A noise estimation and channel equalization method, device and apparatus

Abstract

The embodiment of the present application provides a kind of noise estimation and channel equalization method, equipment and device, it is related to communication technical field, it is applied to receiving end, the above-mentioned method includes: to the signal to be processed is not included signal filtering processing, the first channel estimation processing of containing multi-port separation processing, obtain the intermediate value obtained before carrying out multi-port separation processing in the process of first channel estimation processing, and the first estimation result corresponding to each port obtained after completing first channel estimation processing;Respectively to the first estimation result corresponding to each port is carried out the second channel estimation processing containing signal filtering processing, obtains the second estimation result corresponding to each port;Based on intermediate value and the second estimation result corresponding to each port, calculate the noise value indicating target channel noise;Based on noise value, the channel equalization processing is carried out to the signal to be processed.Application the scheme provided in the embodiment of the present application can improve the accuracy of the noise value and channel equalization result obtained.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a noise estimation and channel equalization method, device, and apparatus. Background Technology

[0002] The signal transmitted between the transmitter and receiver is affected by Gaussian white noise, channel fading, and interference signals during transmission through the channel. These effects can be collectively referred to as noise, causing a difference between the signal received by the receiver and the signal transmitted by the transmitter. The receiver can use channel equalization technology to restore the received signal, thereby removing noise and obtaining the original signal transmitted by the transmitter.

[0003] There are various methods for channel equalization of signals in existing technologies. Most of these methods require channel estimation to obtain noise values ​​representing channel noise, and then the channel equalization process is completed based on these noise values. Therefore, the accuracy of the calculated noise values ​​affects the accuracy of the channel equalization results. To improve the accuracy of the channel equalization results, it is necessary to improve the accuracy of the obtained noise values. Summary of the Invention

[0004] The purpose of this invention is to provide a noise estimation and channel equalization method, apparatus, and device to improve the accuracy of the obtained noise values, thereby improving the accuracy of the channel equalization results. The specific technical solution is as follows:

[0005] In a first aspect, embodiments of the present invention provide a noise estimation and channel equalization method, applied at a receiving end, the method comprising:

[0006] The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed during the first channel estimation process, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is: the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0007] The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port.

[0008] Based on the intermediate value and the second estimation result corresponding to each port, the noise value representing the target channel noise is calculated;

[0009] Based on the noise value, channel equalization processing is performed on the signal to be processed.

[0010] Secondly, embodiments of the present invention provide a noise estimation and channel equalization device, which, as a receiving end, includes a memory, a transceiver, and a processor:

[0011] A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations:

[0012] The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed during the first channel estimation process, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is: the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0013] The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port.

[0014] Based on the intermediate value and the second estimation result corresponding to each port, the noise value representing the target channel noise is calculated;

[0015] Based on the noise value, channel equalization processing is performed on the signal to be processed.

[0016] Thirdly, embodiments of the present invention provide a noise estimation and channel equalization apparatus, applied at a receiving end, the apparatus comprising:

[0017] The first estimation processing module is used to perform a first channel estimation process on the signal to be processed, which does not include signal filtering processing but includes multi-port separation processing, to obtain an intermediate value obtained before multi-port separation processing in the first channel estimation process, and a first estimation result corresponding to each port obtained after the first channel estimation process is completed. The signal to be processed is a signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0018] The second estimation processing module is used to perform second channel estimation processing, which includes signal filtering, on the first estimation results corresponding to each port to obtain the second estimation results corresponding to each port.

[0019] The noise value calculation module is used to calculate the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port;

[0020] The channel equalization module is used to perform channel equalization processing on the signal to be processed based on the noise value.

[0021] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the methods described in the first aspect.

[0022] Fifthly, embodiments of the present invention also provide a computer program product containing instructions that, when run on a computer, cause the computer to perform any of the methods described in the first aspect above.

[0023] Beneficial effects of the embodiments of the present invention:

[0024] This invention provides a noise estimation and channel equalization method. The receiving end first performs a first channel estimation process on the signal to be processed, which does not include channel filtering but includes multi-port separation processing. This obtains an intermediate value before multi-port separation processing and a first estimation result for each port after multi-port separation processing. Then, a second channel estimation process, including signal filtering, is performed on the first estimation results for each port to obtain a second estimation result. Based on the intermediate value and the second estimation result, a noise value is calculated. Channel equalization processing can then be performed on the signal to be processed based on the noise value and the second estimation result.

[0025] As can be seen from the above, since no signal filtering was performed during the first channel estimation process, the noise components in the signal to be processed were almost not removed, thus the intermediate values ​​contain complete noise components. However, signal filtering was performed during the second channel estimation process, so the second estimation results contain almost no noise components. The aforementioned intermediate values ​​are the results obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise can be obtained.

