Tracking elimination method and device for direct current component in receiver, equipment and storage medium

Abstract

The invention provides a tracking elimination method and device for a direct current component in a receiver, equipment and a storage medium, and the method comprises the steps: obtaining system parameters related to a received signal; determining an initial direct current estimation strategy based on the frequency offset information in the system parameters and the characteristics of the specific training field; processing the specific training field by applying an initial direct current estimation strategy to obtain a direct current initial estimation value; for each data symbol, based on the frequency offset information and the characteristics of the data symbol, determining a corresponding direct current tracking strategy and calculating a direct current tracking value of the data symbol; taking the direct current initial estimation value as an iterative initial value, and performing iterative smoothing processing on the direct current tracking value corresponding to each data symbol to obtain a smooth direct current estimation value corresponding to each data symbol; and performing direct-current component offset on each data symbol by using each number of smooth direct-current estimated values so as to output a baseband signal after the direct-current component is eliminated. By adopting the method, the signal processing reliability and the overall performance of the receiver can be remarkably improved.

Description

Technical Field

[0001] This application relates to the field of signal processing, and more specifically, to a method, apparatus, device, and storage medium for tracking and eliminating DC components in a receiver. Background Technology

[0002] As Wireless Local Area Network (WLAN) technology has evolved from Wi-Fi 4 (802.11n) to Wi-Fi 7 (802.11be), technologies such as high-order modulation, ultra-high bandwidth, and multi-user multiple-input multiple-output (MU-MIMO) have been widely adopted to meet the demands for high-speed, low-latency communication. Analog devices in the receiver's RF link (such as amplifiers and mixers) exhibit non-ideal characteristics, easily generating DC (Direct Current) offset. This offset degrades the signal-to-noise ratio, interferes with Orthogonal Frequency Division Multiplexing (OFDM) signal processing, and leads to decreased demodulation performance, severely limiting the throughput and reliability of WLAN receivers.

[0003] In existing technologies, the commonly used DC component elimination scheme is the mean estimation method. Its core is to use the long training field (LTF) in the WLAN frame structure to calculate the arithmetic mean of the signal sampling points in the field as the DC estimate, and then subtract the mean from the subsequent received signal to achieve elimination. Because of its simple principle and small amount of calculation, it is widely used in medium and low speed receivers.

[0004] The core drawback of this technology is its inability to adapt to the time-varying characteristics of DC components: In real-world scenarios, DC offset will dynamically drift with device temperature and power supply fluctuations, while the mean estimation method only performs a one-time static estimation through the frame header training field, and subsequent data segments use fixed values, which easily leads to deviations between the estimated value and the actual DC component. DC elimination is incomplete and it is difficult to meet the high-performance requirements of next-generation WLAN receivers such as WIFI6 / 7. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a method, apparatus, device and storage medium for tracking and eliminating DC components in a receiver, which can significantly improve the signal processing reliability and overall performance of the receiver.

[0006] In a first aspect, embodiments of this application provide a method for tracking and eliminating DC components in a receiver, the method comprising: Acquire system parameters related to the received signal; Based on the frequency offset information in the system parameters and the characteristics of specific training fields, an initial DC estimation strategy is determined. The initial DC estimation strategy is applied to process the specific training field to obtain the initial DC estimate. In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, the corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated; Using the initial DC estimate as the initial value for iteration, the DC tracking value corresponding to each data symbol is iteratively smoothed to obtain the smoothed DC estimate corresponding to each data symbol. The DC component of each data symbol is canceled by using the smoothed DC estimate corresponding to each data symbol, so as to output the baseband signal after eliminating the DC component.

[0007] Optionally, determining the initial DC estimation strategy based on the frequency offset information in the system parameters and the features of a specific training field includes: Based on the frequency offset information and the features of the specific training field, compare it with a preset first threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the initial DC estimation strategy.

[0008] Optionally, the step of applying the initial DC estimation strategy to process the specific training field to obtain an initial DC estimate includes: When the initial DC estimation strategy is the frequency offset estimation method, the time domain signal of the specific training field is subjected to frequency offset compensation and accumulation operations to obtain a first accumulated value. The first accumulated value is multiplied by a first coefficient to obtain the initial DC estimation value. When the initial DC estimation strategy is the mean estimation method, the arithmetic mean of the time-domain signal of the specific training field is calculated to obtain the initial DC estimate.

[0009] Optionally, in the received data segment, for each data symbol, determining the corresponding DC tracking strategy and calculating the DC tracking value of the data symbol based on the frequency offset information and the characteristics of the data symbol includes: Based on the frequency offset information and the characteristics of the data symbol, a comparison is made with a preset second threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the DC tracking strategy for this data symbol. According to the DC tracking strategy, the time-domain signal of the data symbol is processed to calculate its DC tracking value.

[0010] Optionally, the step of using the initial DC estimate as the initial value for iteration and iteratively smoothing the DC tracking values ​​corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol includes: The initial DC estimate is used as the initial state of the iterative sequence; For the k-th data symbol, its DC tracking value is weighted and fused with the smoothed DC estimate of the (k-1)-th data symbol to obtain the smoothed DC estimate of the k-th data symbol.

