Frequency offset estimation method, device, equipment, storage medium and program product
By employing multiple pilot sequence division and periodic extension techniques, the dual requirements of frequency offset estimation accuracy and range in low-Earth orbit satellite communication were addressed, achieving a dual improvement in both the accuracy and range of frequency offset estimation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-03-13
AI Technical Summary
Existing frequency offset estimation methods cannot simultaneously meet the dual requirements of estimation accuracy and estimation range in the high dynamic environment of low-Earth orbit satellite communication, resulting in errors in frequency offset estimation results.
The method employs multiple pilot sequence division and periodic extension techniques. By dividing the received signal into at least two different pilot sequences, the initial frequency offset estimate is determined, and periodic extension is performed. Finally, weighted merging is performed to obtain the target frequency offset estimate.
It achieves a balance between improving estimation accuracy and estimation range in low-Earth orbit satellite communications, thereby enhancing the accuracy and reliability of frequency offset estimation.
Smart Images
Figure CN121664587A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of communication technology, and in particular to a frequency offset estimation method, apparatus, device, storage medium, and program product. Background Technology
[0002] In recent years, satellite internet has become a strategic emerging industry that major players worldwide are vying to develop. At the international level, multiple low-Earth orbit satellite constellation systems have entered the large-scale deployment phase. Regarding technical standards, the international standards organization 3rd Generation Partnership Project (3GPP) has incorporated non-terrestrial networks (NTNs) starting from Release 17 into the 5th Generation Mobile Communication Technology (5G) standard system, marking the formal integration of space-ground communication into the global mobile communication system.
[0003] Against this backdrop, satellite terminals, as key devices connecting space networks and ground users, directly determine the service quality and commercial prospects of the entire satellite internet system. However, low-Earth orbit satellites typically operate at altitudes of 300 to 2000 kilometers, with speeds reaching approximately 7.8 kilometers per second, posing significant technical challenges to satellite-to-ground communication. One of the core challenges is carrier frequency offset (hereinafter referred to as "frequency offset") caused by the Doppler effect. In typical satellite communication frequency bands such as the S-band, Doppler frequency offset can reach tens of thousands of hertz, with a rate of change of hundreds of hertz per second, far exceeding that of traditional terrestrial mobile communication systems. Secondly, the rate of change of Doppler frequency offset is rapid. Due to the high-speed motion of satellites and the large rate of change of radial relative velocity, the rate of change of Doppler frequency offset also reaches hundreds of hertz per second. During continuous communication or after a short period of sleep and wake-up, the frequency offset range of terminal devices will be tens or even hundreds of times larger compared to terrestrial communication. Therefore, existing accurate frequency compensation needs to support a wider range of frequency offset estimation capabilities.
[0004] Since the residual frequency offset value between two frequency offset estimation times is generally within tens of hertz after the initial frequency offset compensation in cell search of terrestrial communication, under the regulation of the Automatic Frequency Control (AFC) module, the estimation range of the existing accurate frequency offset estimation algorithm obviously exceeds this fluctuation range. Therefore, only the estimation accuracy is considered, and the problem of residual frequency offset exceeding the frequency offset estimation range does not need to be considered. At the same time, the pilot density of the existing communication protocol does not need to be designed to be too dense.
[0005] However, in low-Earth orbit (LEO) satellite environments, the residual frequency offset per second can expand to hundreds or even thousands of hertz. Without encryption of the pilot density, existing algorithms are likely to produce inaccurate estimation results due to exceeding the frequency offset estimation range. Furthermore, because the distance between an LEO satellite and a terminal is much greater than the distance between a ground base station and a terminal, the signal-to-noise ratio (SNR) of the LEO satellite signal reaching the terminal after spatial fading is often much lower than that of the signal reaching the ground base station. Given the same pilot resources, the estimation range and accuracy of time-domain correlation algorithms are mutually exclusive: higher accuracy results in a smaller range, and vice versa. Therefore, traditional frequency offset estimation methods cannot simultaneously meet the dual requirements of estimation accuracy and estimation range. Summary of the Invention
[0006] This application aims to at least solve one of the technical problems existing in the related art. To this end, this application proposes a frequency offset estimation method, apparatus, device, storage medium, and program product to solve the problem that traditional frequency offset estimation methods cannot simultaneously meet the dual requirements of estimation accuracy and estimation range, thereby taking into account both estimation accuracy and estimation range when performing frequency offset estimation.
[0007] The frequency offset estimation method according to the first aspect of this application includes: Based on the received signal, at least two different pilot sequence divisions are performed to obtain at least two division data corresponding to each pilot sequence division; For each pilot sequence division, an initial frequency offset estimate is determined based on the division data. For each initial frequency offset estimate, periodic extension is performed to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. From each pilot sequence, a corresponding extended frequency offset estimate is determined to obtain an optimal extended frequency offset estimate group. The target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group.
[0008] According to one embodiment of this application, the step of performing at least two different pilot sequence divisions based on the received signal to obtain at least two division data corresponding to each pilot sequence division includes: Determine the time-domain LS channel estimate of the pilot sequence in the received signal; The time-domain LS channel estimate is divided into at least two different pilot sequences, and at least two partition data corresponding to each pilot sequence partition are obtained.
