Baseband signal receiving and processing method, device and equipment based on channel weighting

Abstract

The invention relates to the technical field of communication, in particular to a baseband signal receiving and processing method, device and equipment based on channel weighting, and the method comprises the steps: obtaining frequency domain data of a baseband signal, carrying out the channel estimation of the frequency domain data through a least square method, and generating a least square method estimation result; based on a linear minimum mean square error method, filtering the estimation result of the least square method to obtain a final estimation result; based on the final estimation result, determining an equalization weight, and equalizing the frequency domain data through the equalization weight; measuring the balanced channel quality information; and demodulating and decoding based on the channel quality information. Therefore, the accuracy of channel estimation can be greatly improved, and meanwhile, the accuracy of baseband signal processing can be further improved by introducing the equalization weight to carry out equalization and measuring the channel quality information to carry out demodulation and decoding.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a baseband signal receiving and processing method, device and equipment based on channel weighting. Background Art

[0002] Orthogonal Frequency Division Multiplexing (OFDM) is a wireless communication technology that divides a high-frequency signal into multiple low-frequency signals and transmits these signals in parallel to improve transmission efficiency and anti-interference capabilities. It is commonly used in broadband wireless communication systems.

[0003] In OFDM-based wireless communication systems, the main processing process of receiving baseband signals generally includes channel estimation, equalization, demodulation, decoding, etc. Among them, the most common channel estimation method is the channel estimation based on the least squares method (LS), but the LS channel estimation is sensitive to noise at low signal-to-noise ratio, so it will amplify the noise.

[0004] In a complex network environment, neighboring cell interference, multipath, etc. can deteriorate the signal quality, thus affecting the receiving performance of the baseband receiver. When estimating the channel using LS, whether frequency domain FIR noise reduction or time domain windowing noise reduction is selected, the filter coefficient and window length should match the actual channel multipath, otherwise the channel signal will be distorted. Therefore, a more accurate channel estimation and baseband signal reception processing method is urgently needed. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a baseband signal receiving and processing method, device and equipment based on channel weighting to overcome the current problem of being unable to balance the complexity and accuracy in the reception and processing of baseband signals.

[0006] To achieve the above objectives, the present invention adopts the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a baseband signal receiving and processing method based on channel weighting, comprising:

[0008] Acquire frequency domain data of the baseband signal, and perform channel estimation on the frequency domain data by using the least squares method to generate a least squares estimation result of the frequency domain data;

[0009] Based on the linear minimum mean square error method, filtering the least squares estimation result to obtain a final estimation result;

[0010] Based on the final estimation result, determining an equalization weight, and equalizing the frequency domain data by using the equalization weight;

[0011] Measuring channel quality information after equalization;

[0012] Demodulation and decoding are performed based on the channel quality information.

[0013] Furthermore, in some embodiments of the present application, filtering the least squares estimation result based on the linear minimum mean square error method to obtain a final estimation result includes:

[0014] Generate filtering weights based on a preset signal-to-noise ratio and a multipath delay spread mean square error;

[0015] The least squares estimation result is filtered based on the filtering weights to obtain the final estimation result.

[0016] Further, in some embodiments of the present application, determining an equalization weight based on the final estimation result, and equalizing the frequency domain data by using the equalization weight includes:

[0017] Determine a covariance matrix of noise interference based on the least squares estimation result and the final estimation result;

[0018] Determining the equalization weight based on the covariance matrix and the final estimation result;

[0019] The frequency domain data is equalized based on the equalization weight.

[0020] Further, in some embodiments of the present application, the channel quality information includes a post-equalization signal-to-noise ratio and an equalization gain;

[0021] The post-equalization signal-to-noise ratio and the equalization equity are determined based on the equalization weight.

[0022] Further, in some embodiments of the present application, the demodulating and decoding based on the channel quality information includes:

[0023] Based on the equalized signal-to-noise ratio or the equalized gain, the equalized frequency data of different modulation orders are demodulated respectively to extract corresponding soft information.

[0024] Furthermore, in some embodiments of the present application, the demodulating and decoding based on the channel quality information further includes: decoding based on the soft information.

