimation method based on statistical algorithms.

[0102] The network interface 63 may include a wireless network interface or a wired network interface, and the network interface 63 is generally used to establish a communication connection between the computer device 6 and other electronic devices.

[0103] The present application also provides another implementation manner, that is, to provide a computer-readable storage medium storing a computer program, and the computer program can be executed by at least one processor to enable the at least one processor to execute the steps of a frequency offset estimation method based on statistical algorithms as described above.

[0104] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation manner. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) and includes several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods of various embodiments of the present application.

[0105] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The drawings of the present application give preferred embodiments, but do not limit the scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or perform equivalent replacements on some of the technical features. Any equivalent structure directly or indirectly using the content of the specification and drawings of the present application in other related technical fields is equally within the protection scope of the present application.

Claims

1. A frequency offset estimation method based on a statistical algorithm, characterized in that: include: Receiving an air interface analog signal, and converting the air interface analog signal into IQ data to obtain initial IQ data; Performing data capture based on the initial IQ data to obtain current IQ data; Calculating the frequency deviation at a current moment based on the current IQ data to obtain a current frequency deviation result, and performing data statistics based on the current frequency deviation result and historical frequency deviation results to determine a target frequency deviation solution; The initial IQ data is subjected to frequency offset correction processing based on the target frequency offset solution.

2. The frequency offset estimation method based on statistical algorithm according to claim 1, characterized in that: The calculating the frequency deviation at the current moment based on the current IQ data to obtain a current frequency deviation result, and performing data statistics based on the current frequency deviation result and historical frequency deviation results to determine a target frequency deviation solution includes: Calculate the frequency deviation at the current moment based on the current IQ data to obtain the current frequency deviation result; Matching an interval corresponding to the current frequency offset result from a plurality of pre-constructed initial intervals to obtain a basic interval; Cache the current frequency offset result in the basic interval, and average the historical frequency offset results and the current frequency offset result in the basic interval to generate a new historical frequency offset result in the basic interval; The plurality of initial intervals and the basic intervals are traversed to determine the target interval, and the target frequency offset solution is determined based on the target interval.

3. The frequency offset estimation method based on statistical algorithm according to claim 2, characterized in that: The step of caching the current frequency offset result in the basic interval and averaging the historical frequency offset result and the current frequency offset result in the basic interval to generate a new historical frequency offset result in the basic interval includes: Increasing the counter of the basic interval by 1, and latching and marking the counter value of the basic interval; Cache the current frequency deviation result in the array of the basic interval; The historical frequency deviation result and the current frequency deviation result in the basic interval are summed and averaged to generate a new historical frequency deviation result in the basic interval.

4. The frequency offset estimation method based on statistical algorithm according to claim 2, characterized in that: The traversing the plurality of initial intervals and the basic intervals to determine the target interval, and determining the target frequency offset solution based on the target interval, includes: Traversing all the initial intervals and the basic intervals to select an interval with the largest counter value as the target interval; The historical frequency offset result in the target interval is used as the target frequency offset solution.

5. The frequency offset estimation method based on statistical algorithm according to claim 2, characterized in that: Before calculating the frequency deviation at the current moment based on the current IQ data to obtain a current frequency deviation result, and performing data statistics based on the current frequency deviation result and historical frequency deviation results to determine a target frequency deviation solution, the method further includes: The interval is divided by using a preset formula based on the preset frequency offset estimation range and the preset adjustable interval width to obtain the initial interval.

6. The frequency offset estimation method based on statistical algorithm according to claim 5, characterized in that: The preset formula is: R j =(-f max +N*(j-1),-f max +j*l],j=(1,2,3,…,l); Among them, R j is the initial interval, f max is the preset frequency offset estimation upper limit value, l is the number of the initial intervals, and N is the preset adjustable interval width.

7. The frequency offset estimation method based on statistical algorithm according to any one of claims 1 to 6, characterized in that: The performing frequency offset correction processing on the initial IQ data based on the target frequency offset solution includes: generating a carrier wave based on the target frequency offset solution; The carrier wave is multiplied by the initial IQ data to perform frequency offset correction processing on the initial IQ data.

8. A frequency deviation estimation device based on a statistical algorithm, characterized in that: include: The analog signal conversion module is used to receive the air interface analog signal and convert the air interface analog signal into IQ data to obtain initial IQ data; A data capture module, configured to capture data based on the initial IQ data to obtain current IQ data; A frequency offset estimation module, configured to calculate the frequency offset at a current moment based on the current IQ data, obtain a current frequency offset result, and perform data statistics based on the current frequency offset result and historical frequency offset results to determine a target frequency offset solution; A frequency offset correction processing module is used to perform frequency offset correction processing on the initial IQ data based on the target frequency offset solution.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the frequency offset estimation method based on a statistical algorithm as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the frequency offset estimation method based on a statistical algorithm according to any one of claims 1 to 7 is implemented.

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