[0009] According to one embodiment of this application, the step of dividing the time-domain LS channel estimate into at least two different pilot sequence partitions includes: If the received signal is in single-carrier format, the time-domain LS channel estimate is divided into segments at least twice; wherein the number of segments in each division is different from the other divisions and the number of segments in different divisions are coprime numbers. If the received signal is in a multi-carrier format, the time-domain LS channel estimate is divided at least twice according to different symbol intervals; wherein the symbol intervals of different divisions are coprime numbers.
[0010] According to one embodiment of this application, when performing periodic extension for each initial frequency offset estimate, the number of left and right extensions for each initial frequency offset estimate is less than or equal to a preset threshold; wherein the preset threshold is determined based on the number of segments or the spacing between segments of the corresponding pilot sequence.
[0011] According to one embodiment of this application, the step of determining an extension frequency offset estimate from each of the corresponding extension frequency offset estimates of each pilot sequence to obtain an optimal extension frequency offset estimate group includes: For each pilot sequence division, select an extended frequency offset estimate and construct at least one combination of extended frequency offset estimates. Among the various combinations of extended frequency offset estimates, the combination of extended frequency offset estimates with the closest mutual deviation is determined as the target combination of extended frequency offset estimates.
[0012] According to one embodiment of this application, determining an initial frequency offset estimate based on each partitioned data for each pilot sequence partition includes: For each partition of the pilot sequence, determine the time-domain correlation value for each partition of the data. Based on the aforementioned time-domain correlation values, the average frequency discrimination cross product value for each pilot sequence division is determined. The initial frequency offset estimate is calculated based on the average frequency discrimination cross product value of each pilot sequence division.
[0013] The frequency offset estimation apparatus according to a second aspect embodiment of this application includes: The partitioning module is used to perform at least two different pilot sequence partitions based on the received signal, and obtain at least two partition data corresponding to each pilot sequence partition; The first determining module is used to determine an initial frequency offset estimate based on each of the partitioned data for each pilot sequence partition. The extension module is used to perform periodic extension on each of the initial frequency offset estimates to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. The second determining module is used to determine one extended frequency offset estimate from each of the extended frequency offset estimates corresponding to each pilot sequence, so as to obtain the optimal extended frequency offset estimate group. The merging module is used to perform weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group to obtain the target frequency offset estimate of the received signal.
[0014] An electronic device according to a third aspect of this application includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the frequency offset estimation methods described above.
[0015] According to a fourth aspect of the present application, the storage medium is a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the frequency offset estimation method as described above.
[0016] A computer program product according to a fifth aspect of this application includes a computer program that, when executed by a processor, implements the frequency offset estimation method as described above.
[0017] The above-described one or more technical solutions in the embodiments of this application have at least the following technical effects: This application performs at least two different pilot sequence divisions based on the received signal, obtaining at least two division data corresponding to each pilot sequence division; then, for each pilot sequence division, an initial frequency offset estimate is determined based on each division data; further, periodic extension is performed on each initial frequency offset estimate to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division; and an extended frequency offset estimate is determined from each extended frequency offset estimate corresponding to each pilot sequence division to obtain an optimal extended frequency offset estimate group; thus, the target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group. Therefore, this application employs a strategy of multiple pilot sequence divisions for frequency offset estimation. Since different pilot sequence divisions have different estimation ranges and accuracies, both estimation range and accuracy can be considered during the initial frequency offset estimation. Furthermore, periodic extension of the initial frequency offset estimate leverages the different estimation ranges under different pilot sequence divisions, effectively expanding the final frequency offset estimation range. Moreover, weighted merging of the frequency offset estimation results from different pilot sequence divisions effectively improves the estimation accuracy of time-domain correlation techniques, resulting in higher final frequency offset estimation accuracy. This achieves a dual improvement in estimation accuracy and estimation range.
[0018] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is one of the flowcharts illustrating the frequency offset estimation method provided in the embodiments of this application.
[0021] Figure 2 This is one of the scenario diagrams of pilot sequence division in the frequency offset estimation method provided in the embodiments of this application.
[0022] Figure 3 This is the second schematic diagram of the pilot sequence division scenario in the frequency offset estimation method provided in the embodiments of this application.
[0023] Figure 4 This is a schematic diagram of a scenario in which the target extended frequency offset estimation value combination is determined in the frequency offset estimation method provided in the embodiments of this application.
[0024] Figure 5 This is the second flowchart of the frequency offset estimation method provided in the embodiments of this application.
[0025] Figure 6 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation
[0026] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0027] It should be noted that in recent years, satellite internet has moved from the technological concept stage to a critical period of large-scale constellation deployment and commercial application, becoming a strategic emerging industry that major global players are vying to develop. In terms of technical standards, the international standards organization 3GPP has incorporated NTN, starting with Release 17, into the 5G standard system, marking the formal integration of space-ground communication into the global mobile communication system.