[0025] In a second aspect, an embodiment of the present application provides a baseband signal receiving and processing device based on channel weighting, characterized in that it includes:

[0026] A first channel estimation module, used for acquiring frequency domain data of a baseband signal, and performing channel estimation on the frequency domain data by a least square method to generate a least square method estimation result of the frequency domain data;

[0027] A second channel estimation module is used to filter the least squares estimation result based on a linear minimum mean square error method to obtain a final estimation result;

[0028] An equalization module, configured to determine an equalization weight based on the final estimation result, and equalize the frequency domain data by using the equalization weight;

[0029] A measurement module, used to measure the channel quality information after equalization;

[0030] The demodulation and decoding module is used to perform demodulation and decoding based on the channel quality information.

[0031] In a third aspect, an embodiment of the present application provides a baseband signal receiving and processing device based on channel weighting, characterized in that it includes a processor and a memory, and the processor is connected to the memory:

[0032] Wherein, the processor is used to call and execute the program stored in the memory;

[0033] The memory is used to store the program, and the program is at least used to execute the baseband signal receiving and processing method based on channel weighting as described above.

[0034] The present application relates to the field of communication technology, and specifically to a baseband signal receiving and processing method, device and equipment based on channel weighting, the method comprising obtaining frequency domain data of a baseband signal, and performing channel estimation on the frequency domain data by the least square method to generate a least square estimation result; filtering the least square estimation result based on the linear minimum mean square error method to obtain a final estimation result; determining equalization weights based on the final estimation result, and equalizing the frequency domain data by the equalization weights; measuring the channel quality information after equalization; and performing demodulation and decoding based on the channel quality information. In this way, the accuracy of channel estimation can be greatly improved, and the accuracy of processing baseband signals can be further improved by introducing equalization weights for equalization and measuring channel quality information for demodulation and decoding. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only 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.

[0036] Figure 1 It is a flow chart of a baseband signal receiving and processing method based on channel weighting provided in an embodiment of the present application;

[0037] Figure 2 is a comparison chart of baseband signal reception and processing method based on channel weighting provided by an embodiment of the present application and baseband reception performance of the prior art;

[0038] Figure 3 It is a measurement result diagram of channel quality information in the baseband signal receiving and processing method based on channel weighting provided in an embodiment of the present application;

[0039] Figure 4 It is a structural diagram of a baseband signal receiving and processing device based on channel weighting provided in an embodiment of the present application;

[0040] Figure 5 It is a structural diagram of a baseband signal receiving and processing device based on channel weighting provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0042] Method Example:

[0043] Figure 1 This is a flow chart of a baseband signal receiving and processing method based on channel weighting provided in an embodiment of the present application. Figure 1 , this embodiment may include the following steps:

[0044] S101. Initialization.

[0045] Specifically, the frequency domain data of the baseband signal is obtained, wherein the baseband signal receiving and processing method based on channel weighting provided in the embodiment of the present application can be applied to a variety of scenarios such as the 100MHz bandwidth scenario of the 5G system.

[0046] S102: Channel estimation.

[0047] Specifically, in the present application, channel estimation is divided into two parts. The first part is to perform channel estimation on the above-mentioned frequency domain data through the least squares method to generate the least squares estimation result of the frequency domain data; the second part is to filter the least squares estimation result based on the linear minimum mean square error method to obtain the final estimation result.

[0048] S103. Balance.

[0049] Specifically, in the present application, the frequency data is equalized by using the MMSE equalization method using the result of channel estimation, which includes determining the equalization weight based on the final estimation result, and then equalizing the frequency domain data by using the equalization weight.

[0050] S104: Channel quality measurement.

[0051] Specifically, after equalization is completed, the channel quality may be measured based on the equalized result to obtain the equalized channel quality information.

[0052] S105: Demodulation and soft information extraction.

[0053] S106: Decoding.

[0054] Specifically, after the channel quality information is obtained, demodulation and soft information extraction and decoding are performed based on the channel quality information.

[0055] The baseband signal receiving and processing method based on channel weighting provided by the present application first obtains the frequency domain data of the baseband signal, and performs channel estimation on the frequency domain data by the least square method to generate the least square estimation result; then, based on the linear minimum mean square error method, the least square estimation result is filtered to obtain the final estimation result; then, based on the final estimation result, the equalization weight is determined, and the frequency domain data is equalized by the equalization weight; the channel quality information after equalization is measured; finally, demodulation and decoding are performed based on the channel quality information. In this way, the accuracy of channel estimation can be greatly improved, and the accuracy of processing baseband signals can be further improved by introducing equalization weights for equalization and measuring channel quality information for demodulation and decoding.