[0011] Optionally, the step of using the smoothed DC estimate corresponding to each data symbol to cancel the DC component of each data symbol, so as to output a baseband signal after eliminating the DC component, includes: The corresponding smoothed DC estimate is subtracted from the time-domain signal of each data symbol for cancellation processing; The time-domain signals of all data symbols after cancellation are combined and output.

[0012] Optionally, the specific training field is the last long training field in the wireless LAN physical layer frame structure.

[0013] Secondly, embodiments of this application provide a tracking and cancellation device for DC components in a receiver, the device comprising: The system parameter acquisition module is used to acquire system parameters related to the received signal; The DC estimation strategy determination module is used to determine the initial DC estimation strategy based on the frequency offset information in the system parameters and the characteristics of a specific training field. The DC initial estimate determination module is used to process the specific training field by applying the initial DC estimation strategy to obtain the DC initial estimate. The DC tracking value determination module is used to determine the corresponding DC tracking strategy and calculate the DC tracking value of the data symbol for each data symbol in the received data segment, based on the frequency offset information and the characteristics of the data symbol. The smoothed DC estimate determination module is used to use the initial DC estimate as the initial value for iteration, and to iteratively smooth the DC tracking value corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol. The DC component cancellation module is used to cancel the DC component of each data symbol by using the smoothed DC estimate corresponding to each data symbol, so as to output the baseband signal after the DC component is eliminated.

[0014] Optionally, when the DC estimation strategy determination module determines the initial DC estimation strategy based on the frequency offset information in the system parameters and the features of a specific training field, it is specifically used for: Based on the frequency offset information and the features of the specific training field, compare it with a preset first threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the initial DC estimation strategy.

[0015] Optionally, when the DC initial estimate determination module processes the specific training field using the initial DC estimation strategy to obtain the DC initial estimate, it is specifically used for: When the initial DC estimation strategy is the frequency offset estimation method, the time domain signal of the specific training field is subjected to frequency offset compensation and accumulation operations to obtain a first accumulated value. The first accumulated value is multiplied by a first coefficient to obtain the initial DC estimation value. When the initial DC estimation strategy is the mean estimation method, the arithmetic mean of the time-domain signal of the specific training field is calculated to obtain the initial DC estimate.

[0016] Optionally, when the DC tracking value determination module is used to determine the corresponding DC tracking strategy and calculate the DC tracking value of each data symbol based on the frequency offset information and the characteristics of the data symbol in the received data segment, it is specifically used for: Based on the frequency offset information and the characteristics of the data symbol, a comparison is made with a preset second threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the DC tracking strategy for this data symbol. According to the DC tracking strategy, the time-domain signal of the data symbol is processed to calculate its DC tracking value.

[0017] Optionally, when the smoothed DC estimate determination module uses the initial DC estimate as the initial value for iteration to iteratively smooth the DC tracking values ​​corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol, it is specifically used for: The initial DC estimate is used as the initial state of the iterative sequence; For the k-th data symbol, its DC tracking value is weighted and fused with the smoothed DC estimate of the (k-1)-th data symbol to obtain the smoothed DC estimate of the k-th data symbol.

[0018] Optionally, when the DC component cancellation module is used to cancel the DC component of each data symbol using the smoothed DC estimate corresponding to each data symbol, so as to output a baseband signal after eliminating the DC component, it is specifically used for: The corresponding smoothed DC estimate is subtracted from the time-domain signal of each data symbol for cancellation processing; The time-domain signals of all data symbols after cancellation are combined and output.

[0019] Optionally, the specific training field is the last long training field in the wireless LAN physical layer frame structure.

[0020] Thirdly, embodiments of this application provide a computer device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the DC component tracking and elimination method in the receiver described in any of the optional embodiments of the first aspect above.

[0021] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the DC component tracking and elimination method in a receiver as described in any of the optional embodiments of the first aspect.

[0022] The technical solution provided in this application includes, but is not limited to, the following beneficial effects: Acquiring system parameters related to the received signal is a crucial step that provides comprehensive and essential data support for the entire DC component tracking and elimination process. The acquired system parameters cover key information such as frame structure characteristics, communication environment status, and algorithm configuration, ensuring that subsequent operations have a clear basis. The completeness and accuracy of these parameters prevent estimation and tracking errors caused by missing or biased data from the outset, laying a solid foundation for the reliable operation of the entire method.

[0023] Based on the frequency offset information in the system parameters and the characteristics of specific training fields, an initial DC estimation strategy is determined. This step selects the initial estimation strategy by combining the frequency offset information with the inherent characteristics of specific training fields, ensuring that the strategy is highly adapted to the actual communication scenario and signal characteristics, thus avoiding the limitations of a single strategy. This targeted strategy selection method allows the initial DC estimation to better reflect the actual situation, significantly improving the rationality and adaptability of the initial estimation, and providing a crucial guarantee for obtaining accurate initial DC values ​​subsequently.

[0024] The initial DC estimation strategy is applied to the specific training field to obtain an initial DC estimate. This step applies a highly adaptable initial DC estimation strategy to the specific training field, fully utilizing the stability and deterministic characteristics of the specific training field to ensure that the obtained initial DC estimate has high accuracy. A reliable initial DC value provides a high-quality starting benchmark for DC tracking in subsequent data segments, effectively reducing correction costs and error accumulation during subsequent tracking.