[0026] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at various frequency domain positions after multi-port multiplexing, existing technologies, when performing multi-port separation, add the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then take the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions affects the variance of the noise contained in the result. Therefore, if the noise value is calculated based on the first estimation result obtained after multi-port separation, the calculated noise value will be inaccurate. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0028] Figure 1 A flowchart illustrating the first noise estimation and channel equalization method provided in an embodiment of the present invention;

[0029] Figure 2 This is a flowchart illustrating the second noise estimation and channel equalization method provided in an embodiment of the present invention.

[0030] Figure 3 A flowchart illustrating the third noise estimation and channel equalization method provided in this embodiment of the invention;

[0031] Figure 4 A schematic diagram of a noise estimation and channel equalization device provided in an embodiment of the present invention;

[0032] Figure 5 This is a schematic diagram of the structure of the first noise estimation and channel equalization device provided in an embodiment of the present invention;

[0033] Figure 6 This is a schematic diagram of the structure of the second noise estimation and channel equalization device provided in an embodiment of the present invention;

[0034] Figure 7This is a schematic diagram of the third noise estimation and channel equalization device provided in an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of the present invention.

[0036] To improve the accuracy of the obtained noise values, and thus the accuracy of the obtained channel equalization results, embodiments of the present invention provide a noise estimation and channel equalization method, device, and apparatus.

[0037] This invention provides a noise estimation and channel equalization method applied at a receiver. The method includes:

[0038] The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed during the first channel estimation process, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0039] The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port.

[0040] Based on the above intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise is calculated;

[0041] Based on the above noise value and the second estimation result, channel equalization processing is performed on the above signal to be processed.

[0042] As can be seen from the above, since no signal filtering was performed during the first channel estimation process, the noise components in the signal to be processed were almost not removed, thus the intermediate values ​​contain noise components. However, signal filtering was performed during the second channel estimation process, so the second estimation results contain almost no noise components. The aforementioned intermediate values ​​are the results obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise can be obtained.

[0043] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at various frequency domain positions after multi-port multiplexing, existing technologies, when performing multi-port separation, add the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then take the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions affects the variance of the noise contained in the result. Therefore, if the noise value is calculated based on the first estimation result obtained after multi-port separation, the calculated noise value will be inaccurate. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy.

[0044] First, the application scenario of this invention is described. In this embodiment, the transmitting end sends a signal to the receiving end through a target channel. The transmitted signal is affected by noise in the target channel, causing the signal received by the receiving end to differ from the signal sent by the transmitting end. The signal received by the receiving end is the signal to be processed in the following text. The aforementioned noise effects include the effects of Gaussian white noise and channel interference.

[0045] After receiving the signal to be processed, the receiving end can use channel equalization technology to process the signal and recover the original signal sent by the transmitting end. Channel equalization technology is divided into two main categories: linear detection and nonlinear detection. Linear detection includes detection methods such as ML (Maximum Likelihood) algorithm and spherical decoding algorithm, while nonlinear detection includes detection methods such as ZF (Zero Forcing) algorithm and MMSE (Minimum Mean Square Error) equalization algorithm.

[0046] Specifically, when the target channel experiences relatively weak channel interference and the noise is mainly Gaussian white noise, the signal to be processed can be represented by the following formula:

[0047] Y = XH + Z

[0048] Wherein, Y is the signal to be processed, X is the DMRS (Demodulation Reference Signal) symbol sent by the transmitter, H is the channel parameter of the target channel, and Z represents Gaussian white noise.

[0049] In the above situation, if the MMSE equalization algorithm is used for channel equalization, the signal X transmitted by the transmitter is recovered by calculating the channel to be processed according to the following formula:

[0050] X = H H (HH H +δ 2 I) -1 Y

[0051] Where X is the DMRS symbol transmitted by the transmitter, H is the channel parameter of the target channel, and the above δ 2 Let I be the white noise variance of the target channel's Gaussian white noise, I be the identity matrix, and Y be the signal to be processed.

[0052] Therefore, the white noise variance δ mentioned above can be seen. 2 The accuracy of the channel equalization processing result X will affect the accuracy of the channel equalization processing result X.

[0053] When the target channel experiences strong channel interference, and the noise is a combination of Gaussian white noise and channel interference, the channel interference has a significant impact on the signal to be processed. The signal to be processed can be expressed by the following formula:

[0054] Y = XH + X dis H dis +Z

[0055] Wherein, Y is the signal to be processed, X is the DMRS symbol transmitted by the transmitter, H is the channel parameter of the target channel, and X... dis H represents the pilot signal of the interference signal. dis Z represents the channel parameter of the channel through which the interference signal passes, and Z represents Gaussian white noise.

[0056] In the above situation, if the MMSE equalization algorithm is used for channel equalization, the DMRS symbol X transmitted by the transmitter can be recovered by calculating the channel to be processed according to the following formula:

[0057] X = H H (HH H +RI) -1 Y

[0058] Where X is the DMRS symbol transmitted by the transmitter, H is the channel parameter of the target channel, R is the covariance matrix representing the channel interference received by the target channel, I is the identity matrix, and Y is the signal to be processed.

[0059] Therefore, it can be seen that the accuracy of the covariance matrix R will affect the accuracy of the channel equalization result X.