[0056] Further, in some implementations of the present application, after obtaining the baseband frequency data Y, channel estimation is performed using the least squares method, and the specific formula is:

[0057]

[0058] in, represents the least squares estimation result, X dmrs is the training pilot sequence.

[0059] On this basis, the least squares estimation result obtained above is filtered based on the linear minimum mean square error (LMMSE) to obtain the final estimation result, which is as follows:

[0060]

[0061] in, is the final estimation result, N is the filtering weight, is the channel cross-correlation matrix, is the inverse of the channel autocorrelation matrix, and SNR is the signal-to-noise ratio. It should be noted that in this formula, in order to conveniently reflect the form of the channel mutual correlation matrix and the channel autocorrelation matrix, H and To represent the channel cross-correlation matrix and channel autocorrelation matrix, that is, the actual channel H and its least squares estimation result In practical applications, the actual channel H in this formula is estimated by the least squares method. approximate.

[0062] In practical applications, LMMSE channel estimation has better performance in noise suppression, and LMMSE channel estimation can measure the multipath power spectrum delay spectrum in real time, can match the channel well, and can suppress noise, so LMMSE will have more accurate channel estimation results than LS, but its implementation complexity is high. Therefore, in some embodiments of the present application, on the basis of the above embodiments, for complex network environments, especially when multipath fading is more serious, when performing frequency domain LMMSE filtering on the estimated channel in the frequency domain (i.e., filtering the least squares estimation result), different from the traditional conventional LMMSE channel estimation method, it can be verified through a large number of simulations that when generating the filtering weights, a fixed SNR and multipath delay spread mean square error τ can be set rms , thereby reducing its complexity.

[0063] Specifically, the elements in the above channel cross-correlation matrix and channel autocorrelation matrix satisfy the following conditions:

[0064]

[0065] r t (l) = J 0 (2*π*f max *l*T sym )=1

[0066] The first condition above indicates that the multipath power delay spectrum obeys an exponential distribution, r f (k) represents frequency domain correlation, k and l represent the subcarrier and symbol numbers respectively, j represents the imaginary part of the complex number, π represents pi, and f max is the maximum Doppler frequency, T sym is the time length of a symbol; the second condition indicates that considering 1D frequency domain filtering, the time domain correlation r t (l) = 1, J 0 (x) is the first kind of zero-order Bessel function; SNR is fixed at 30 dB; Δf is the subcarrier spacing; τrms is the mean square error of multipath delay spread, taking a fixed value τ rms =1.5e-5 seconds.

[0067] In this way, the implementation complexity can be greatly reduced while ensuring performance. In a complex network environment, the above channel estimation method has better performance than the traditional least squares-based channel estimation method.

[0068] Furthermore, in some embodiments of the present application, the method of performing equalization based on the final estimation result may specifically include: determining the covariance matrix of noise interference based on the least squares estimation result and the final estimation result; determining the equalization weight based on the covariance matrix and the final estimation result; and equalizing the frequency domain data based on the equalization weight.

[0069] Specifically, the MMSE equalization method is used for equalization in this application, and the specific equalization is expressed as follows:

[0070]

[0071] in, is the result of equalizing the frequency data Y, W is the equalization weight, and the specific calculation formula is:

[0072] W=(H H *R -1 *H+I) -1 *H H *R -1

[0073] In this formula, H represents the final estimation result, that is, Rnn-1 represents the covariance matrix of the background noise (in this application, the background noise can be the difference between the least squares estimation result based on the frequency domain data and the final estimation result), I represents the unit matrix, H H The superscript H in represents the conjugation operation.

[0074] In practical applications, the demodulation outputs soft information as the input of the decoder, and its size represents the credibility of the signal. In the prior art, the patent "Anti-interference signal receiving method, device and equipment" with application number CN202311835683.8 discloses a weighted soft information extraction scheme based on idle NI. When there is interference from neighboring cells, the idle NI can reflect the impact of interference on channel quality. However, in multipath channel scenarios or when there is multi-stream space division of services, the idle NI cannot reflect the current real channel quality. The use of this soft information extraction method will cause the demodulation performance to be affected by multipath and damaged.