[0025] In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, a corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated. This step determines the tracking strategy and calculates the tracking value separately for each data symbol in the data segment, realizing dynamic, symbol-by-symbol tracking of the DC component. This refined processing method can respond promptly to the time-varying characteristics of the DC component, ensuring that the DC tracking value corresponding to each data symbol matches the actual situation, effectively solving the estimation deviation problem caused by DC drift, and improving the timeliness and targeting of DC tracking.

[0026] Using the initial DC estimate as the initial value for iteration, the DC tracking values ​​corresponding to each data symbol are iteratively smoothed to obtain smoothed DC estimates for each data symbol. This step, through iterative smoothing, integrates the initial DC estimate with the tracking values ​​of each data symbol, effectively reducing the interference of DC component time-domain fluctuations and noise on the estimation results. The smoothed DC estimate is more stable and reliable, avoiding the instantaneous errors that may exist with a single tracking value, and providing a high-quality basis for subsequent accurate DC elimination.

[0027] The DC component of each data symbol is canceled using a smoothed DC estimate corresponding to that symbol, resulting in a baseband signal with the DC component eliminated. This step uses a corresponding smoothed DC estimate for each data symbol to achieve accurate and thorough elimination of the DC component, ensuring that the output baseband signal is free from DC interference. A clean baseband signal guarantees the performance of subsequent demodulation and decoding processes, avoiding signal distortion and processing errors caused by DC components, and directly improving the signal processing quality of the receiver.

[0028] The six steps in this application are progressive and logically coherent, forming a complete DC component tracking and cancellation system. From acquiring basic parameters to selecting appropriate strategies, and then to accurate estimation, dynamic tracking, smoothing optimization, and complete cancellation, each step plays a crucial role, collaboratively ensuring the accuracy, timeliness, and stability of DC cancellation. Ultimately, through the orderly coordination of each step, the adverse effects of DC components on receiver performance are effectively resolved, significantly improving the receiver's signal processing reliability and overall performance.

[0029] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 A flowchart of a method for tracking and eliminating DC components in a receiver, as provided in Embodiment 1 of this application, is shown. Figure 2 A flowchart of an initial DC estimation strategy determination method provided in Embodiment 1 of this application is shown; Figure 3 A flowchart of a DC tracking value determination method provided in Embodiment 1 of this application is shown; Figure 4 A flowchart of a method for determining a smoothed DC estimate provided in Embodiment 1 of this application is shown; Figure 5 A flowchart of a method for determining the baseband signal after eliminating the DC component, provided in Embodiment 1 of this application, is shown. Figure 6 This illustration shows a schematic diagram of a non-HT frame format in WIFI4 provided in Embodiment 1 of this application; Figure 7 This illustration shows a schematic diagram of an HT frame format in WIFI4 provided in Embodiment 1 of this application; Figure 8 This illustration shows a schematic diagram of a VHT frame format in WIFI5 provided in Embodiment 1 of this application; Figure 9 This illustration shows a schematic diagram of a HE-SU frame format in WIFI6 provided in Embodiment 1 of this application; Figure 10 This illustration shows a schematic diagram of a HE-MU frame format in WIFI6 provided in Embodiment 1 of this application; Figure 11 This application illustrates an EHT-MU frame format in WIFI7 provided in Embodiment 1. Figure 12 This illustration shows a schematic diagram of the structure of a DC component tracking and elimination device in a receiver provided in Embodiment 2 of this application; Figure 13 A schematic diagram of the structure of a computer device provided in Embodiment 3 of this application is shown. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments 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, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0033] Example 1 To facilitate understanding of this application, the following is combined with... Figure 1 The flowchart illustrating a method for tracking and eliminating DC components in a receiver according to Embodiment 1 of this application provides a detailed description of Embodiment 1 of this application.

[0034] See Figure 1 As shown, Figure 1 A flowchart of a method for tracking and eliminating DC components in a receiver according to Embodiment 1 of this application is shown, wherein the method includes steps S101 to S106: S101: Acquire system parameters related to the received signal.

[0035] Specifically, the system parameters need to cover the core configuration information required for DC (Direct Current) tracking and cancellation, including the length N of the last LTF (Long Training Field) without GI (Guard Interval) in the frame structure, the length L of the data field without GI, the total number of symbols in the data segment P, and the frequency offset normalized by the receiver bandwidth. (If the system bandwidth is B and the system frequency offset is F, then) =F / B), and the threshold value of integer multiple frequency offset of subcarriers. (0≤) ≤1) (0≤) ≤1), DC filter coefficient α (0≤α<1). Wherein, , The parameters can be flexibly adjusted according to the actual environment of the receiver, while the remaining parameters need to be automatically identified and obtained based on the frame structure characteristics of the received signal.

[0036] S102: Based on the frequency offset information in the system parameters and the characteristics of specific training fields, determine the initial DC estimation strategy.

[0037] Specifically, the frequency offset information is the receiver's frequency offset f, and the specific training field is the last LTF (Long Training Field) in the WLAN (Wireless Local Area Network) frame structure, whose core feature is the field length N.

[0038] This field corresponds to different types in different WLAN standard devices: WIFI4 (Wireless Fidelity 4) corresponds to LLTF (Legacy Long Training Field) / HT-LTF (High Throughput-Long Training Field), WIFI5 (Wireless Fidelity 5) corresponds to VHT-LTF (Very High Throughput-Long Training Field), WIFI6 (Wireless Fidelity 6) corresponds to HE-LTF (High Efficiency-Long Training Field), and WIFI7 (Wireless Fidelity 7) corresponds to EHT-LTF (Extremely High Throughput-Long Training Field).