[0028] With the finalization of the 5G-Advanced standard (Release 18), NTN technology has been further enhanced in terms of support capabilities, network architecture, and terminal adaptation, laying an important foundation for the large-scale development of the industry. Against this backdrop, satellite terminals, as the sole physical interface connecting space networks and terrestrial users, directly determine the service quality and commercial prospects of the entire satellite internet system through their performance, cost control, and industrialization progress. They are the core carrier for transforming technological achievements into market value.
[0029] In this process, technological innovation in terminal devices has become a key factor in improving system performance: by achieving precise frequency compensation, intelligent beam management, and seamless switching in highly dynamic environments, terminals can directly improve the transmission reliability, spectrum utilization efficiency, and user experience continuity of satellite links. In the future, terminal technologies supporting intelligent convergence of satellite and terrestrial networks and lossless service switching will be an important development direction for terrestrial-satellite converged networks in the 5G-Advanced and 6th Generation Mobile Communication Technology (6G) stages.
[0030] Currently, low-Earth orbit (LEO) satellites typically operate at altitudes of 300–2000 kilometers, with short orbital periods (approximately 90 minutes per orbit around the Earth) and speeds as high as 7.8 kilometers per second. Their Doppler shift characteristics differ significantly from those of terrestrial communications. Firstly, the Doppler shift is greater, according to the formula: ; in, For Doppler frequency shift, For carrier frequency, The radial relative velocity of the satellite domain terminal. The speed of light is a factor. In the S-band, the Doppler shift can reach tens of thousands of hertz, far exceeding that of terrestrial communication. Secondly, the rate of change of the Doppler shift is rapid; due to the high-speed motion of the satellite and the large rate of change of its radial relative velocity, the rate of change of the Doppler shift is also as high as hundreds of hertz per second. During continuous communication or after a short period of sleep and wake-up, the frequency offset range of terminal equipment will be tens or even hundreds of times larger than that of terrestrial communication. Therefore, existing accurate frequency compensation needs to support a wider range of frequency offset estimation capabilities.
[0031] Because in terrestrial communication, after initial frequency offset compensation during cell search, the residual frequency offset value between two frequency offset estimation times is generally within tens of hertz under the control of the automatic frequency control module, the estimation range of existing accurate frequency offset estimation algorithms obviously exceeds this fluctuation range. Therefore, they often only consider the estimation accuracy and do not need to consider the problem of residual frequency offset exceeding the frequency offset estimation range. At the same time, the pilot density of existing communication protocols does not need to be designed to be too dense. However, in the low-Earth orbit satellite environment, the residual frequency offset value per second has expanded to hundreds or even thousands of hertz. At this time, if the protocol pilot density is not encrypted, existing algorithms are likely to cause estimation errors because they exceed the frequency offset estimation range.
[0032] On the other hand, because the distance between low-Earth orbit satellites and terminals is much greater than that between low-Earth orbit satellites and ground base stations, the signal-to-noise ratio (SNR) of low-Earth orbit satellites reaching the terminal after spatial fading is often much lower than that of signals reaching the ground base station. Furthermore, under the same pilot resources, the estimation range and estimation accuracy of time-domain correlation algorithms are mutually exclusive; higher accuracy results in a smaller range, and lower accuracy results in a larger range. Existing methods cannot simultaneously meet the dual requirements of estimation accuracy and estimation range.
[0033] Based on this, this application proposes a frequency offset estimation method, apparatus, device, storage medium, and program product. Without changing the existing number and density of pilot resources, it adopts multiple frequency offset estimations and uses frequency offset merging + periodic extension technology with different estimation ranges to achieve a dual improvement in estimation accuracy and estimation range, thereby solving the problem of high dynamic and accurate frequency offset compensation in low-orbit satellite communication.
[0034] It should be noted that all actions involving the acquisition of signals, information, or data in this application are carried out in compliance with the relevant data protection laws and regulations of the locality and with authorization from the owner of the relevant device.
[0035] Figure 1 This is one of the flowcharts illustrating the frequency offset estimation method provided in the embodiments of this application, such as... Figure 1 As shown, the frequency offset estimation method includes: Step 110: Perform at least two different pilot sequence divisions based on the received signal, and obtain at least two division data corresponding to each pilot sequence division.
[0036] Step 120: For each pilot sequence division, determine the initial frequency offset estimate based on each division data.
[0037] Step 130: Perform periodic extension on each initial frequency offset estimate to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division.
[0038] Step 140: Determine one extended frequency offset estimate from each of the extended frequency offset estimates corresponding to each pilot sequence to obtain the optimal extended frequency offset estimate group.
[0039] Step 150: Based on the weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group, the target frequency offset estimate of the received signal is obtained.
[0040] It should be noted that the execution subject of the frequency offset estimation method provided in this application embodiment can be a computer device, such as a mobile phone, tablet computer, laptop computer, handheld computer, vehicle-mounted electronic device, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA). Specifically, the computer device can be a satellite terminal that supports satellite communication or a general-purpose terminal that does not support satellite communication, and will be referred to as the terminal below.
