Wireless communication signal processing method and device, electronic equipment, storage medium and computer product

Abstract

The invention relates to the technical field of communication, and provides a wireless communication signal processing method and device, electronic equipment, a storage medium and a computer product, and the method comprises the steps: determining a target nonlinear function based on a processing instruction of a to-be-processed wireless communication signal; determining an input value of the target nonlinear function based on the processing instruction; mapping the input value to an integer according to the linearity type of the segment of the parabola-like interval where the input value is located to obtain mapping data; extracting a first preset number of effective bits from the mapping data from a high bit to a low bit, and indexing according to the bit position and the bit value of each effective bit to obtain a first index value; determining a function result of the target nonlinear function according to the first index value; and performing data smoothing processing based on the function result to obtain a signal processing result. The signal processing efficiency of the wireless communication equipment can be improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a wireless communication signal processing method, device, electronic device, storage medium and computer product. Background Art

[0002] Long Term Evolution (LTE) / New Radio (NR) is a very important international standard in the field of wireless communication. The wireless communication signal transceiver algorithm under this standard is widely used in various communication devices. In order to meet the requirements of the signal processing process of LTE / NR wireless communication on the power consumption and complexity of the equipment, the transceiver algorithm needs to reduce the complexity and power consumption as much as possible while ensuring the performance. This requires that the algorithm should be implemented as much as possible with low-complexity algorithms or implementation methods during design, so as to ensure the simplicity of hardware implementation. Nonlinear functions are widely used in wireless communication systems, especially in the receiving end algorithms of LTE / NR. For example: trigonometric functions such as cos / sin need to be performed when compensating for frequency offset; atan2 function is needed when estimating frequency offset; Doppler spread estimation needs to be based on Bessel inverse function implementation; time domain / frequency domain correlation coefficient calculation needs to be based on Bessel / Sinc function implementation, etc.

[0003] However, it is very difficult to accurately solve the above nonlinear function. Directly using conventional mathematical methods to solve it will consume huge time and power consumption costs, thereby reducing the signal processing efficiency of wireless communication devices. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the related art. To this end, the present application proposes a wireless communication signal processing method, device, electronic device, storage medium and computer product to solve the problem that the accurate solution of the current nonlinear function consumes huge time and power consumption costs, so as to improve the signal processing efficiency of the wireless communication device.

[0005] According to the first aspect of the present application, a wireless communication signal processing method includes: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; determining an input value of the target nonlinear function based on the processing instructions; Mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data; Extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value; Determine a function result of the target nonlinear function according to the first index value; Data smoothing processing is performed based on the function result to obtain a signal processing result.

[0006] According to an embodiment of the present application, determining a function result of the target nonlinear function according to the first index value includes: Indexing the offset table according to the first index value to obtain offset information; If the offset information passes the verification, determining a target value based on the first index value and the offset information; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

[0007] According to an embodiment of the present application, the offset information includes a first offset and a second offset; after the offset table is indexed according to the first index value to obtain the offset information, it also includes: Comparing the first offset in the offset information with the second offset; If the first offset is the same as the second offset, determining that the offset information passes verification; If the first offset is different from the second offset, it is determined that the offset information fails verification.

[0008] According to one embodiment of the present application, after determining that the offset information fails the verification, the method further includes: Re-extracting a second preset number of valid bits after the first preset number of valid bits from the mapping data, and performing indexing according to the bit value of each valid bit to obtain a second index value; Determine a target value based on the first index value, the offset information and the second index value; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

[0009] According to an embodiment of the present application, determining a target value based on the first index value, the offset information, and the second index value includes: The first index value, the offset information, and the second index value are added to obtain a target value.

[0010] According to an embodiment of the present application, performing data smoothing based on the function result to obtain a signal processing result includes: Data interpolation or data fitting is performed based on the function result to obtain a signal processing result.

[0011] According to the second aspect of the present application, a wireless communication signal processing device includes: A first determination module, configured to determine a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; A second determination module, configured to determine an input value of the target nonlinear function based on the processing instruction; A mapping module, used for mapping the input value to an integer according to the linearity type of the parabola-like interval segment where the input value is located, to obtain mapping data; An indexing module, configured to extract a first preset number of valid bits from the mapping data from high bits to low bits, and perform indexing according to the bit position and bit value of each valid bit to obtain a first index value; A third determination module, configured to determine a function result of the target nonlinear function according to the first index value; The processing module is used to perform data smoothing processing based on the function result to obtain a signal processing result.