[0039] The receiver can automatically identify the current frame type and match the corresponding fields by examining the initial fields of the frame structure, and then parse the frame. When determining the strategy, N and... The fractional part of the absolute value of the product, then multiplied by the threshold value. Comparison: If the decimal part is not greater than Choose the frequency offset estimation method to obtain a more accurate initial value for DC; if the decimal part is greater than The mean method is chosen to avoid the impact of noise amplification factor on the estimation accuracy.

[0040] S103: Apply the initial DC estimation strategy to process the specific training field to obtain the initial DC estimate.

[0041] Specifically, if the strategy is frequency offset compensation estimation, the time-domain signal of the last LTF field needs to be frequency offset compensated and then accumulated. The accumulated value is then multiplied by the noise amplification factor (an empirically fixed value) of that field to obtain the initial DC value. If the strategy is the mean method, the arithmetic mean of the time-domain signal of the LTF field is directly calculated as the initial DC value. As a fixed training sequence, the LTF field usually provides relatively accurate DC estimation results, avoiding estimation distortion problems that occur when the frequency offset is an integer multiple of the subcarrier.

[0042] S104: In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, the corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated.

[0043] Specifically, the total number of symbols in the data segment is P, and each data symbol is sequentially indexed by k (1≤k≤P). The core characteristic of a data symbol is the length L of the data field excluding the guard interval (GI). The frequency offset information remains the receiver's frequency offset. The logic for selecting the tracking strategy is consistent with the initial DC estimation: calculating L and The fractional part of the absolute value of the product and the threshold value Compare and choose between the frequency offset estimation method or the mean method.

[0044] When calculating the tracking value, the frequency offset compensation method requires frequency offset compensation and accumulation of the time domain signal of the kth data field, and then multiplying it by the noise amplification factor of the data field (an empirically fixed value); the mean value method directly calculates the mean of the time domain signal of the data field, and finally obtains the DC tracking value of the kth data symbol, so as to realize the continuous monitoring of time-varying DC.

[0045] S105: Using the initial DC estimate as the initial value for iteration, the DC tracking value corresponding to each data symbol is iteratively smoothed to obtain the smoothed DC estimate corresponding to each data symbol.

[0046] Specifically, the initial value of the iteration is set to the initial value of DC obtained by estimating through the LTF field. Subsequently, for the k-th data symbol, the DC tracking value of the current data symbol is weighted and fused with the smoothed DC estimate of the (k-1)-th data symbol by the DC filtering coefficient α (0≤α<1) to obtain the smoothed DC estimate of the k-th data symbol.

[0047] The core purpose of this processing is to reduce the impact of DC time-domain fluctuations and noise. Even if the initial value has a large deviation, the correction mechanism in the subsequent tracking process can gradually correct it and ensure the estimation accuracy.

[0048] S106: Use the smoothed DC estimate corresponding to each data symbol to cancel the DC component of each data symbol, so as to output the baseband signal after eliminating the DC component.

[0049] Specifically, for the k-th data symbol, its original time-domain signal is subtracted from the corresponding smoothed DC estimate to cancel the DC component. Then, according to the receiving order of the data symbols (k from 1 to P), all the canceled signals are combined to form a complete baseband signal to be processed without DC influence.

[0050] The process handles delays without affecting real-time communication and can meet the requirements of high-throughput scenarios. The principle is that the current symbol resolution and DC estimation are performed synchronously, and the current estimated DC is used to compensate for the next symbol without affecting the resolution of the next symbol. This can effectively avoid the impact of DC on data segment demodulation and decoding, greatly improve the throughput performance of WLAN receivers, and is compatible with various WLAN standard devices from WIFI4 to WIFI7, making it highly practical.

[0051] In an optional implementation, see Figure 2 As shown, Figure 2 The flowchart illustrates a method for determining an initial DC estimation strategy according to Embodiment 1 of this application. The method for determining the initial DC estimation strategy based on the frequency offset information in the system parameters and the characteristics of a specific training field includes steps S201-S202: S201: Based on the frequency offset information and the features of the specific training field, compare it with a preset first threshold; Specifically, in Wi-Fi 4, Wi-Fi 5, Wi-Fi 6, and Wi-Fi 7 devices, the last LTF field in their frame format refers to LLTF / HT-LTF, VHT-LTF, HE-LTF, and EHT-LTF, respectively. This is determined by the product of the known frequency offset f and the length N of the last LTF, and the threshold value of an integer multiple of the subcarrier frequency offset. By comparing the results, we can obtain a method for estimating the initial value of DC.

[0052] S202: Based on the comparison results, select either the frequency offset estimation method or the mean estimation method as the initial DC estimation strategy.

[0053] Specifically, Indicates to Decimal operation, Indicates to Find the absolute value.

[0054] The rules for determining the comparison results and the corresponding methods for selection are as follows: like If the system frequency offset is not an integer multiple of the subcarrier, the noise amplification factor is very small. In this case, the frequency offset estimation method is selected to obtain a more accurate DC initial value.