[0041] Specifically, in this application, the terminal can receive downlink signals (hereinafter referred to as received signals) from satellites (including low-Earth orbit satellites, medium-Earth orbit satellites, and high-Earth orbit satellites).
[0042] Furthermore, the terminal can calculate the time-domain least squares (LS) channel estimate of the pilot sequence in the received signal.
[0043] It should be noted that the satellite downlink signal may be in single-carrier format or multi-carrier format.
[0044] Therefore, after obtaining the time-domain LS channel estimate, the time-domain LS channel estimate can be divided into pilot data multiple times (which can be referred to as pilot sequence division in this application) according to the specific format of the received signal and the corresponding division principle. For example, two-time division, three-time division, and five-time division can be performed.
[0045] The division principles can include division by segment and division by symbol interval.
[0046] When dividing by segments, the number of segments in each division must be different from the previous divisions. For example, if the first division is into 2 segments, then subsequent divisions cannot also be into 2 segments, and the number of segments in different divisions must be coprime numbers. If the first division is into 2 segments, then subsequent divisions must have a number of segments that are coprime to 2. For example, if the first division is into 2 segments, the second division can be into 3 segments, the third division can be into 5 segments, and so on.
[0047] For partitioning by sign interval, the sign interval of each partition must be different from that of the previous partitions. For example, if the sign interval of the first partition is 2, then the sign interval of subsequent partitions cannot be 2, and the sign intervals of different partitions must be coprime numbers. If the sign interval of the first partition is 2, then the sign interval of subsequent partitions must be coprime numbers of 2. For example, if the sign interval of the first partition is 2, the sign interval of the second partition can be 3, the sign interval of the third partition can be 5, and so on.
[0048] Therefore, each division yields a corresponding number of data portions, and in this application, each data portion can be defined as a division data.
[0049] Furthermore, for each pilot sequence division, the correlation values of adjacent segments / specified symbol spacing can be conjugately multiplied and like terms can be summed to obtain the average frequency discrimination cross product value of that pilot sequence division.
[0050] Then, based on the average frequency discrimination cross product value of each pilot sequence division, the frequency offset estimate of that pilot sequence division can be calculated and used as the initial frequency offset estimate.
[0051] It should be noted that large frequency offset scenarios can easily cause phase blurring, meaning that the phase rotation caused by the frequency offset exceeds 2. This exceeds the effective estimation range of the atan2 function, thus causing the estimated initial frequency offset value to be... Error.
[0052] Therefore, this application employs a multiple partitioning method using coprime numbers, with each partition having a frequency discrimination range of [-]. , (Unit: Hertz), where The estimated frequency offset value is then periodically extended, with each extension not exceeding [a certain value]. The formula is as follows: ; in, .
[0053] Therefore, each pilot sequence division can yield multiple extended frequency offset estimates.
[0054] Furthermore, for each pilot sequence division, one can be selected from its corresponding extended frequency offset estimates, and a combination (which can be referred to as the extended frequency offset estimate group) can be formed by selecting the extended frequency offset estimates.
[0055] Therefore, multiple different combinations can be obtained.
[0056] Furthermore, the combination with the closest frequency offset values among the various combinations can be identified as the optimal extended frequency offset estimation value group.
[0057] Furthermore, by combining the weight values of each pilot sequence division, the extended frequency offset estimates in the optimal extended frequency offset estimate group can be weighted and merged, and the frequency offset estimate obtained by weighted merging can be used as the final frequency offset estimate, which is the target frequency offset estimate of the received signal.
[0058] Specifically, the target frequency offset estimate can be calculated using the following formula: ; in, This represents the final frequency offset estimate, i.e., the target frequency offset estimate. This represents the weight value of the m-th pilot sequence division. M represents the number of partitions; This represents the extended frequency offset estimate of the m-th pilot sequence division in the optimal extended frequency offset estimate group; , and Initially The value can be any value in k, and it is the optimal value in k when calculating the target frequency offset estimate (that is, the k value corresponding to the extended frequency offset estimate of the pilot sequence in the optimal extended frequency offset estimate group). ; ; This indicates the number of segments or symbol intervals in the corresponding subpilot sequence.
[0059] Specifically, , … For the order found in subsequent searches The minimum result is corresponding to value.
[0060] Among them, the weight value for each partition This is related to the signal-to-noise ratio (SNR) of the pilots involved in the partitioning, and also to the frequency discrimination interval. Related, that is: ; This weighting formula also illustrates that when using the same pilot resources (with consistent SNR across different partitions), the symbol spacing... The larger the value, the higher the reliability of the estimated frequency offset, but the corresponding estimation range... The smaller the value, the better. This application comprehensively utilizes the accuracy of estimation results under various divisions, further improves the reliability of the estimation through weighted merging, and also expands the frequency offset estimation range through period extension. It can effectively cope with the characteristics of rapid frequency offset changes and low signal-to-noise ratio of low-Earth orbit satellite systems.
[0061] After obtaining the target frequency offset estimate of the received signal, the terminal can perform subsequent signal processing, such as frequency offset compensation, and then execute subsequent communication processes to achieve reliable and high-quality communication.