[0012] According to an electronic device of an embodiment of the third aspect of the present application, the electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the wireless communication signal processing method described in any one of the above methods is implemented.

[0013] According to the storage medium of the fourth aspect embodiment of the present application, the storage medium is a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements any one of the wireless communication signal processing methods described above.

[0014] A computer program product according to an embodiment of the fifth aspect of the present application includes a computer program, which, when executed by a processor, implements any one of the wireless communication signal processing methods described above.

[0015] The above one or more technical solutions in the embodiments of the present application have at least the following technical effects: After determining the target nonlinear function based on the processing instruction of the wireless communication signal to be processed and determining the input value of the target nonlinear function based on the processing instruction, the input value is mapped to an integer according to the linearity type of the parabola-like interval segmentation where the input value is located, to obtain mapping data, and then extracting a first preset number of valid bits from the mapping data from high to low, indexing according to the bit position and bit value of each valid bit, to obtain a first index value, so that the function result of the target nonlinear function can be determined according to the first index value, and finally data smoothing processing is performed based on the function result to obtain a signal processing result. By dividing the nonlinear function into interval segments according to the parabola-like trend and mapping the input value to an integer according to the linearity type of the interval segmentation, the high-order bit can be selected as the table lookup index to realize non-uniform segmentation, without storing segmentation information, and without comparing with the start and end points of each segment, the complexity and storage amount of the non-uniform segmentation algorithm are greatly reduced, and the signal processing result is obtained by smoothing the data according to the function result, which can ensure that the number of segments is close to the ideal non-uniform segmentation method under the premise of certain accuracy requirements, so that the signal processing efficiency of the wireless communication device can be improved.

[0016] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flowchart of a wireless communication signal processing method provided in an embodiment of the present application.

[0019] Figure 2 It is a schematic diagram of the overall flow of the wireless communication signal processing method provided in an embodiment of the present application.

[0020] Figure 3 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0021] The following is a further detailed description of the implementation of the present application in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but cannot be used to limit the scope of the present application.

[0022] In the description of the embodiments of the present application, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the embodiments of the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0023] In the description of the embodiments of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0024] In the embodiments of the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0025] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0026] The present application proposes a wireless communication signal processing method, device, electronic device, storage medium and computer product.

[0027] Figure 1 is a flow chart of a wireless communication signal processing method provided in an embodiment of the present application, such as Figure 1 As shown, the wireless communication signal processing method includes: Step 110: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed.

[0028] Step 120 : determining an input value of a target nonlinear function based on the processing instruction.

[0029] Step 130 , mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data.

[0030] Step 140 , extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value.

[0031] Step 150: Determine a function result of the target nonlinear function according to the first index value.

[0032] Step 160: Perform data smoothing processing based on the function result to obtain a signal processing result.

[0033] It should be noted that the execution subject of the wireless communication signal processing method provided in the embodiment of the present application may be a computer device including a fixed-point processor or a fixed-point digital signal processor (DSP), and the computer device may be, for example, a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a receiver, a netbook or a personal digital assistant (PDA), etc., which can be used for communication. It should be noted that the data required to be obtained in this application are all obtained through formal channels after authorization by relevant users.

[0034] A wireless communication signal processing device may be provided in or connected to the computer device of the present application, thereby controlling the wireless communication signal processing device to execute the wireless communication signal processing method of the present application.

[0035] It should be noted that nonlinear functions are opposite to linear functions (i.e., linear functions). Their graphs are not straight lines, but present various complex shapes. Such functions include basic elementary functions such as exponential functions, power functions, logarithmic functions, polynomial functions, and composite functions composed of them.

[0036] The nonlinear function targeted by the present application can be composed of a combination of curves showing parabolic characteristics in multiple intervals, that is, one side of the interval has better linearity and the other side has worse linearity. For example: in the cos / sin function [0, ] can be divided into 4 or 2 segments, each of which presents a parabola-like characteristic. For example, the Bessel / Bessel inverse and Sinc functions, the area between their zero crossings can be regarded as a parabola-like shape.