[0055] like If the system frequency offset is determined to be an integer multiple of the subcarrier, the noise amplification factor will cause the result of the frequency offset estimation method to be inaccurate. Therefore, the mean estimation method is selected to ensure the reliability of the initial estimate.

[0056] In an optional implementation, applying the initial DC estimation strategy to the specific training field to obtain an initial DC estimate includes: When the initial DC estimation strategy is the frequency offset estimation method, the time domain signal of the specific training field is subjected to frequency offset compensation and accumulation operations to obtain a first accumulated value. The first accumulated value is multiplied by a first coefficient to obtain the initial DC estimation value. Specifically, if the frequency offset compensation method is used based on the threshold judgment result, the estimation steps for the initial value of DC are as follows: The frequency offset of the last LTF field in the frame structure is padded, and then the accumulated value is calculated. Let the time-domain signal of the last LTF field be... Then the accumulated value The calculation method is as follows:

[0057] Accumulated value The initial DC value is obtained by multiplying by the noise amplification factor of the last LTF field in the frame structure. The specific calculation method is as follows:

[0058] in, This is the noise amplification factor for the last LTF field in the frame structure.

[0059] When the initial DC estimation strategy is the mean estimation method, the arithmetic mean of the time-domain signal of the specific training field is calculated to obtain the initial DC estimate. Specifically, if the threshold judgment result is based on the mean method, then the initial value of DC is... for:

[0060] The purpose of this implementation plan is to determine whether the system frequency offset is an integer multiple of the subcarrier frequency offset (the judgment criterion is...). If the noise amplification factor is small, the DC estimation result will be inaccurate, and the mean method needs to be used to estimate the initial value of DC; otherwise, the noise amplification factor is considered to be very small, and the frequency offset method can be used to obtain a more accurate initial value of DC.

[0061] In an optional implementation, see Figure 3 As shown, Figure 3The flowchart illustrates a DC tracking value determination method provided in Embodiment 1 of this application. In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, a corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated, including steps S301-S303: S301: Based on the frequency offset information and the characteristics of the data symbol, compare it with a preset second threshold.

[0062] Specifically, after determining the initial value of DC, to prevent the impact of DC time-varying values ​​on the system, the DC value needs to be accurately tracked. Threshold comparison of data fields: based on known frequency offsets. and the length of the data field The product of the product and the threshold value of integer multiples of the subcarrier frequency offset Compare them.

[0063] S302: Based on the comparison results, select either the frequency offset estimation method or the mean estimation method as the DC tracking strategy for this data symbol.

[0064] Specifically, the comparison is as follows: like Then the frequency offset estimation method is used to find the initial value of DC.

[0065] like If so, the mean method is used to estimate the initial value of DC.

[0066] S303: According to the DC tracking strategy, process the time-domain signal of the data symbol and calculate its DC tracking value.

[0067] Specifically, if the frequency offset compensation method is used based on the threshold judgment result, the calculation steps for the DC tracking value in the data field are as follows: After frequency offset compensation of the data field, the accumulated value is calculated. Let the time-domain signal of the k-th data field be... Then the accumulated value of the k-th data field The calculation method is as follows:

[0068] Accumulate the value of the k-th data field. Multiplying by the noise amplification factor of the data segment yields the DC tracking value of the k-th data field. The specific calculation method is as follows:

[0069] in, This is the noise amplification factor for the data field.

[0070] If the threshold judgment result is obtained using the mean method, then the DC tracking value of the kth data point... for:

[0071] Similarly, the purpose of this implementation scheme is to determine whether the system frequency offset is an integer multiple of the subcarrier frequency offset (the determination is based on the data field length). With system frequency offset product If the noise amplification factor is small, the DC estimation result will be inaccurate, and the mean method should be used to estimate the DC tracking value of the k-th data field; otherwise, the noise amplification factor is considered to be very small, and the frequency offset method can be used to obtain a more accurate DC tracking value of the k-th data field.

[0072] In an optional implementation, see Figure 4 As shown, Figure 4 The flowchart illustrates a smoothed DC estimate determination method provided in Embodiment 1 of this application. The method involves using the initial DC estimate as the initial value for iteration, and iteratively smoothing the DC tracking values ​​corresponding to each data symbol to obtain a smoothed DC estimate for each data symbol. This includes steps S401-S402: S401: Use the initial DC estimate as the initial state of the iterative sequence.

[0073] S402: For the kth data symbol, its DC tracking value is weighted and fused with the smoothed DC estimate of the (k-1)th data symbol to obtain the smoothed DC estimate of the kth data symbol.

[0074] Specifically, the DC tracking value of the kth data field is filtered and smoothed to obtain the filtered and smoothed DC tracking value. The purpose of this step is to reduce the impact of DC time-domain fluctuations and noise. The specific calculation method is as follows:

[0075] in, This indicates the initial value of DC determined by the last LTF field. , The filtered and smoothed DC tracking value is obtained by filtering and smoothing the DC tracking value of the (k-1)th data field.

[0076] In an optional implementation, see Figure 5 As shown, Figure 5 The flowchart illustrates a method for determining a baseband signal after eliminating the DC component, as provided in Embodiment 1 of this application. The method involves cancelling the DC component of each data symbol using a smoothed DC estimate corresponding to that symbol, to output a baseband signal after eliminating the DC component. This includes steps S501-S502. S501: Subtract the corresponding smoothed DC estimate from the time-domain signal of each data symbol for cancellation processing.