[0060] White noise variance δ2 Both the noise value and the covariance matrix R represent the noise value of the target channel. Therefore, the accuracy of the noise value will affect the accuracy of the channel equalization result X.

[0061] In addition, the transmitting end contains multiple ports capable of transmitting signals. In this embodiment, the transmitting end performs multi-port multiplexing processing on the signals when transmitting them, that is, it integrates the signals corresponding to multiple ports into a single signal before sending it to the receiving end. The receiving end, upon receiving the signal to be processed, needs to perform multi-port separation processing, which is the opposite of multi-port multiplexing.

[0062] Specifically, the transmitting end can implement the multi-port multiplexing process based on the methods specified in the existing technology protocols. For example, when the transmitting end transmits signals based on 5GNR (The 5th Generation mobile communication technology New Radio), based on type 1, multi-port multiplexing of 8 ports can be realized, that is, the transmitting end can integrate the signals of 8 ports into the same signal and transmit it through the target channel.

[0063] See Figure 1 This is a flowchart illustrating the first noise estimation and channel equalization method provided in this embodiment of the invention, applied to the receiving end. The method includes the following steps S101-S104.

[0064] S101: Perform a first channel estimation process on the signal to be processed, which does not include signal filtering but includes multi-port separation processing, to obtain the intermediate value obtained before multi-port separation processing in the first channel estimation process, and the first estimation result corresponding to each port obtained after the first channel estimation process is completed.

[0065] The signal to be processed is the signal that the transmitting end performs multi-port multiplexing on, and then transmits to the receiving end through the target channel. The target channel is the channel used by the transmitting end to send the signal to be processed to the receiving end.

[0066] Specifically, the aforementioned intermediate value can be the value obtained after the conjugate multiplication calculation included in the first channel estimation processing of the signal to be processed. The first channel estimation processing can be performed based on the LS (Least Squares) algorithm, or it can be completed based on other algorithms in the prior art. This embodiment does not limit this.

[0067] In one embodiment of the present invention, when the target channel experiences weak channel interference and the noise is mainly Gaussian white noise, if the first channel estimation process is performed based on the LS algorithm, the approximate value of the intermediate value obtained in the first channel estimation process can be expressed as:

[0068]

[0069] Among them, the above This represents the estimated intermediate value obtained before multi-port separation processing during the first channel estimation process. H is the channel parameter of the target channel, and Z represents Gaussian white noise.

[0070] In another embodiment of the present invention, when the target channel is subject to strong channel interference and the noise is mainly channel interference, if the first channel estimation process is performed based on the LS algorithm, the approximate value of the intermediate value obtained in the first channel estimation process can be expressed as:

[0071]

[0072] Among them, the above This represents the estimated intermediate value obtained before multi-port separation processing during the first channel estimation process. H is the channel parameter of the target channel, Z represents Gaussian white noise, and S represents the interference signal.

[0073] Specifically, since the PN (Pseudo-noise) sequence contained in the signal to be processed has good cross-correlation, S can be approximated as part of Gaussian white noise. Regardless of whether the target channel is subject to strong channel interference, the above intermediate value can be considered as the sum of the channel parameters of the target channel and the value representing Gaussian white noise.

[0074] The above intermediate value can be expressed by the following formula:

[0075]

[0076] In addition, since the above intermediate value is the value before multi-port separation processing, the above intermediate value can be considered as the value obtained after channel reconstruction of the first estimation result corresponding to the port sharing the same frequency domain position when the transmitter performs port multiplexing processing.

[0077] Specifically, the first estimation result for each port contains multiple different sub-estimation results corresponding to different frequency domain positions.

[0078] S102: Perform a second channel estimation process, including signal filtering, on the first estimation results corresponding to each port to obtain the second estimation results corresponding to each port.

[0079] In one embodiment of the present invention, the second channel estimation process can be implemented based on the MMSE channel estimation algorithm, or the above-mentioned second channel estimation process can be implemented based on other channel estimation algorithms that include signal filtering. This embodiment does not limit the specific implementation of the second channel estimation process.

[0080] Specifically, for each port, the second estimation result corresponding to that port contains multiple different sub-estimation results corresponding to different frequency domain positions.

[0081] Taking the signal to be processed as an example generated based on 5G NR type 1, the calculated second estimation result corresponding to port 0 includes sub-estimation results corresponding to different frequency domain positions such as frequency domain position 1, frequency domain position 3, and frequency domain position 5, which can be expressed as follows:

[0082]

[0083] Where k represents the frequency domain position number, the above expression takes k = 1, 3, 5 as an example. This represents the sub-estimation result corresponding to frequency domain position k in the second estimation result for port 0. This represents the sub-estimation result corresponding to frequency domain position 1 in the second estimation result for port 0. This represents the sub-estimation result corresponding to frequency domain position 3 in the second estimation result for port 0. This represents the sub-estimation result corresponding to frequency domain position 5 in the second estimation result for port 0.