[0037] Specifically, the wireless communication signal processing method of the present application can be used to assist in processing wireless communication signals, and may include but is not limited to compensating for frequency offset, frequency offset estimation, Doppler spread estimation, and time domain / frequency domain correlation coefficient calculation.

[0038] Therefore, in the present application, a processing instruction for a wireless communication signal to be processed may be received, and the processing instruction may include but is not limited to compensating for frequency offset, estimating frequency offset, estimating Doppler spread, and calculating time domain / frequency domain correlation coefficients.

[0039] Furthermore, after obtaining the processing instruction of the wireless communication signal to be processed, the nonlinear function required for processing the wireless communication signal can be determined according to the data processing requirements corresponding to the processing instruction and used as the target nonlinear function. For example, when compensating for frequency deviation of the wireless communication signal, trigonometric functions such as cos / sin can be used as the target nonlinear function; when estimating frequency deviation of the wireless communication signal, the atan2 function can be used as the target nonlinear function; when estimating Doppler spread of the wireless communication signal, the Bessel inverse function can be used as the target nonlinear function; when calculating the time domain / frequency domain correlation coefficient of the wireless communication signal, the Bessel / Sinc function can be used as the target nonlinear function, and so on.

[0040] Furthermore, the input value of the target nonlinear function is determined according to the processing instruction. For example, when compensating for frequency deviation of a wireless communication signal, information of a complex sinusoidal wave signal that varies with time can be used as the input value of a trigonometric function such as cos / sin.

[0041] When frequency offset estimation is performed on a wireless communication signal, signal information related to the atan2 function in the wireless communication signal may be used as an input value of a target nonlinear function.

[0042] When Doppler spread estimation is performed on a wireless communication signal, signal information related to the Bessel inverse function in the wireless communication signal may be used as an input value of a target nonlinear function.

[0043] When calculating the time domain / frequency domain correlation coefficient for the wireless communication signal, signal information related to the Bessel / Sinc function in the wireless communication signal may be used as an input value of the target nonlinear function.

[0044] Furthermore, in the present application, segmentation can be performed according to the parabolic characteristics of the nonlinear function, thereby dividing the nonlinear function into one or more parabolic interval segments, such as [0, ] can be divided into 4 or 2 segments, each of which exhibits parabolic characteristics.

[0045] Furthermore, the parabola-like interval segment in which the input value is located in the target nonlinear function can be determined, and the linearity type of the parabola-like interval segment in which the input value is located can be further determined. Among them, the linearity type in this application can be divided into from good to bad (LinearMode=0) and from bad to good (LinearMode=1).

[0046] Among them, good linearity means that the first-order derivative of the function changes slowly with the change of the independent variable, and poor linearity means that the first-order derivative of the function changes quickly with the change of the independent variable.

[0047] Then, the input value can be mapped to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, thereby obtaining the mapping data. Specifically, if the linearity type is from good to bad (LinearMode=0), the integer after mapping is (i.e. mapping data) ; If the linearity type is from bad to good (LinearMode=1), the integer after mapping It can be expressed as: ; is an unsigned number, , (pre-stored coefficients), Represents an integer The number of bits.

[0048] Furthermore, we can Count the high bits of the binary representation of to the low bits, and get the index of the position of the first "1" , and starting from this position, continuously obtain the first preset number bits as valid bits.

[0049] Among them, the bit value of each valid bit is expressed as ,in ,in The bit value at the position where the most significant bit "1" is located.

[0050] Furthermore, indexing is performed according to the bit position and bit value of each valid bit, and the value obtained by the indexing is used as the first index value n1.

[0051] Specifically, the index can be performed using the following formula: .

[0052] With K=4, =2 is used as an example, as shown in Table 1 below: Table 1 Note: * indicates 0 or 1.

[0053] K and M (included With subsequent ) value for The interval segmentation has an impact, specifically: The larger the K value is, the more segments there are in the interval, and the more densely distributed the segments are in the area with poor linearity; The larger the M value is, the more segments there are in the interval and the more evenly the segments are distributed in the region.