[0062] According to the frequency offset estimation method of this application embodiment, at least two different pilot sequence divisions are performed based on the received signal to obtain at least two division data corresponding to each pilot sequence division; then, for each pilot sequence division, an initial frequency offset estimate is determined based on each division data; further, periodic extension is performed on each initial frequency offset estimate to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division; and an extended frequency offset estimate is determined from each extended frequency offset estimate corresponding to each pilot sequence division to obtain an optimal extended frequency offset estimate group; thus, the target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group. Therefore, this application employs a strategy of multiple pilot sequence divisions for frequency offset estimation. Since different pilot sequence divisions have different estimation ranges and accuracies, both estimation range and accuracy can be considered during the initial frequency offset estimation. Furthermore, periodic extension of the initial frequency offset estimate leverages the different estimation ranges under different pilot sequence divisions, effectively expanding the final frequency offset estimation range. Moreover, weighted merging of the frequency offset estimation results from different pilot sequence divisions effectively improves the estimation accuracy of time-domain correlation techniques, resulting in higher final frequency offset estimation accuracy. This achieves a dual improvement in estimation accuracy and estimation range.
[0063] In one embodiment, taking the Cell-Specific Reference Signal (CRS) pilot of Long Term Evolution (LTE) as an example, the CRS pilot is divided according to the symbol spacing, divided three times, with symbol spacings of {3, 4, 7}; its frequency offset estimation ranges are {[-2500, 2500], [-1875, 1875], [-1071, 1071]} (unit: Hertz). By periodically extending the frequency offset estimation value, the overall frequency offset estimation range can be extended to [-7500, 7500] (unit: Hertz).
[0064] In one embodiment, at least two different pilot sequence divisions are performed based on the received signal to obtain at least two division data corresponding to each pilot sequence division, including: Determine the time-domain least-squares LS channel estimate of the pilot sequence in the received signal; The time-domain LS channel estimate is divided into at least two different pilot sequences, and at least two partition data corresponding to each pilot sequence partition are obtained.
[0065] In addition, the time-domain LS channel estimate is divided into at least two distinct pilot sequence partitions, including: If the received signal is in single-carrier format, the time-domain LS channel estimate is divided into segments at least twice; wherein the number of segments in each division is different from the other divisions and the number of segments in different divisions are coprime numbers. If the received signal is in multi-carrier format, the time-domain LS channel estimate is divided at least twice according to different symbol intervals; wherein the symbol intervals of different divisions are coprime numbers.
[0066] It should be noted that since the downlink signal from the satellite may be in single-carrier or multi-carrier format, the terminal can perform corresponding processing procedures for the received signal in different carrier formats, and finally complete the pilot sequence division of the received signal, obtaining at least two division data corresponding to each pilot sequence division.
[0067] Specifically, for a single-carrier received signal, the time-domain pilot sequence in the received signal (the position of the pilot sequence can be determined based on the timing estimate) can be divided by the pilot sequence stored locally at the terminal to obtain the time-domain LS channel estimate. This can be achieved using the following formula: ; in, In order to receive signals, This is a local pilot sequence. These are timed estimates.
[0068] If the magnitude of the local pilot sequence is 1, then division can be replaced by conjugate multiplication.
[0069] It should be noted that this application may assume that a timing estimate has been obtained. If not, the pilot sequence division and time-domain correlation value calculation can be performed based on different timing preset values, and the timing preset value with the largest correlation value energy can be selected as the timing estimate.
[0070] Secondly, the time-domain LS channel estimate is divided M times, with each division involving the number of pilot segments. ,and They are coprime numbers.
[0071] Figure 2 This is one of the scenario diagrams illustrating pilot sequence partitioning in the frequency offset estimation method provided in this application embodiment, such as... Figure 2 As shown, in this application, the time-domain LS channel estimate containing the pilot sequence can be divided twice: first into 3 segments of pilot data, and second into 5 segments of pilot data, while the data sequence is not processed for the time being.
[0072] For received signals in multi-carrier format, the frequency domain pilot sequence corresponding to each symbol in the received signal can be divided by the locally stored pilot sequence to obtain the frequency domain LS channel estimate. This can be achieved using the following formula: ; in, It is a frequency domain pilot sequence. This is a local pilot sequence.
[0073] Furthermore, the frequency-domain LS channel estimate can be converted into a time-domain LS channel estimate using the inverse fast Fourier transform (IFFT). Simultaneously, one or more effective path locations can be obtained based on the power delay profile (PDP) information, thus yielding the time-domain LS channel estimate at each effective path location. .
[0074] Furthermore, the time-domain LS channel estimate can be divided M times according to the symbol spacing, with the symbol spacing of each division being... ,and They are coprime numbers.
[0075] Figure 3 This is a second schematic diagram of the pilot sequence partitioning scenario in the frequency offset estimation method provided in this application embodiment, as shown below. Figure 3 As shown, this application can divide the time-domain LS channel estimate into three parts. The first part is divided at an interval of 4 symbols, resulting in two pairs of pilot data. The second part is divided at an interval of 3 symbols, resulting in one pair of pilot data. The third part is divided at an interval of 7 symbols, resulting in two pairs of pilot data.