[0084] In addition, the second estimation result corresponding to port 1 includes sub-estimation results corresponding to different frequency domain positions, such as frequency domain position 1, frequency domain position 3, and frequency domain position 5, which can be represented as follows:

[0085]

[0086] Where k represents the frequency domain position number, the above expression takes k = 1, 3, 5 as an example. This represents the sub-estimation result corresponding to frequency domain position k in the second estimation result for port 1. This represents the sub-estimation result corresponding to frequency domain position 1 in the second estimation result for port 1. This represents the sub-estimation result corresponding to frequency domain position 3 in the second estimation result for port 1. This represents the sub-estimation result corresponding to frequency domain position 5 in the second estimation result for port 1.

[0087] Specifically, the positive and negative values ​​of each sub-estimation result are specified in the prior art protocol.

[0088] S103: Based on the above intermediate values ​​and the second estimation results corresponding to each port, calculate the noise value representing the target channel noise.

[0089] Specifically, for each port and each frequency domain location, a sub-noise value corresponding to that port and frequency domain location can be calculated based on the sub-intermediate value corresponding to that port and frequency domain location in the intermediate value and the sub-estimation result corresponding to that port and frequency domain location in the second estimation result. After calculating each sub-noise value separately, a noise value containing each sub-noise value can be obtained.

[0090] The noise values ​​mentioned above can be considered as the noise variance representing the target channel noise. The dimension of these noise values ​​is the antenna data at the transmitting end multiplied by the number of frequency domain locations.

[0091] In one embodiment of the present invention, it can be achieved through the following: Figure 2 Steps S103A-S103B shown implement the above step S103, which will not be described in detail here.

[0092] S 104: Based on the above noise values, perform channel equalization processing on the above signal to be processed.

[0093] In one embodiment of the present invention, the above-mentioned channel equalization process can be implemented using existing techniques, and this embodiment does not limit this to any particular method. Specifically, taking the MMSE equalization algorithm for channel equalization as an example, as described above, the calculated noise value is substituted into the formula of the MMSE equalization algorithm shown above to recover the signal transmitted by the transmitter.

[0094] As can be seen from the above, since no signal filtering was performed during the first channel estimation process, the noise components in the signal to be processed were almost not removed, thus the intermediate values ​​contain noise components. However, signal filtering was performed during the second channel estimation process, so the second estimation results contain almost no noise components. The aforementioned intermediate values ​​are the results obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise can be obtained.

[0095] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at each frequency domain position after multi-port multiplexing, existing technologies perform multi-port separation by adding the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then taking the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions may result in low accuracy and affect the variance of the noise contained in the result. Therefore, calculating the noise value based on the first estimation result obtained after multi-port separation will lead to inaccurate noise values. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy.

[0096] Furthermore, in the process of channel equalization using existing technologies, it is often necessary to calculate noise values, and this calculation typically involves both first and second channel estimation processes. However, the parameters used in the prior art to calculate the noise values ​​differ from those in this embodiment. In other words, the channel equalization process in this solution is similar to the calculation steps performed in existing technologies. Compared to existing technologies, channel equalization using this embodiment does not consume excessive additional computational resources.

[0097] See Figure 2 This is a flowchart illustrating the second noise estimation and channel equalization method provided in this embodiment of the invention, which is consistent with the aforementioned... Figure 1 Compared to the embodiment shown, step S103 can be implemented by the following steps S103A-S103B.

[0098] S103A: Perform channel reconstruction processing on the second estimation results corresponding to each port to obtain the channel reconstruction results.

[0099] In one embodiment of the present invention, the second estimation result includes sub-estimation results corresponding to different frequency domain positions. For each different frequency domain position, channel reconstruction processing can be performed on the sub-estimation results corresponding to that frequency domain position in each of the second estimation results to obtain the channel reconstruction sub-result corresponding to that frequency domain position. This results in a channel reconstruction result containing the channel reconstruction sub-results corresponding to each frequency domain position.

[0100] Furthermore, as mentioned earlier, due to the influence of multi-port multiplexing, the transmitting end adjusts the sign of the signal values ​​at certain ports and frequency domain positions to their opposites before transmitting the signal. After the first and second channel estimation processes, the sign of the sub-estimation result in the second estimation result, calculated from the signal value with the opposite sign, will become the original normal sign. This normal sign is the sign after multi-port separation processing. During the channel reconstruction process, the intermediate value of the first channel estimation result has not yet undergone multi-port separation processing; therefore, the intermediate value carries the opposite sign, which will affect the channel reconstruction result. Therefore, step S103A can be implemented through steps A-C to remove the influence of the sign on the channel reconstruction result.

[0101] Step A: For each port, adjust the sign of each sub-estimation result corresponding to that port based on the port orthogonal code.

[0102] Each sub-estimation result corresponds to a frequency domain position in the signal to be processed.

[0103] Specifically, after adjusting the sign of each sub-estimation result based on the port orthogonal code, the sign of the sub-estimation result that was originally negative will be adjusted to the opposite number, while the sign of the sub-estimation result that was originally positive will remain unchanged.