[0075] Therefore, based on the above embodiments, the present application also provides two channel quality measurement methods for complex network environments, multipath fading channels, or when there is sub-band neighboring area interference, which can accurately measure the signal-to-noise ratio of each sub-band within the effective bandwidth, thereby reflecting the true channel quality, and then demodulating the equalized result, etc., wherein the channel quality information of the two channel quality measurement methods are the equalized signal-to-noise ratio and the equalization gain.

[0076] The post-equalization signal-to-noise ratio and the equalization equity can both be determined based on the equalization equity in the above-mentioned equalization process. The specific formula is as follows:

[0077]

[0078] β=W*H

[0079] Wherein, Sinr is the noise ratio after equalization, β is the equalization gain. It should be noted that in the above two formulas, the meaning of each symbol is the same as that in the calculation formula of the equalization weight, and they are not shown one by one here.

[0080] In the present application, for complex network environments, multipath fading channels, or when there is sub-band neighboring area interference, frequency selection or interference causes deep fading in some sub-bands. The channel quality information measured above is used for demodulation and soft information extraction, and then decoding is performed, which can reduce the soft information confidence of poor signal quality, thereby achieving better decoding performance and baseband signal reception capability.

[0081] Specifically, the Sinr and β obtained by the above measurement and calculation are uniformly recorded as snr, and the equalized data of different demodulation orders are calculated by the following formula (the snr in the calculation formula can be any one of Sinr and β). Demodulate and extract soft information LLR. For any input i-th equalized data The demodulation method is as follows, where i represents the i-th element.

[0082] The calculation formula for BPSK is:

[0083]

[0084] The calculation formula for QPSK is:

[0085]

[0086] The calculation formula for 16QAM is:

[0087]

[0088] The calculation formula for 64QAM is:

[0089]

[0090] LLR(i+4)=(d*2-|LLR(i+2)|)*snr

[0091] LLR(i+5)=(d*2-|LLR(i+3)|)*snr

[0092] The calculation formula for 256QAM is:

[0093]

[0094]

[0095] LLR(i+4)=(d*4-|LLR(i+2)|)*snr

[0096] LLR(i+5)=(d*4-|LLR(i+3)|)*snr

[0097] LLR(i+6)=(d*2-|LLR(i+4)|)*snr

[0098] LLR(i+7)=(d*2-|LLR(i+5)|)*snr

[0099]

[0100] In this way, the demodulation soft information extraction based on channel quality information can reduce the soft information confidence of poor signal quality, thereby achieving better decoding performance and baseband signal reception capability, as shown in the following example: Figure 2 and Figure 3 As shown, Figure 2 It is a comparison chart of the baseband signal reception processing method based on channel weighting provided in an embodiment of the present application and the baseband reception performance of the prior art, which shows that the demodulation and soft information extraction based on the two channel quality measurements proposed in the present invention are compared with the baseband reception performance based on NI measurement proposed in the patent of prior art application number CN202311835683.8 (specifically, the comparison of BLER, i.e., block error rate), which has a performance improvement of about 2dB. Figure 3 1 is a diagram showing the measurement result of the channel quality information in the baseband signal receiving and processing method based on channel weighting provided in an embodiment of the present application, which shows the measurement result of the channel quality information SINR of the example proposed by the present invention, that is, the signal-to-noise ratio measurement curve after equalization, from Figure 3 It can be seen that this measurement method can measure the received signal-to-noise ratio of different sub-bands, thereby providing accurate weighting factors for soft information extraction.

[0101] After the soft information is extracted through the above formula, the soft information LLR is used as input for subsequent descrambling and decoding to complete the processing of the baseband signal.

[0102] Device Example:

[0103] Based on the same inventive concept, the present invention also provides a baseband signal receiving and processing device based on channel weighting, which is used to implement the above method embodiment. Figure 4 is a structural diagram of a baseband signal receiving and processing device based on channel weighting provided in an embodiment of the present application, such as Figure 4 As shown, the device comprises:

[0104] A first channel estimation module 11 is used to obtain frequency domain data of a baseband signal, and perform channel estimation on the frequency domain data by a least square method to generate a least square method estimation result of the frequency domain data;

[0105] A second channel estimation module 12 is used to filter the least squares estimation result based on a linear minimum mean square error method to obtain a final estimation result;

[0106] An equalization module 13, configured to determine an equalization weight based on the final estimation result, and equalize the frequency domain data by using the equalization weight;

[0107] A measuring module 14, used to measure the channel quality information after equalization;

[0108] The demodulation and decoding module 15 is used to perform demodulation and decoding based on the channel quality information.