[0054] The value of the number of bits K and the number of high-order bits M can control the uniformity of the non-uniform segmentation and achieve a limited degree of free adjustment.

[0055] Furthermore, a table lookup index offset calculation can be performed according to the first index value to obtain offset information, and the offset information is verified. If it is determined that the offset information passes the verification, a target value is determined based on the index value and the offset information; and then a table lookup is performed according to the target value to obtain a function result of the target nonlinear function. The process of performing a table lookup index offset calculation according to the index value can be implemented by existing technology, and this application does not specifically limit it.

[0056] Then, according to the function result, data smoothing processing is performed by data interpolation or data fitting to obtain the signal processing result. Then, according to the signal processing result, actual signal processing operations such as frequency offset compensation, frequency offset estimation, Doppler spread estimation and time domain / frequency domain correlation coefficient calculation can be performed.

[0057] According to the wireless communication signal processing method of the embodiment of the present application, after determining the target nonlinear function based on the processing instruction of the wireless communication signal to be processed and determining the input value of the target nonlinear function based on the processing instruction, the input value is mapped to an integer by segmenting the linearity type according to the parabola-like interval in which the input value is located to obtain mapping data, and then a first preset number of valid bits are extracted from the mapping data from high to low, and indexed according to the bit position and bit value of each valid bit to obtain a first index value, so that the function result of the target nonlinear function can be determined according to the first index value, and finally data smoothing processing is performed based on the function result to obtain a signal processing result. By dividing the nonlinear function into interval segments according to a parabolic trend and mapping the input value to an integer according to the linearity type of the interval segmentation, the high-order bit can be selected as a lookup table index to realize non-uniform segmentation. There is no need to store segmentation information or compare with the start and end points of each segment, which greatly reduces the complexity and storage volume of the non-uniform segmentation algorithm. Data smoothing is performed according to the function result to obtain the signal processing result. It can ensure that under the premise of certain accuracy requirements, the number of segments is close to the ideal non-uniform segmentation method, thereby improving the signal processing efficiency of wireless communication equipment.

[0058] Based on the above embodiment, determining a function result of the target nonlinear function according to the first index value includes: Index the offset table according to the first index value to obtain offset information; If the offset information passes the verification, determining the target value based on the first index value and the offset information; According to the target value, a table is looked up to obtain the function result of the target nonlinear function.

[0059] Specifically, after obtaining the first index value n1, the next index value n1+1 of the first index value can be further determined. and The value of the index offset table LUT_Ofs is checked to obtain the first offset LUT_Ofs[ ] and the second offset LUT_Ofs[ ] offset information.

[0060] Furthermore, LUT_Ofs[ ] and LUT_Ofs[ ] to verify the offset information.

[0061] If the offset information passes the verification, it is determined that there is no need to further refine the segmentation, so the target value can be determined based on the index value and the offset information. Specifically, the index value and the first offset LUT_Ofs[ ] are added as the target value n.

[0062] Furthermore, the next target value n+1 can be determined according to the target value n, and a table lookup is performed based on n and n+1 respectively to obtain the nonlinear function values ​​LUT_Fx[n] and LUT_Fx[n+1] as the function results of the target nonlinear function.

[0063] Specifically, the lookup table of the present application stores the index n corresponding to and Value. Among them, Therefore, we can find the left and right neighboring grid points and their results in the lookup table based on the index n calculated in the above steps: and , and The result of the function as a nonlinear function of the target.

[0064] Alternatively, the lookup table stores the corresponding coefficients of the linear function in each segment, such as the first-order linear function In and .

[0065] Therefore, the linear function coefficient can be found in the lookup table according to the index n and The result of the function as a nonlinear function of the target.

[0066] By verifying the offset information, the present application can reduce unnecessary segment refinement, thereby avoiding overly complex calculations, saving time and computing resources, and thus improving the signal processing efficiency of wireless communication devices.

[0067] Further, after the offset table is indexed according to the first index value to obtain the offset information, the method further includes: Compare the first offset and the second offset in the offset information; If the first offset is the same as the second offset, determining that the offset information passes verification; If the first offset is different from the second offset, it is determined that the offset information fails verification.