[0077] Specifically, let the time-domain signal of the k-th data field be... Then the k-th data field after DC elimination is the time-domain signal. The calculation method is as follows:

[0078] S502: Combines and outputs the time-domain signals of all data symbols after cancellation processing.

[0079] Specifically, the total number of symbols in the data segment is P. According to the receiving order of the data symbols (k from 1 to P), all time-domain signals after DC elimination are combined in sequence to form a complete baseband signal without DC influence. This signal can be directly used in the subsequent signal processing flow of the receiver.

[0080] In an optional implementation, the specific training field is the last long training field in the wireless LAN physical layer frame structure.

[0081] Specifically, this field is a fixed training field in the WLAN frame structure. It can be used not only to estimate the system's signal-to-noise ratio and channel characteristics, but also to make full use of its stability and determinism to accurately estimate the time-varying DC component, and the estimation results are usually quite accurate.

[0082] In devices using different WLAN standards, there is a clear correspondence between the specific types of this particular training field. The receiver can automatically identify the current frame type and select the corresponding field (the identification principle is based on automatic identification through the preceding fields in the frame structure, followed by parsing). The specific correspondence is as follows: For WIFI4 devices: the corresponding LLTF / HT-LTF field (including WIFI4's non-HT and HT frame formats); for WIFI5 devices: the corresponding VHT-LTF field; for WIFI6 devices: the corresponding HE-LTF field (including HE-SU single-user frame format and HE-MU multi-user frame format); and for WIFI7 devices: the corresponding EHT-LTF field (EHT-MU multi-user frame format). The DC estimation result of this field can be promptly compensated into the first symbol of the data field, laying a solid foundation for subsequent data segment DC tracking.

[0083] More specifically, the meanings of the abbreviations in each mode frame structure are explained below: (1) Common fields for WIFI4 / WIFI5 / WIFI6 / WIFI7: L-STF: Legacy Short Training Field; L-LTF: Legacy Long Training Field; L-SIG: Legacy SIGNAL Field; Data: Data field; PE: Packet Extension field.

[0084] (2) WIFI4 (HT) specific fields: HT-SIG: HT SIGNAL, HT signaling field; HT-STF: HT Short Training Field; HT-LTF: HT Long Training Field.

[0085] (3) WIFI5 (VHT) specific fields: VHT-SIG-A: VHT SIGNAL A, VHT signaling field A; VHT-STF: VHT Short Training Field; VHT-LTF: VHT Long Training Field; VHT-SIG-B: VHT SIGNAL B, VHT signaling field B.

[0086] (4) WIFI6 (HE) specific fields: RL-SIG: Repeated Legacy SIGNAL, a field for regular repeating signaling; HE-SIG-A: HE SIGNAL A, HE signaling field A; HE-STF: HE Short Training Field; HE-LTF: HE Long Training Field; HE-SIG-B: HE SIGNAL B, HE signaling field B.

[0087] (5) WIFI7 (HE) specific fields: RL-SIG: Repeated Legacy SIGNAL, a field for regular repeating signaling; U-SIG: Universal SIGNAL, a shared signaling field; EHT-SIG: EHT SIGNAL, EHT signaling field; EHT-STF: EHT Short Training Field; EHT-LTF: EHT Long Training Field.

[0088] See Figure 6 As shown, Figure 6 The illustration shows a schematic diagram of a non-HT frame format in WIFI4 provided in Embodiment 1 of this application. The fields of this frame format are L-STF (Legacy Short Training Field), L-LTF (Legacy Long Training Field), L-SIG (Legacy Signal Field), Data, and PE (Packet Extension). This frame format contains only one LTF field (i.e., L-LTF). Therefore, the specific training field (the last long training field) mentioned in this application corresponds to L-LTF in this frame format.

[0089] See Figure 7 As shown, Figure 7 The illustration shows a schematic diagram of an HT frame format in WIFI4 provided in Embodiment 1 of this application. The fields of this frame format are, in order: L-STF (Standard Short Training Field), L-LTF (Standard Long Training Field), L-SIG (Standard Signal Field), HT-SIG (High Throughput Signal Field), HT-STF (High Throughput Short Training Field), HT-LTF (High Throughput Long Training Field), Data (Data Field), and PE (Packet Extension). This frame format contains multiple HT-LTF fields, and the specific training field (the last long training field) described in this application corresponds to the HT-LTF at the end of the sequence in this frame format.

[0090] See Figure 8 As shown, Figure 8The illustration shows a schematic diagram of a VHT frame format in WIFI5 provided in Embodiment 1 of this application. The fields of this frame format are, in order: L-STF (Conventional Short Training Field), L-LTF (Conventional Long Training Field), L-SIG (Conventional Signal Field), VHT-SIG-A (Very High Throughput Signal Field A), VHT-STF (Very High Throughput Short Training Field), VHT-LTF (Very High Throughput Long Training Field), VHT-SIG-B (Very High Throughput Signal Field B), Data (Data Field), and PE (Packet Extension). This frame format contains multiple VHT-LTF fields, and the specific training field (the last long training field) described in this application corresponds to the VHT-LTF at the end of the sequence in this frame format.