[0109] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0110] Device Example:

[0111] Based on the same inventive concept, the present invention also provides a baseband signal receiving and processing device based on channel weighting, which is used to implement the above method embodiment. Figure 5 is a structural diagram of a baseband signal receiving and processing device based on channel weighting provided in an embodiment of the present application, such as Figure 5 As shown, the baseband signal receiving and processing device based on channel weighting of this embodiment includes a processor 21 and a memory 22, and the processor 21 is connected to the memory 22. The processor 21 is used to call and execute the program stored in the memory 22; the memory 22 is used to store the program, and the program is at least used to execute the baseband signal receiving and processing method based on channel weighting in the above embodiment.

[0112] The specific implementation scheme of the baseband signal receiving and processing device based on channel weighting provided in the embodiment of the present application can refer to the implementation scheme of the baseband signal receiving and processing method based on channel weighting in any of the above embodiments, which will not be repeated here.

[0113] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0114] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0115] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0116] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0117] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0118] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0119] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0120] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" 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 present invention. In this specification, the schematic representation of the above terms does 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.

[0121] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A baseband signal receiving and processing method based on channel weighting, It is characterized in that include: Acquire frequency domain data of the baseband signal, and perform channel estimation on the frequency domain data by using the least squares method to generate a least squares estimation result of the frequency domain data; Based on the linear minimum mean square error method, filtering the least squares estimation result to obtain a final estimation result; Based on the final estimation result, determining an equalization weight, and equalizing the frequency domain data by using the equalization weight; Measuring channel quality information after equalization; Demodulation and decoding are performed based on the channel quality information.

2. The baseband signal receiving and processing method based on channel weighting according to claim 1, It is characterized in that The filtering process is performed on the least square method estimation result based on the linear minimum mean square error method to obtain the final estimation result, including: Generate filtering weights based on a preset signal-to-noise ratio and a multipath delay spread mean square error; The least squares estimation result is filtered based on the filtering weights to obtain the final estimation result.

3. The baseband signal receiving and processing method based on channel weighting according to claim 1, It is characterized in that The determining the equalization weight based on the final estimation result, and equalizing the frequency domain data by using the equalization weight, comprises: Determine a covariance matrix of noise interference based on the least squares estimation result and the final estimation result; Determining the equalization weight based on the covariance matrix and the final estimation result; The frequency domain data is equalized based on the equalization weight.

4. The baseband signal receiving and processing method based on channel weighting according to claim 1, It is characterized in that The channel quality information includes a post-equalization signal-to-noise ratio and an equalization gain; The post-equalization signal-to-noise ratio and the equalization equity are determined based on the equalization weight.

5. The baseband signal receiving and processing method based on channel weighting according to claim 4, It is characterized in that The demodulating and decoding based on the channel quality information includes: Based on the equalized signal-to-noise ratio or the equalized gain, the equalized frequency data of different modulation orders are demodulated respectively to extract corresponding soft information.

6. The baseband signal receiving and processing method based on channel weighting according to claim 5, It is characterized in that The demodulating and decoding based on the channel quality information further includes: decoding based on the soft information.

7. A baseband signal receiving and processing device based on channel weighting, It is characterized in that include: A first channel estimation module, used for acquiring frequency domain data of a baseband signal, and performing channel estimation on the frequency domain data by a least square method to generate a least square method estimation result of the frequency domain data; A second channel estimation module is used to filter the least squares estimation result based on a linear minimum mean square error method to obtain a final estimation result; An equalization module, configured to determine an equalization weight based on the final estimation result, and equalize the frequency domain data by using the equalization weight; A measurement module, used to measure the channel quality information after equalization; The demodulation and decoding module is used to perform demodulation and decoding based on the channel quality information.

8. A baseband signal receiving and processing device based on channel weighting, It is characterized in that The invention comprises a processor and a memory, wherein the processor is connected to the memory: Wherein, the processor is used to call and execute the program stored in the memory; The memory is used to store the program, and the program is at least used to execute the baseband signal receiving and processing method based on channel weighting as described in any one of claims 1-6.

Images