[0068] Specifically, after the offset table is indexed according to the first index value to obtain the offset information, the present application may also compare the first offset with the second offset in the offset information, thereby verifying the offset information.

[0069] More specifically, the second offset may be subtracted from the first offset, and LUT_Ofs[ ]-LUT_Ofs[ ] is equal to 0. If it is equal to 0, it is determined that the first offset is the same as the second offset. Further, if the first offset is the same as the second offset, it is determined that the offset information passes the verification.

[0070] If it is not equal to 0, it is determined that the first offset is different from the second offset. If the first offset is different from the second offset, it is determined that the offset information fails to pass the verification.

[0071] By verifying the offset information, the present application can reduce unnecessary segment refinement, thereby avoiding overly complex calculations, saving time and computing resources, and thus improving the signal processing efficiency of wireless communication devices.

[0072] Further, after determining that the offset information fails to pass the verification, the method further includes: Re-extracting a second preset number of valid bits after the first preset number of valid bits from the mapping data, and performing indexing according to the bit value of each valid bit to obtain a second index value; Determine a target value based on the first index value, the offset information and the second index value; According to the target value, a table is looked up to obtain the function result of the target nonlinear function.

[0073] Further, determining the target value based on the first index value, the offset information and the second index value includes: The first index value, the offset information, and the second index value are added together to obtain a target value.

[0074] Specifically, after determining that the offset information fails to pass the verification, the present application may also After the bit, continue to extract the second preset number bits as valid bits, and index according to the bit value of each valid bit to obtain a second index value , specifically, it can be indexed by the following formula: ; in, Respectively represent the bit value of each effective bit extracted.

[0075] Furthermore, the first index value, the offset information and the second index value are added together to obtain a target value. Specifically, the target value can be determined by the following formula: .

[0076] Furthermore, the next target value n+1 can be determined according to the target value n, and a table lookup is performed based on n and n+1 respectively to obtain the nonlinear function values ​​LUT_Fx[n] and LUT_Fx[n+1] as the function results of the target nonlinear function.

[0077] By refining the index value, the present application can reduce the error propagation caused by inaccurate initial offset information and improve the accuracy of the overall calculation. In addition, compared with complex recalculation, updating the index value through simple addition operation can obtain the target value faster and improve the calculation efficiency.

[0078] Based on the above embodiment, data smoothing is performed based on the function result to obtain a signal processing result, including: Data interpolation or data fitting is performed based on the function results to obtain signal processing results.

[0079] After obtaining the function result, this application can be implemented by interpolation or fitting, and different methods store different contents.

[0080] Specifically, according to With left grid The distance between and To interpolate, the process is as follows: ; ; What you get Finally, the result value of the signal processing result is obtained by removing the dimension. The result is a power of 2, so there is no need to perform division, only shifting.

[0081] The advantage of the interpolation method is that the error at the endpoints of each segment is 0, but the error in the middle of each segment is the largest, and the error is greater than the maximum error of the linear piecewise fitting (fitting based on the maximum error criterion).

[0082] Or, taking a first-order linear function as an example, execute , the data fitting of the function result can be performed to obtain the final fitting result and serve as the signal processing result.

[0083] Polynomial segmented fitting is to divide a nonlinear function into segments, and use a polynomial function to fit and approximate each segment. The approximation criterion can be the minimum average error or the minimum maximum error. The segmentation can be uniform or non-uniform, and the polynomial function can be a first-order linear function or a higher-order function. Different choices have different complexity, accuracy, and storage capacity.

[0084] Segmented fitting can be divided into two types: uniform segmentation and non-uniform segmentation. Uniform segmentation is to perform uniform segmentation in the entire interval of the function's independent variable, which is conducive to addressing, but the fitting errors between different segments will vary greatly; non-uniform segmentation is segmented according to the linearity of the nonlinear function at different positions. We know that the linearity of nonlinear functions at different positions varies greatly. Under the same error, areas with good linearity can be segmented more sparsely, and areas with poor linearity can be segmented more densely, which is conducive to reducing the number of segments under the same fitting error conditions. However, non-uniform segmentation is not conducive to addressing. Non-uniform segmentation requires storing the segmentation information of each segment, and the input variable It is necessary to compare with the start and end points of each segment to determine which segment it falls into, and then obtain the polynomial coefficients, and it is also necessary to store the location information of each segment. This makes the complexity and storage overhead of the non-uniform segmentation algorithm much higher than that of the uniform segmentation, and it cannot be used in high-timeliness scenarios.