[0104] Step B: For each frequency domain location, perform channel reconstruction processing on each sub-estimation result corresponding to different ports after symbol adjustment, to obtain the channel reconstruction sub-result corresponding to that frequency domain location.

[0105] In one embodiment of the present invention, for frequency domain position k, each port using frequency domain position k is determined when the transmitting end performs port multiplexing processing, and the sub-estimation result after symbol adjustment of the determined port corresponding to frequency domain position k is used for channel reconstruction processing.

[0106] Step C: Obtain the channel reconstruction result, which includes the channel reconstruction sub-results corresponding to each frequency domain position.

[0107] Specifically, the channel reconstruction results can be merged into a single channel reconstruction result according to the order of their corresponding frequency domain positions.

[0108] S103B: Subtract the above intermediate value from the above channel reconstruction result to obtain the noise value representing the target channel noise.

[0109] In one embodiment of the present invention, for each frequency domain location, the sub-intermediate value corresponding to that frequency domain location in the aforementioned intermediate values ​​and the channel reconstruction sub-result corresponding to that frequency domain location in the channel reconstruction results can be subtracted to obtain the sub-noise value corresponding to that frequency domain location. This yields a noise value containing the sub-noise values ​​corresponding to each frequency domain location.

[0110] Specifically, for frequency domain position k, the sub-noise value corresponding to frequency domain position k can be calculated using the following formula:

[0111]

[0112] Among them, the above noise k This represents the sub-noise value corresponding to frequency domain position k. This is an approximation of the sub-intermediate value corresponding to position k in the frequency domain. It is an approximation of the sub-estimation result corresponding to the frequency domain position k contained in the second estimation result.

[0113] As can be seen from the above, channel reconstruction processing is performed on the second estimation results corresponding to each port. The channel reconstruction result includes the second estimation results corresponding to each port after noise removal. The intermediate value obtained above is the preliminary channel estimation result without noise removal and without multi-port separation processing. The main difference between the intermediate value and the channel reconstruction result is that the intermediate value contains noise, while the channel reconstruction result does not contain noise. Subtracting the above from the channel reconstruction result yields the noise value.

[0114] See Figure 3 This is a flowchart illustrating the third noise estimation and channel equalization method provided in this embodiment of the invention, which is consistent with the aforementioned... Figure 1 The embodiment shown can be implemented by the following steps S104A-S104B, compared to step S104 described above.

[0115] S104A: Calculate the product of the above noise values ​​to obtain the interference covariance matrix.

[0116] Specifically, the dimension of the noise value is the number of antennas at the transmitting end × the number of frequency domain locations, and the dimension of the calculated covariance matrix is ​​the number of antennas × the number of antennas.

[0117] S104B: Based on the above interference covariance matrix, perform channel equalization processing on the above signal to be processed.

[0118] In one embodiment of the present invention, the above-mentioned channel equalization process can be implemented using methods in the prior art, and this embodiment does not limit this.

[0119] Specifically, taking the channel equalization process using the MMSE equalization algorithm as an example, as described above, the calculated interference covariance matrix is ​​used as δ. 2 Substituting into the formula X = H of the MMSE equalization algorithm shown earlier... H (HH H +δ 2 I) -1 In Y, the signal sent by the sending end is recovered.

[0120] Alternatively, the calculated covariance matrix can be used as R and substituted into the formula X = H in the MMSE equilibrium algorithm shown above. H (HH H +RI) -1 In Y, the signal sent by the sending end is recovered.

[0121] As can be seen from the above, after calculating the noise value, the interference covariance matrix can be calculated based on the noise value. Then, based on the algorithm in the existing technology, the above interference covariance matrix can be used to realize the channel equalization process of the signal to be processed.

[0122] Corresponding to the aforementioned noise estimation and channel equalization devices applied to the receiving end, this embodiment of the invention also provides a noise estimation and channel equalization device.

[0123] See Figure 4 This is a schematic diagram of a noise estimation and channel equalization device provided in an embodiment of the present invention. As a receiving end, it includes a memory 401, a transceiver 402, and a processor 403.

[0124] Memory 401 is used to store computer programs; transceiver 402 is used to send and receive data under the control of the processor; processor 403 is used to read the computer programs in the memory and perform the following operations:

[0125] The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed during the first channel estimation process, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is: the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0126] The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port.

[0127] Based on the intermediate value and the second estimation result corresponding to each port, the noise value representing the target channel noise is calculated;

[0128] Based on the noise value, channel equalization processing is performed on the signal to be processed.

[0129] Among them, Figure 4 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 403) and memory (memory 401). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 402 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor 403 is responsible for managing the bus architecture and general processing, and the memory 401 can store data used by the processor 403 during operation.

[0130] The processor 403 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0131] As can be seen from the above, since no signal filtering was performed during the first channel estimation process, the noise components in the signal to be processed were almost not removed, thus the intermediate values ​​contain noise components. However, signal filtering was performed during the second channel estimation process, so the second estimation results contain almost no noise components. The aforementioned intermediate values ​​are the results obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise can be obtained.