[0091] See Figure 9 As shown, Figure 9 The illustration shows a schematic diagram of a WIFI6 HE-SU frame format provided in Embodiment 1 of this application. The fields of this frame format are, in order: L-STF (Regular Short Training Field), L-LTF (Regular Long Training Field), L-SIG (Regular Signal Field), RL-SIG (Repeated Legacy Signal Field), HE-SIG-A (High Efficiency Signal Field A), HE-STF (High Efficiency Short Training Field), HE-LTF (High Efficiency Long Training Field), Data (Data Field), and PE (Packet Extension). This frame format contains multiple HE-LTF fields, and the specific training field (the last long training field) described in this application corresponds to the HE-LTF at the end of the sequence in this frame format.

[0092] See Figure 10 As shown, Figure 10The diagram illustrates a WIFI 6 HE-MU frame format provided in Embodiment 1 of this application. The fields of this frame format are, in order: L-STF (regular short training field), L-LTF (regular long training field), L-SIG (regular signal field), RL-SIG (repeated regular signal field), HE-SIG-A (high efficiency signal field A), HE-SIG-B (High Efficiency Signal Field B), HE-STF (high efficiency short training field), HE-LTF (high efficiency long training field), Data (data field), and PE (packet extension). This frame format contains multiple HE-LTF fields, and the specific training field (the last long training field) described in this application corresponds to the HE-LTF at the end of the sequence in this frame format.

[0093] See Figure 11 As shown, Figure 11 This application illustrates an EHT-MU frame format in WIFI7 provided in Embodiment 1. The fields of this frame format are, in order: L-STF (Standard Short Training Field), L-LTF (Standard Long Training Field), L-SIG (Standard Signal Field), RL-SIG (Repeated Standard Signal Field), U-SIG (Universal Signal Field), EHT-SIG (Extremely High Throughput Signal Field), EHT-STF (Extremely High Throughput Short Training Field), EHT-LTF (Extremely High Throughput Long Training Field), Data (Data Field), and PE (Packet Extension). This frame format contains multiple EHT-LTF fields, and the specific training field (the last long training field) described in this application corresponds to the EHT-LTF at the end of the sequence in this frame format.

[0094] Example 2 See Figure 12 As shown, Figure 12 The diagram shows a schematic of a DC component tracking and cancellation device in a receiver according to Embodiment 2 of this application, wherein the device includes: The system parameter acquisition module 1201 is used to acquire system parameters related to the received signal; The DC estimation strategy determination module 1202 is used to determine an initial DC estimation strategy based on the frequency offset information in the system parameters and the characteristics of a specific training field. The DC initial estimate determination module 1203 is used to process the specific training field by applying the initial DC estimation strategy to obtain the DC initial estimate. The DC tracking value determination module 1204 is used to determine the corresponding DC tracking strategy and calculate the DC tracking value of the data symbol for each data symbol in the received data segment, based on the frequency offset information and the characteristics of the data symbol. The smoothed DC estimate determination module 1205 is used to use the initial DC estimate as the initial value for iteration, and to perform iterative smoothing on the DC tracking value corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol. The DC component cancellation module 1206 is used to cancel the DC component of each data symbol by using the smoothed DC estimate corresponding to each data symbol, so as to output the baseband signal after the DC component is cancelled.

[0095] In an optional implementation, the DC estimation strategy determination module, when determining the initial DC estimation strategy based on the frequency offset information in the system parameters and the features of a specific training field, specifically performs the following: Based on the frequency offset information and the features of the specific training field, compare it with a preset first threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the initial DC estimation strategy.

[0096] In an optional implementation, the DC initial estimate determination module, when processing the specific training field by applying the initial DC estimation strategy to obtain the DC initial estimate, specifically performs the following: When the initial DC estimation strategy is the frequency offset estimation method, the time domain signal of the specific training field is subjected to frequency offset compensation and accumulation operations to obtain a first accumulated value. The first accumulated value is multiplied by a first coefficient to obtain the initial DC estimation value. When the initial DC estimation strategy is the mean estimation method, the arithmetic mean of the time-domain signal of the specific training field is calculated to obtain the initial DC estimate.

[0097] In an optional implementation, the DC tracking value determination module, when used in the received data segment to determine the corresponding DC tracking strategy and calculate the DC tracking value of each data symbol based on the frequency offset information and the characteristics of the data symbol, specifically performs the following: Based on the frequency offset information and the characteristics of the data symbol, a comparison is made with a preset second threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the DC tracking strategy for this data symbol. According to the DC tracking strategy, the time-domain signal of the data symbol is processed to calculate its DC tracking value.

[0098] In an optional implementation, the smoothed DC estimate determination module, when using the initial DC estimate as the initial value for iteration to iteratively smooth the DC tracking values ​​corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol, specifically performs the following: The initial DC estimate is used as the initial state of the iterative sequence; For the k-th data symbol, its DC tracking value is weighted and fused with the smoothed DC estimate of the (k-1)-th data symbol to obtain the smoothed DC estimate of the k-th data symbol.

[0099] In an optional implementation, the DC component cancellation module, when used to cancel the DC component of each data symbol using the smoothed DC estimate corresponding to each data symbol, and outputting a baseband signal after DC component cancellation, is specifically used for: The corresponding smoothed DC estimate is subtracted from the time-domain signal of each data symbol for cancellation processing; The time-domain signals of all data symbols after cancellation are combined and output.