[0085] Lookup table interpolation method converts nonlinear function At even intervals Record The value of For a given variable , first determine the two adjacent grid points, and then according to The distances to adjacent grid points The advantage of this method is that it does not require the monotonicity of the function, and the data range of the calculation process is completely controllable; its complexity is between linear (first-order function) fitting and high-order function fitting.

[0086] This application combines the processor addressing characteristics and uses input variables The high-order significant bits are used as non-uniform segmentation addressing addresses, which solves the problem of addressing difficulties in non-uniform segmentation schemes. At the same time, in view of the flexible change in linearity of non-linear curves, the first step is to perform non-uniform segmentation in the entire variable interval according to the degree of good linearity, and the second step is to perform further non-uniform segmentation for areas with extremely poor linearity. This solves the problem of the inflexibility of high-order significant bits as segmentation addressing indexes and greatly reduces storage overhead. The present application has a complexity and storage overhead approximately equal to that of the uniform segmentation algorithm, and the accuracy can approximate the accuracy of non-uniform segmentation under the same number of segments. And the present application is particularly suitable for vector processor calculations or hardware implementations.

[0087] The application adopts the partitioning strategy of non-uniform distribution + local uniform distribution, so that the application can adapt to various types of nonlinear functions with a wider range of adaptation. According to the accuracy requirements, the application can add denser uniform segmentation in a specific interval segment, so that under the same accuracy, the number of segments or storage size divided by the application is much smaller than the traditional technology. The application breaks down complex nonlinear operations into simple fixed-point operations and table lookup operations, completes the operation in a very short time, and gives results that meet the performance requirements of the relevant algorithms, which can improve the signal processing efficiency of wireless communication equipment.

[0088] Figure 2 is a schematic diagram of the overall flow of the wireless communication signal processing method provided in an embodiment of the present application, such as Figure 2 As shown, the present application determines the target nonlinear function based on the processing instruction of the wireless communication signal to be processed; and after the input value of the target nonlinear function is determined based on the processing instruction as the input variable x, the input variable x can be mapped to the specified bit width integer x_int according to the linearity. Furthermore, M1 valid bits on x_int can be extracted from high to low to obtain the initial indexes n1 and n1+1; then the index offset LUT_Ofs can be searched according to n1 and n1+1, and the final table lookup index values ​​n and n+1 can be calculated. It can further be determined that the searched LUT_Ofs[ ]-LUT_Ofs[ ] is not equal to 0. If so, continue to extract M2 bits n2 after M1 bits, and update the final table lookup index values ​​n and n+1 according to n2. If not, directly update the final table lookup index values ​​n1 and LUT_Ofs[ ] Determine the table index values ​​n and n+1. Therefore, the nonlinear function values ​​LUT_Fx[n] and LUT_Fx[n+1] can be obtained according to the table lookup of n and n+1, and the approximate value f(x) of the nonlinear function corresponding to x can be obtained by interpolation or linear fitting, and it is used as the output result.

[0089] In a specific embodiment, the present application can provide a zero-order Bessel function in the time domain autocorrelation coefficient calculation in the interval The simulation results inside.

[0090] Specifically, according to the above process, configure K=5, , The parameters are implemented by interpolation method, and the fitting error of each point is calculated. The formula is as follows: ; For scenarios used on fixed-point processors or hardware, the stored values ​​are: Using 8-bit bit width storage, the storage result is: LUT_X=[0,8,16,24,32,40,48,56,64,72,80,88,96,104,112,120,128,144,160,176,192,208,224,240,256]; Using 16-bit bit width storage, the storage result is: LUT_Fx=[32768,32722,32584,32355,32035,31626,31130,30549,29885,29140,28319,27425,26461,25431,24340,23192,21992,19455,16772,13985,11141,8284,5459,2712,82].

[0091] The index offset is stored in 4 bits, and the storage result is: LUT_Ofs=[0,0,0,0,0,0,0,0,0,0, 1,1,2,2,3,3,4,4,5,5,6,6,7,7,8].