[0132] Furthermore, during the multi-port separation process, for each frequency domain location, the signal values ​​corresponding to the multiplexed ports at that frequency domain location are canceled out to separate the first estimation result corresponding to each port. Since the number of multiplexed ports is often small, the mutual cancellation of signal values ​​corresponding to a small number of ports leads to low accuracy of the separated first estimation result. The noise components contained therein may change, thus affecting the variance of the noise. Therefore, if the noise value is calculated based on the first estimation result obtained after multi-port separation, the calculated noise value will be inaccurate. However, this scheme uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise components contained in the intermediate value are not affected by the multi-port separation process, so the noise value calculated based on the intermediate value has higher accuracy.

[0133] In one embodiment of the present invention, the step of calculating the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port specifically includes:

[0134] The second estimation results corresponding to each port are processed for channel reconstruction to obtain the channel reconstruction results.

[0135] Subtracting the intermediate value from the channel reconstruction result yields the noise value representing the target channel noise.

[0136] As can be seen from the above, channel reconstruction processing is performed on the second estimation results corresponding to each port. The channel reconstruction result includes the second estimation results corresponding to each port after noise removal. The intermediate value obtained above is the preliminary channel estimation result without noise removal and without multi-port separation processing. The main difference between the intermediate value and the channel reconstruction result is that the intermediate value contains noise, while the channel reconstruction result does not contain noise. Subtracting the above from the channel reconstruction result yields the noise value.

[0137] In one embodiment of the present invention, the channel reconstruction processing of the second estimation results corresponding to each port to obtain the channel reconstruction result specifically includes:

[0138] For each port, based on the port orthogonal code, the sign of each sub-estimation result corresponding to that port is adjusted, wherein each sub-estimation result corresponds to a frequency domain position in the signal to be processed;

[0139] For each frequency domain location, channel reconstruction processing is performed on each sub-estimation result corresponding to different ports after sign adjustment, to obtain the channel reconstruction sub-result corresponding to that frequency domain location;

[0140] Obtain the channel reconstruction result, which includes the channel reconstruction sub-results corresponding to each frequency domain position.

[0141] As can be seen from the above, negative sub-estimation results can affect the channel reconstruction results during the channel reconstruction process. Therefore, the sub-estimation results can be adjusted to positive values ​​in advance before calculating the channel reconstruction results to remove the influence of negative sub-estimation results on the channel reconstruction results.

[0142] In one embodiment of the present invention, the channel equalization processing of the signal to be processed based on the noise value specifically includes:

[0143] The interference covariance matrix is ​​obtained by multiplying the noise values ​​together.

[0144] Based on the interference covariance matrix, channel equalization processing is performed on the signal to be processed.

[0145] As can be seen from the above, after calculating the noise value, the interference covariance matrix can be calculated based on the noise value. Then, based on the algorithm in the existing technology, the above interference covariance matrix can be used to realize the channel equalization process of the signal to be processed.

[0146] Corresponding to the aforementioned noise estimation and channel equalization methods applied to the receiving end, this embodiment of the invention also provides a noise estimation and channel equalization device.

[0147] See Figure 5 This is a schematic diagram of the structure of a first noise estimation and channel equalization device provided in an embodiment of the present invention, applied at a receiving end. The device includes:

[0148] The first estimation processing module 501 is used to perform a first channel estimation process on the signal to be processed, which does not include signal filtering processing but includes multi-port separation processing, to obtain an intermediate value before multi-port separation processing and a first estimation result corresponding to each port after the first channel estimation processing is completed. The signal to be processed is a signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal.

[0149] The second estimation processing module 502 is used to perform second channel estimation processing, which includes signal filtering, on the first estimation results corresponding to each port to obtain the second estimation results corresponding to each port.

[0150] The noise value calculation module 503 is used to calculate the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port;

[0151] The channel equalization module 504 is used to perform channel equalization processing on the signal to be processed based on the noise value.

[0152] As can be seen from the above, since no signal filtering was performed during the first channel estimation process, the noise components in the signal to be processed were almost not removed, thus the intermediate values ​​contain noise components. However, signal filtering was performed during the second channel estimation process, so the second estimation results contain almost no noise components. The aforementioned intermediate values ​​are the results obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate values ​​and the second estimation results corresponding to each port, the noise value representing the target channel noise can be obtained.

[0153] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at each frequency domain position after multi-port multiplexing, existing technologies perform multi-port separation by adding the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then taking the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions may result in low accuracy and affect the variance of the noise contained in the result. Therefore, calculating the noise value based on the first estimation result obtained after multi-port separation will lead to inaccurate noise values. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy.

[0154] See Figure 6 This is a schematic diagram of the structure of the second noise estimation and channel equalization device provided in the embodiment of the present invention, which is consistent with the aforementioned Figure 5 Compared to the embodiment shown, the noise value calculation module 503 described above includes:

[0155] The channel reconstruction submodule 503A is used to perform channel reconstruction processing on the second estimation results corresponding to each port to obtain the channel reconstruction result.