[0076] Therefore, multiple pilot sequence divisions can be completed, and at least two division data corresponding to each pilot sequence division can be obtained (that is, each division can correspond to multiple pilot data segments or a corresponding number of pilot pairs).
[0077] This application divides the time-domain LS channel estimate into multiple pilot sequences. Since different pilot sequence divisions have different estimation ranges and accuracies, the estimation range and accuracy can be taken into account when performing preliminary frequency offset estimation, which helps to achieve a dual improvement in estimation accuracy and estimation range.
[0078] In one embodiment, for each pilot sequence partition, an initial frequency offset estimate is determined based on each partition data, including: For each partition of the pilot sequence, determine the time-domain correlation value for each partition of the data. Based on the correlation values in each time domain, the average frequency discrimination cross product value for each pilot sequence division is determined. The initial frequency offset estimate is calculated based on the average frequency discrimination cross product value of each pilot sequence division.
[0079] Specifically, for a single-carrier format received signal, the correlation summation value of each segment of pilot data in each division can be determined as the time-domain correlation value using the following formula. : ; in, For intra-segment pilot index, , .
[0080] Furthermore, for received signals in multi-carrier format, the time-domain LS channel estimate at the effective path position within a symbol can be obtained. By performing a summation, we obtain the correlation values in the time domain and the correlation values in the instantaneous domain. Specifically, this can be achieved using the following formula: ; in, , For symbol indexing.
[0081] Furthermore, the correlation values of adjacent segments / specified symbol spacing in each pilot sequence division can be multiplied by their conjugates and summed to obtain the average frequency discrimination cross product value of that pilot sequence division. The formula is as follows: ; in, express The conjugate transpose of n, where the value of n has the same sign as the corresponding value in the above formula.
[0082] Furthermore, due to the aforementioned frequency discrimination cross product value The phase information is ,in This is the estimated value of the frequency offset to be determined under the current partition. This is the time interval between two adjacent center points / specified symbol spacing. Therefore, the frequency offset estimate under the current segmentation is the initial frequency offset estimate. for: ; in, This represents the arctangent function, which aims to return the arctangent of y / x in radians.
[0083] This application determines an initial frequency offset estimate based on each pilot sequence division, allowing subsequent periodic extension based on this initial estimate. The optimal extended frequency offset estimates for each division are then weighted and combined to obtain the received signal's frequency offset estimate. Since different pilot sequence divisions have different estimation ranges and accuracies, both estimation range and accuracy can be considered during initial frequency offset estimation. Furthermore, periodic extension of the initial frequency offset estimate leverages the different estimation ranges under different pilot sequence divisions, effectively expanding the final frequency offset estimation range. Moreover, weighted merging of frequency offset estimation results from different pilot sequence divisions effectively improves the estimation accuracy of time-domain correlation techniques, resulting in higher final frequency offset estimation accuracy. This achieves a dual improvement in estimation accuracy and range.
[0084] In one embodiment, an extension frequency offset estimate is determined from each pilot sequence's corresponding extension frequency offset estimate to obtain an optimal extension frequency offset estimate set, including: For each pilot sequence division, select an extended frequency offset estimate and construct at least one combination of extended frequency offset estimates. Among the various combinations of extended frequency offset estimates, the combination of extended frequency offset estimates with the closest deviation from each other is determined as the target combination of extended frequency offset estimates.
[0085] Specifically, a combination of extended frequency offset estimates can be formed by selecting one extended frequency offset estimate from each pilot sequence division: ; in, , and for It can take any value.
[0086] Furthermore, by iterating through all combinations of extended frequency offset estimates, and searching for the combination of extended frequency offset estimates that deviates most from each other, the following formula can be optimized. The minimum combination of extended frequency offset estimates: ; ; Therefore, the optimal combination of extended frequency offset estimates can be obtained and determined as the target combination of extended frequency offset estimates. Each extended frequency offset estimate in the target combination is the optimal extended frequency offset estimate for the corresponding sub-pilot sequence.
[0087] Figure 4 This is a schematic diagram illustrating a scenario in the frequency offset estimation method provided in this application for determining the combination of target extended frequency offset estimates, as shown in the example. Figure 4 As shown, in one embodiment, this application performs two divisions: the first division into 3 segments, and the second division into 5 segments. Wherein, Figure 4 The solid arrows represent the frequency offset estimates from the two divisions, and the frequency offset estimates are periodically extended respectively. Figure 4 (The dashed arrow in the middle) indicates that the frequency offset values of the first segment and the second segment are closest. Therefore, these two values are selected as the final estimated values for each segment, i.e., the optimal extended frequency offset estimates, and thus the combination of target extended frequency offset estimates can be obtained.
[0088] After periodic extension of the frequency offset, this application uses the combination with the smallest deviation from the mean as the search index to find the final correct frequency offset estimate and avoid erroneous estimation.