[0100] In an optional implementation, the specific training field is the last long training field in the wireless LAN physical layer frame structure.

[0101] In an optional implementation, the specific training field is the last long training field in the wireless LAN physical layer frame structure.

[0102] Example 3 Based on the same application concept, see [link / reference] Figure 13 As shown, Figure 13 This illustration shows a structural schematic diagram of a computer device provided in Embodiment 3 of this application, wherein, as shown... Figure 13 As shown, the computer device 1300 provided in Embodiment 3 of this application includes: The computer device 1300 includes a processor 1301, a memory 1302, and a bus 1303. The memory 1302 stores machine-readable instructions executable by the processor 1301. When the computer device 1300 is running, the processor 1301 and the memory 1302 communicate via the bus 1303. When the machine-readable instructions are executed by the processor 1301, they perform the steps of the DC component tracking and elimination method in the receiver shown in Embodiment 1 above.

[0103] Example 4 Based on the same concept, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the DC component tracking and elimination method in the receiver described in any of the above embodiments.

[0104] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0105] The computer program product for tracking and eliminating DC components in a receiver provided in this application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0106] The DC component tracking and elimination device in the receiver provided in this application embodiment can be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this application embodiment are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0107] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0108] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0110] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they 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 the prior art, 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.

[0111] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0112] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for tracking and eliminating DC components in a receiver, characterized in that, The method includes: Acquire system parameters related to the received signal; Based on the frequency offset information in the system parameters and the characteristics of specific training fields, an initial DC estimation strategy is determined. The initial DC estimation strategy is applied to process the specific training field to obtain the initial DC estimate. In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, the corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated; Using the initial DC estimate as the initial value for iteration, the DC tracking value corresponding to each data symbol is iteratively smoothed to obtain the smoothed DC estimate corresponding to each data symbol. The DC component of each data symbol is canceled by using the smoothed DC estimate corresponding to each data symbol, so as to output the baseband signal after eliminating the DC component.

2. The method according to claim 1, characterized in that, The initial DC estimation strategy is determined based on the frequency offset information in the system parameters and the features of specific training fields, including: Based on the frequency offset information and the features of the specific training field, a comparison is made with a preset first threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the initial DC estimation strategy.

3. The method according to claim 2, characterized in that, The process of applying the initial DC estimation strategy to the specific training field to obtain the initial DC estimate includes: When the initial DC estimation strategy is the frequency offset estimation method, the time domain signal of the specific training field is subjected to frequency offset compensation and accumulation operations to obtain a first accumulated value. The first accumulated value is multiplied by a first coefficient to obtain the initial DC estimation value. When the initial DC estimation strategy is the mean estimation method, the arithmetic mean of the time-domain signal of the specific training field is calculated to obtain the initial DC estimate.

4. The method according to claim 1, characterized in that, In the received data segment, for each data symbol, based on the frequency offset information and the characteristics of the data symbol, the corresponding DC tracking strategy is determined and the DC tracking value of the data symbol is calculated, including: Based on the frequency offset information and the characteristics of the data symbol, a comparison is made with a preset second threshold; Based on the comparison results, either the frequency offset estimation method or the mean estimation method is selected as the DC tracking strategy for this data symbol. According to the DC tracking strategy, the time-domain signal of the data symbol is processed to calculate its DC tracking value.

5. The method according to claim 1, characterized in that, The step of using the initial DC estimate as the initial value for iteration and iteratively smoothing the DC tracking values ​​corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol includes: The initial DC estimate is used as the initial state of the iterative sequence; For the k-th data symbol, its DC tracking value is weighted and fused with the smoothed DC estimate of the (k-1)-th data symbol to obtain the smoothed DC estimate of the k-th data symbol.

6. The method according to claim 1, characterized in that, The step of using the smoothed DC estimate corresponding to each data symbol to cancel the DC component of each data symbol, so as to output a baseband signal after eliminating the DC component, includes: The corresponding smoothed DC estimate is subtracted from the time-domain signal of each data symbol for cancellation processing; The time-domain signals of all data symbols after cancellation are combined and output.

7. The method according to claim 1, characterized in that, The specific training field is the last long training field in the physical layer frame structure of the wireless local area network.

8. A tracking and cancellation device for DC components in a receiver, characterized in that, The device includes: The system parameter acquisition module is used to acquire system parameters related to the received signal; The DC estimation strategy determination module is used to determine the initial DC estimation strategy based on the frequency offset information in the system parameters and the characteristics of a specific training field. The DC initial estimate determination module is used to process the specific training field by applying the initial DC estimation strategy to obtain the DC initial estimate. The DC tracking value determination module is used to determine the corresponding DC tracking strategy and calculate the DC tracking value of the data symbol for each data symbol in the received data segment, based on the frequency offset information and the characteristics of the data symbol. The smoothed DC estimate determination module is used to use the initial DC estimate as the initial value for iteration, and to iteratively smooth the DC tracking value corresponding to each data symbol to obtain the smoothed DC estimate corresponding to each data symbol. The DC component cancellation module is used to cancel the DC component of each data symbol by using the smoothed DC estimate corresponding to each data symbol, so as to output the baseband signal after the DC component is eliminated.

9. A computer device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the tracking and cancellation method for the DC component in the receiver as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the tracking and elimination method for the DC component in the receiver as described in any one of claims 1 to 7.

Images