[0156] The noise value calculation submodule 503B is used to subtract the intermediate value from the channel reconstruction result to obtain the noise value representing the target channel noise.

[0157] As can be seen from the above, channel reconstruction processing is performed on the second estimation results corresponding to each port. The channel reconstruction result includes the second estimation results corresponding to each port after noise removal. The intermediate value obtained above is the preliminary channel estimation result without noise removal and without multi-port separation processing. The main difference between the intermediate value and the channel reconstruction result is that the intermediate value contains noise, while the channel reconstruction result does not contain noise. Subtracting the above from the channel reconstruction result yields the noise value.

[0158] See Figure 7 This is a schematic diagram of the third noise estimation and channel equalization device provided in the embodiments of the present invention, which is consistent with the aforementioned Figure 6 Compared to the illustrated embodiment, the channel reconstruction submodule 503A described above includes:

[0159] The result adjustment unit 503A1 is used to adjust the sign of each sub-estimation result corresponding to each port based on the port orthogonal code, wherein each sub-estimation result corresponds to a frequency domain position in the signal to be processed.

[0160] The channel reconstruction unit 503A2 is used to perform channel reconstruction on each sub-estimation result corresponding to different ports after symbol adjustment for each frequency domain position, so as to obtain the channel reconstruction sub-result corresponding to the frequency domain position.

[0161] The result acquisition unit 503A3 is used to obtain the channel reconstruction result, which includes the channel reconstruction sub-results corresponding to each frequency domain position.

[0162] As can be seen from the above, negative sub-estimation results can affect the channel reconstruction results during the channel reconstruction process. Therefore, the sub-estimation results can be adjusted to positive values ​​in advance before calculating the channel reconstruction results to remove the influence of negative sub-estimation results on the channel reconstruction results.

[0163] In one embodiment of the present invention, the channel equalization module 504 is specifically used for:

[0164] The interference covariance matrix is ​​obtained by multiplying the noise values ​​together.

[0165] Based on the interference covariance matrix, channel equalization processing is performed on the signal to be processed.

[0166] As can be seen from the above, after calculating the noise value, the interference covariance matrix can be calculated based on the noise value. Then, based on the algorithm in the existing technology, the above interference covariance matrix can be used to realize the channel equalization process of the signal to be processed.

[0167] In another embodiment of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored therein, and when the computer program is executed by a processor, it implements the steps of any of the above-described noise estimation and channel equalization methods.

[0168] When performing noise estimation and channel equalization using the computer-readable storage medium provided in this embodiment of the invention, since no signal filtering is performed during the first channel estimation process, the noise components in the signal to be processed are almost not removed, thus the intermediate value contains noise components. However, signal filtering is performed during the second channel estimation process, so the second estimation result contains almost no noise components. The aforementioned intermediate value is the result obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined second estimation results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate value and the second estimation results corresponding to each port, a noise value representing the target channel noise can be obtained.

[0169] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at each frequency domain position after multi-port multiplexing, existing technologies perform multi-port separation by adding the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then taking the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions may result in low accuracy and affect the variance of the noise contained in the result. Therefore, calculating the noise value based on the first estimation result obtained after multi-port separation will lead to inaccurate noise values. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy.

[0170] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform any of the noise estimation and channel equalization methods described in the above embodiments.

[0171] When performing noise estimation and channel equalization using the computer program product provided in this embodiment of the invention, since no signal filtering is performed during the first channel estimation process, the noise components in the signal to be processed are almost not removed, thus the intermediate value contains noise components. However, signal filtering is performed during the second channel estimation process, so the second estimation result contains almost no noise components. The aforementioned intermediate value is the result obtained before multi-port separation processing and can reflect the channel condition of the target channel after being affected by noise. Each second estimation result corresponds to a different port, and the combined second estimation results can collectively reflect the channel condition of the target channel when it is not affected by noise. Therefore, based on the aforementioned intermediate value and the second estimation results corresponding to each port, a noise value representing the noise of the target channel can be obtained.

[0172] Furthermore, after multi-port multiplexing, the signals corresponding to the multiple ports are combined into a single signal to be processed. Based on the sign characteristics of the signal values ​​at each frequency domain position after multi-port multiplexing, existing technologies perform multi-port separation by adding the signal values ​​corresponding to adjacent frequency domain positions in the signal to be processed to cancel out the positive and negative signs, then taking the average value to separate the sub-estimation results corresponding to each port at each frequency domain position. Thus, for the same port, a first estimation result containing all the sub-estimation results corresponding to that port is obtained. However, since the number of frequency domain positions corresponding to the signal values ​​processed during port separation is often small, multi-port separation based on the mutual cancellation of a small number of signal values ​​corresponding to different frequency domain positions may result in low accuracy and affect the variance of the noise contained in the result. Therefore, calculating the noise value based on the first estimation result obtained after multi-port separation will lead to inaccurate noise values. However, this solution uses the intermediate value obtained before multi-port separation to calculate the noise value. The noise component contained in the intermediate value is not affected by the multi-port separation process, therefore the noise value calculated based on the intermediate value has higher accuracy.