[0089] Figure 5 This is a second schematic flowchart of the frequency offset estimation method provided in the embodiments of this application, as shown below. Figure 5 As shown, the frequency offset estimation method specifically includes: Calculate the time-domain LS channel estimate at the pilot position in the received signal, and divide the pilot sequence M times, with the number of segments or symbol spacing in each division being... And obtain the relevant estimated value for each segment or symbol. .
[0090] Furthermore, for each division, the relevant values of the spacing between adjacent segments or specified symbols are multiplied by their conjugates, and like terms are summed to obtain... .
[0091] Furthermore, the frequency offset estimate for each partition is obtained, i.e., the initial frequency offset estimate. And perform periodic extension to obtain .
[0092] Then, find the F with the highest clustering degree under different divisions, and the weighted merging is the final frequency offset estimate, which is also the target frequency offset estimate.
[0093] Since the spacing used in different partitions is a prime number, the length of their extension periods is different. In an ideal scenario, there is only one frequency offset value (expected value) that points to the same frequency offset position in different partitions.
[0094] Therefore, this application utilizes multiple frequency offset estimation results under different division principles, improves the estimation accuracy of time domain correlation technology through weighted merging, and solves the problem of limited frequency offset estimation range in existing technologies through periodic extension technology, so that existing protocols for ground stations can be directly extended to low-orbit satellites.
[0095] The frequency offset estimation device provided in this application is described below. The frequency offset estimation device described below can be referred to in correspondence with the frequency offset estimation method described above.
[0096] Furthermore, this application also provides a frequency offset estimation device.
[0097] The frequency offset estimation device includes: The partitioning module is used to perform at least two different pilot sequence partitions based on the received signal, and obtain at least two partition data corresponding to each pilot sequence partition; The first determining module is used to determine an initial frequency offset estimate based on each of the partitioned data for each pilot sequence partition. The extension module is used to perform periodic extension on each of the initial frequency offset estimates to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. The second determining module is used to determine one extended frequency offset estimate from each of the extended frequency offset estimates corresponding to each pilot sequence, so as to obtain the optimal extended frequency offset estimate group. The merging module is used to perform weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group to obtain the target frequency offset estimate of the received signal.
[0098] The frequency offset estimation device of this application performs at least two different pilot sequence divisions based on the received signal, obtaining at least two division data corresponding to each pilot sequence division; then, for each pilot sequence division, an initial frequency offset estimate is determined based on each division data; further, each initial frequency offset estimate is periodically extended to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division; and an extended frequency offset estimate is determined from each extended frequency offset estimate corresponding to each pilot sequence division to obtain an optimal extended frequency offset estimate set; thus, the target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate set. Therefore, this application employs a strategy of multiple pilot sequence divisions for frequency offset estimation. Since different pilot sequence divisions have different estimation ranges and accuracies, both estimation range and accuracy can be considered during the initial frequency offset estimation. Furthermore, periodic extension of the initial frequency offset estimate leverages the different estimation ranges under different pilot sequence divisions, effectively expanding the final frequency offset estimation range. Moreover, weighted merging of the frequency offset estimation results from different pilot sequence divisions effectively improves the estimation accuracy of time-domain correlation techniques, resulting in higher final frequency offset estimation accuracy. This achieves a dual improvement in estimation accuracy and estimation range.
[0099] In one embodiment, the partitioning module is specifically used for: Determine the time-domain LS channel estimate of the pilot sequence in the received signal; The time-domain LS channel estimate is divided into at least two different pilot sequences, and at least two partition data corresponding to each pilot sequence partition are obtained.
[0100] In one embodiment, the partitioning module is further configured to: If the received signal is in single-carrier format, the time-domain LS channel estimate is divided into segments at least twice; wherein the number of segments in each division is different from the other divisions and the number of segments in different divisions are coprime numbers. If the received signal is in a multi-carrier format, the time-domain LS channel estimate is divided at least twice according to different symbol intervals; wherein the symbol intervals of different divisions are coprime numbers.
[0101] In one embodiment, the first determining module is specifically used for: For each partition of the pilot sequence, determine the time-domain correlation value for each partition of the data. Based on the aforementioned time-domain correlation values, the average frequency discrimination cross product value for each pilot sequence division is determined. The initial frequency offset estimate is calculated based on the average frequency discrimination cross product value of each pilot sequence division.
[0102] In one embodiment, the second determining module is specifically used for: For each pilot sequence division, select an extended frequency offset estimate and construct at least one combination of extended frequency offset estimates. Among the various combinations of extended frequency offset estimates, the combination of extended frequency offset estimates with the closest mutual deviation is determined as the target combination of extended frequency offset estimates.
[0103] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device may include a processor 610, a communications interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communications interface 620, and the memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute the following method: performing at least two different pilot sequence divisions based on the received signal, and obtaining at least two division data corresponding to each pilot sequence division; For each pilot sequence division, an initial frequency offset estimate is determined based on the division data. For each initial frequency offset estimate, periodic extension is performed to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. From each pilot sequence, a corresponding extended frequency offset estimate is determined to obtain an optimal extended frequency offset estimate group. The target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group.