[0092] In another specific embodiment, the present application can provide an inverse function of the zero-order Bessel function in Doppler spread estimation in the interval Simulation results of According to the curve characteristics of the inverse function of the zero-order Bessel function, it can be achieved in the entire The error in the interval is relatively balanced, so K=16 is configured. , , which is implemented using the interpolation method, and the fitting error is calculated for each point.

[0093] For scenarios used on fixed-point processors or hardware, the stored values ​​are: Using 16-bit storage, the storage result is: LUT_X=[0,8192,16384,20480, 24576,26624,28672,29696,30720,31232,31744,32000,32256,32384,32512,32576,32640,32672,32704,32720,32736,32744,32752,32756,32760,32762,32764,32765,32766,32767,32767,32768].

[0094] Using 16-bit storage width, the storage result is: LUT_Fx=[19700,16014,12461,10572,8471,7272,5887,5077,4129,3568,2908,2516,2052,1776,1450,1255,1025,887,724,627,512,443,362,314,256,222,181,157,128,111,90,0].

[0095] LUT_Ofs is always equal to 0 and does not need to be stored.

[0096] The wireless communication signal processing device provided in the present application is described below. The wireless communication signal processing device described below and the wireless communication signal processing method described above can be referenced to each other.

[0097] Furthermore, the present application also provides a wireless communication signal processing device.

[0098] The wireless communication signal processing device comprises: A first determination module, configured to determine a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; A second determination module, configured to determine an input value of the target nonlinear function based on the processing instruction; A mapping module, used for mapping the input value to an integer according to the linearity type of the parabola-like interval segment where the input value is located, to obtain mapping data; An indexing module, configured to extract a first preset number of valid bits from the mapping data from high bits to low bits, and perform indexing according to the bit position and bit value of each valid bit to obtain a first index value; A third determination module, configured to determine a function result of the target nonlinear function according to the first index value; The processing module is used to perform data smoothing processing based on the function result to obtain a signal processing result.

[0099] The wireless communication signal processing device of the present application determines the target nonlinear function based on the processing instruction of the wireless communication signal to be processed and determines the input value of the target nonlinear function based on the processing instruction, maps the input value to an integer according to the linearity type of the parabola-like interval segment where the input value is located, obtains mapping data, and then extracts a first preset number of valid bits from the mapping data from high to low, indexes according to the bit position and bit value of each valid bit, obtains a first index value, so that the function result of the target nonlinear function can be determined according to the first index value, and finally performs data smoothing processing based on the function result to obtain a signal processing result. By dividing the nonlinear function into interval segments according to the parabola-like trend and mapping the input value to an integer according to the linearity type of the interval segment, the high-order bit can be selected as the table lookup index to realize non-uniform segmentation, without storing segmentation information, and without comparing with the start and end points of each segment, which greatly reduces the complexity and storage of the non-uniform segmentation algorithm, and obtains the signal processing result by smoothing the data according to the function result, which can ensure that the number of segments is close to the ideal non-uniform segmentation method under the premise of certain accuracy requirements, so as to improve the signal processing efficiency of the wireless communication device.

[0100] In one embodiment, the third determination module is specifically configured to: Indexing the offset table according to the first index value to obtain offset information; If the offset information passes the verification, determining a target value based on the first index value and the offset information; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

[0101] In one embodiment, the third determining module is further configured to: Comparing the first offset in the offset information with the second offset; If the first offset is the same as the second offset, determining that the offset information passes verification; If the first offset is different from the second offset, it is determined that the offset information fails verification.

[0102] In one embodiment, the third determining module is further configured to: Re-extracting a second preset number of valid bits after the first preset number of valid bits from the mapping data, and performing indexing according to the bit value of each valid bit to obtain a second index value; Determine a target value based on the first index value, the offset information and the second index value; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

[0103] In one embodiment, the third determination module includes a computing unit, and the computing unit is used to: The first index value, the offset information, and the second index value are added to obtain a target value.

[0104] In one embodiment, the processing module is specifically used for: Data interpolation or data fitting is performed based on the function result to obtain a signal processing result.