[0173] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0174] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0175] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for devices, apparatuses, storage media, and computer programs are basically similar to the method embodiments, and therefore the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0176] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0177] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0178] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0179] These processors can execute instructions that can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0180] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations of this application fall within the scope of the embodiments of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A noise estimation and channel equalization method, characterized in that, Applied to the receiving end, the method includes: The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed in the first channel estimation process is obtained, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal. The intermediate value is the value obtained after the conjugate multiplication calculation included in the first channel estimation process of the signal to be processed. The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port. Based on the intermediate value and the second estimation result corresponding to each port, the noise value representing the target channel noise is calculated; Based on the noise value, channel equalization processing is performed on the signal to be processed.

2. The method according to claim 1, characterized in that, The calculation of the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port includes: The second estimation results corresponding to each port are processed for channel reconstruction to obtain the channel reconstruction results. Subtracting the intermediate value from the channel reconstruction result yields the noise value representing the target channel noise.

3. The method according to claim 2, characterized in that, The channel reconstruction process is performed on the second estimation results corresponding to each port to obtain the channel reconstruction results, including: For each port, based on the port orthogonal code, the sign of each sub-estimation result corresponding to that port is adjusted, wherein each sub-estimation result corresponds to a frequency domain position in the signal to be processed; For each frequency domain location, channel reconstruction processing is performed on each sub-estimation result corresponding to different ports after sign adjustment, to obtain the channel reconstruction sub-result corresponding to that frequency domain location; Obtain the channel reconstruction result, which includes the channel reconstruction sub-results corresponding to each frequency domain position.

4. The method according to any one of claims 1-3, characterized in that, The process of performing channel equalization on the signal to be processed based on the noise value includes: The interference covariance matrix is ​​obtained by multiplying the noise values ​​together. Based on the interference covariance matrix, channel equalization processing is performed on the signal to be processed.

5. A noise estimation and channel equalization device, characterized in that, As the receiving end, it includes memory, transceiver, and processor: A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations: The signal to be processed is subjected to a first channel estimation process that does not include signal filtering but includes multi-port separation processing. The intermediate value obtained before multi-port separation processing is performed in the first channel estimation process is obtained, and the first estimation result corresponding to each port is obtained after the first channel estimation process is completed. The signal to be processed is the signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal. The intermediate value is the value obtained after the conjugate multiplication calculation included in the first channel estimation process of the signal to be processed. The first estimation results corresponding to each port are subjected to a second channel estimation process that includes signal filtering to obtain the second estimation results corresponding to each port. Based on the intermediate value and the second estimation result corresponding to each port, the noise value representing the target channel noise is calculated; Based on the noise value, channel equalization processing is performed on the signal to be processed.

6. The device according to claim 5, characterized in that, The calculation of the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port specifically includes: The second estimation results corresponding to each port are processed for channel reconstruction to obtain the channel reconstruction results. Subtracting the intermediate value from the channel reconstruction result yields the noise value representing the target channel noise.

7. The device according to claim 6, characterized in that, The channel reconstruction process, which involves performing channel reconstruction on the second estimation results corresponding to each port, to obtain the channel reconstruction results, specifically includes: For each port, based on the port orthogonal code, the sign of each sub-estimation result corresponding to that port is adjusted, wherein each sub-estimation result corresponds to a frequency domain position in the signal to be processed; For each frequency domain location, channel reconstruction processing is performed on each sub-estimation result corresponding to different ports after sign adjustment, to obtain the channel reconstruction sub-result corresponding to that frequency domain location; Obtain the channel reconstruction result, which includes the channel reconstruction sub-results corresponding to each frequency domain position.

8. The device according to any one of claims 5-7, characterized in that, The channel equalization process performed on the signal to be processed based on the noise value specifically includes: The interference covariance matrix is ​​obtained by multiplying the noise values ​​together. Based on the interference covariance matrix, channel equalization processing is performed on the signal to be processed.

9. A noise estimation and channel equalization device, characterized in that, Applied to the receiving end, the device includes: The first estimation processing module is used to perform a first channel estimation process on the signal to be processed, which does not include signal filtering processing but includes multi-port separation processing. It obtains an intermediate value obtained before multi-port separation processing in the first channel estimation process, and a first estimation result corresponding to each port obtained after the first channel estimation process is completed. The signal to be processed is a signal that is sent to the receiving end through the target channel after the transmitting end performs multi-port multiplexing processing on the signal. The intermediate value is the value obtained after the conjugate multiplication calculation included in the first channel estimation process on the signal to be processed. The second estimation processing module is used to perform second channel estimation processing, which includes signal filtering, on the first estimation results corresponding to each port to obtain the second estimation results corresponding to each port. The noise value calculation module is used to calculate the noise value representing the target channel noise based on the intermediate value and the second estimation result corresponding to each port; The channel equalization module is used to perform channel equalization processing on the signal to be processed based on the noise value.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-4.

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