[0104] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or a portion 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 instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0105] In another aspect, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the methods provided in the above embodiments, such as including: performing at least two different pilot sequence divisions based on a received signal, and obtaining at least two division data corresponding to each pilot sequence division; For each pilot sequence division, an initial frequency offset estimate is determined based on the division data. For each initial frequency offset estimate, periodic extension is performed to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. From each pilot sequence, a corresponding extended frequency offset estimate is determined to obtain an optimal extended frequency offset estimate group. The target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group.
[0106] In another aspect, embodiments of this application also provide a computer program product, on which a computer program is stored. When the computer program is executed by a processor, it is implemented to perform the methods provided in the above embodiments, such as: performing at least two different pilot sequence divisions based on the received signal, and obtaining at least two division data corresponding to each pilot sequence division; For each pilot sequence division, an initial frequency offset estimate is determined based on the division data. For each initial frequency offset estimate, periodic extension is performed to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. From each pilot sequence, a corresponding extended frequency offset estimate is determined to obtain an optimal extended frequency offset estimate group. The target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group.
[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0108] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of software products. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0109] Finally, it should be noted that the above embodiments are only used to illustrate this application and are not intended to limit this application. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application.
Claims
1. A frequency offset estimation method, characterized in that, include: Based on the received signal, at least two different pilot sequence divisions are performed to obtain at least two division data corresponding to each pilot sequence division; For each pilot sequence division, an initial frequency offset estimate is determined based on the division data. For each initial frequency offset estimate, periodic extension is performed to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. From each pilot sequence, a corresponding extended frequency offset estimate is determined to obtain an optimal extended frequency offset estimate group. The target frequency offset estimate of the received signal is obtained by weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group.
2. The frequency offset estimation method according to claim 1, characterized in that, The process involves dividing the received signal into at least two different pilot sequence segments, obtaining at least two segments of data corresponding to each segment, including: Determine the time-domain least-squares LS channel estimate of the pilot sequence in the received signal; The time-domain LS channel estimate is divided into at least two different pilot sequences, and at least two partition data corresponding to each pilot sequence partition are obtained.
3. The frequency offset estimation method according to claim 2, characterized in that, The process of dividing the time-domain LS channel estimate into at least two distinct pilot sequence partitions includes: If the received signal is in single-carrier format, the time-domain LS channel estimate is divided into segments at least twice; wherein the number of segments in each division is different from the other divisions and the number of segments in different divisions are coprime numbers. If the received signal is in a multi-carrier format, the time-domain LS channel estimate is divided at least twice according to different symbol intervals; wherein the symbol intervals of different divisions are coprime numbers.
4. The frequency offset estimation method according to claim 1, characterized in that, When performing periodic extension for each initial frequency offset estimate, the number of left and right extensions for each initial frequency offset estimate is less than or equal to a preset threshold; wherein the preset threshold is determined based on the number of segments or the spacing between segments of the corresponding pilot sequence.
5. The frequency offset estimation method according to claim 1, characterized in that, The step of determining an extension frequency offset estimate from each of the corresponding extension frequency offset estimates for each pilot sequence to obtain the optimal extension frequency offset estimate set includes: For each pilot sequence division, select an extended frequency offset estimate and construct at least one combination of extended frequency offset estimates. Among the various combinations of extended frequency offset estimates, the combination of extended frequency offset estimates with the closest mutual deviation is determined as the target combination of extended frequency offset estimates.
6. The frequency offset estimation method according to claim 1, characterized in that, The step of determining an initial frequency offset estimate based on each partitioned pilot sequence for each partition includes: For each partition of the pilot sequence, determine the time-domain correlation value for each partition of the data. Based on the aforementioned time-domain correlation values, the average frequency discrimination cross product value for each pilot sequence division is determined. The initial frequency offset estimate is calculated based on the average frequency discrimination cross product value of each pilot sequence division.
7. A frequency offset estimation device, characterized in that, include: The partitioning module is used to perform at least two different pilot sequence partitions based on the received signal, and obtain at least two partition data corresponding to each pilot sequence partition; The first determining module is used to determine an initial frequency offset estimate based on each of the partitioned data for each pilot sequence partition. The extension module is used to perform periodic extension on each of the initial frequency offset estimates to obtain at least two extended frequency offset estimates corresponding to each pilot sequence division. The second determining module is used to determine one extended frequency offset estimate from each of the extended frequency offset estimates corresponding to each pilot sequence, so as to obtain the optimal extended frequency offset estimate group. The merging module is used to perform weighted merging of each extended frequency offset estimate in the optimal extended frequency offset estimate group to obtain the target frequency offset estimate of the received signal.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the frequency offset estimation method as described in any one of claims 1 to 6.
9. A storage medium, said storage medium being a non-transitory computer-readable storage medium, wherein a computer program is stored thereon, characterized in that, When the computer program is executed by the processor, it implements the frequency offset estimation method as described in any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the frequency offset estimation method according to any one of claims 1 to 6.