[0105] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the following method: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; determining an input value of the target nonlinear function based on the processing instructions; Mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data; Extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value; Determine a function result of the target nonlinear function according to the first index value; Data smoothing processing is performed based on the function result to obtain a signal processing result.

[0106] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0107] In another aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method provided by each of the above embodiments is implemented, for example, including: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; determining an input value of the target nonlinear function based on the processing instructions; Mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data; Extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value; Determine a function result of the target nonlinear function according to the first index value; Data smoothing processing is performed based on the function result to obtain a signal processing result.

[0108] In another aspect, an embodiment of the present application further provides a computer program product having a computer program stored thereon, and when the computer program is executed by a processor, the method provided by each of the above embodiments is implemented, for example, including: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; determining an input value of the target nonlinear function based on the processing instructions; Mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data; Extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value; Determine a function result of the target nonlinear function according to the first index value; Data smoothing processing is performed based on the function result to obtain a signal processing result.

[0109] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0110] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0111] Finally, it should be noted that the above implementation modes are only used to illustrate the present application, rather than to limit the present application. Although the present application is described in detail with reference to the embodiments, a person skilled in the art should understand that various combinations, modifications or equivalent substitutions of the technical solutions of the present application do not depart from the spirit and scope of the technical solutions of the present application.

Claims

1. A wireless communication signal processing method, characterized in that: include: determining a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; determining an input value of the target nonlinear function based on the processing instructions; Mapping the input value to an integer according to the linearity type of the parabola-like interval segment in which the input value is located, to obtain mapping data; Extracting a first preset number of valid bits from the mapping data from high bits to low bits, and performing indexing according to the bit position and bit value of each valid bit to obtain a first index value; Determine a function result of the target nonlinear function according to the first index value; Data smoothing processing is performed based on the function result to obtain a signal processing result.

2. The wireless communication signal processing method according to claim 1, characterized in that: The determining the function result of the target nonlinear function according to the first index value includes: Indexing the offset table according to the first index value to obtain offset information; If the offset information passes the verification, determining a target value based on the first index value and the offset information; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

3. The wireless communication signal processing method according to claim 2, characterized in that: The offset information includes a first offset and a second offset; after the offset table is indexed according to the first index value to obtain the offset information, the method further includes: Comparing the first offset in the offset information with the second offset; If the first offset is the same as the second offset, determining that the offset information passes verification; If the first offset is different from the second offset, it is determined that the offset information fails verification.

4. The wireless communication signal processing method according to claim 3, characterized in that: After determining that the offset information fails to pass the verification, the method further includes: Re-extracting a second preset number of valid bits after the first preset number of valid bits from the mapping data, and performing indexing according to the bit value of each valid bit to obtain a second index value; Determine a target value based on the first index value, the offset information and the second index value; A table lookup is performed according to the target value to obtain a function result of the target nonlinear function.

5. The wireless communication signal processing method according to claim 4, characterized in that: The determining a target value based on the first index value, the offset information, and the second index value includes: The first index value, the offset information, and the second index value are added to obtain a target value.

6. The wireless communication signal processing method according to claim 1, characterized in that: The step of performing data smoothing based on the function result to obtain a signal processing result includes: Data interpolation or data fitting is performed based on the function result to obtain a signal processing result.

7. A wireless communication signal processing device, characterized in that: include: A first determination module, configured to determine a target nonlinear function based on a processing instruction of a wireless communication signal to be processed; A second determination module, configured to determine an input value of the target nonlinear function based on the processing instruction; A mapping module, used for mapping the input value to an integer according to the linearity type of the parabola-like interval segment where the input value is located, to obtain mapping data; An indexing module, configured to extract a first preset number of valid bits from the mapping data from high bits to low bits, and perform indexing according to the bit position and bit value of each valid bit to obtain a first index value; A third determination module, configured to determine a function result of the target nonlinear function according to the first index value; The processing module is used to perform data smoothing processing based on the function result to obtain a signal processing result.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the wireless communication signal processing method according to any one of claims 1 to 6 is implemented.

9. A storage medium, the storage medium being a non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that: When the computer program is executed by a processor, the wireless communication signal processing method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the wireless communication signal processing method according to any one of claims 1 to 6 is implemented.

Images