Signal processing method and device, computer program product and readable storage medium

Abstract

The invention discloses a signal processing method and device, a computer program product and a readable storage medium. The signal processing method comprises the following steps: acquiring an interference covariance matrix of an ith REG bundle; based on the interference covariance matrix of the ith REG bundle and the interference covariance matrix of the M historical REG bundles, obtaining the noise interference correlation between the current antennas and the current noise interference power; the historical REG bundle is an REG bundle which is located in front of the ith REG bundle in the current time slot; based on the interference covariance matrix of the ith REG bundle, obtaining the noise interference correlation between the current antennas and the current noise interference power; and determining a target interference elimination algorithm for performing interference elimination based on the switching threshold. By adopting the scheme, the interference detection accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a signal processing method, an apparatus, a computer program product, and a readable storage medium. Background Art

[0002] In a wireless communication system, when a terminal device has multiple receiving antennas, in order to maximize the signal-to-interference plus noise ratio (SINR) of the signals combined by the multiple receiving antennas, the maximum ratio combining (MRC) algorithm or the interference rejection combining (IRC) algorithm is usually used to combine the signals received by the multiple antennas.

[0003] In the prior art, usually taking a resource element group bundle (REG bundle) as a unit, the interference covariance matrix of each received REG bundle is obtained. Based on the interference covariance matrix of a single REG bundle, the target interference cancellation algorithm to be adopted is determined as the maximum ratio combining algorithm or the interference rejection combining algorithm.

[0004] However, in the prior art, when the size of the REG bundle is small, since the number of samples for calculating the interference covariance matrix of the REG bundle is small, the target interference cancellation algorithm cannot be accurately determined, thereby resulting in poor accuracy of interference detection and affecting the performance of multi-receiving antenna combination. Summary of the Invention

[0005] The purpose of the present invention is to provide at least a signal processing method, an apparatus, a computer program product, and a readable storage medium, which can improve the accuracy of interference detection and the performance of multi-receiving antenna combination.

[0006] In a first aspect, the present invention provides a signal processing method, including: obtaining an interference covariance matrix of the i-th resource element group bundle (REG bundle) in a current time slot; i is a positive integer and 1≤i≤N, where N is the total number of REG bundles in the current time slot; based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles, obtaining the current inter-antenna noise interference correlation and the current noise interference power; the historical REG bundles are the REG bundles in the current time slot that are before the i-th REG bundle, and M is a positive integer and M < i; based on the current inter-antenna noise interference correlation and the current noise interference power, determining a switching threshold; based on the switching threshold, determining a target interference cancellation algorithm, where the target interference cancellation algorithm includes any one of the following: maximum ratio combining algorithm, interference suppression combining algorithm.

[0007] Based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles, the current inter-antenna noise interference correlation and the current noise interference power are obtained, and then the switching threshold is determined, and the target interference cancellation algorithm is determined based on the switching threshold. By determining the switching threshold through the interference covariance matrices corresponding to M + 1 REG bundles, the influence of the error of the interference covariance matrix corresponding to a single REG bundle on determining the target interference cancellation algorithm can be reduced, the accuracy of interference detection can be improved, and thus the performance of multi-receiving antenna combining can be improved.

[0008] Optionally, the M historical REG bundles are: the M REG bundles received before obtaining the i-th REG bundle.

[0009] Optionally, the current inter-antenna noise interference correlation is characterized by a first mean value, and the current noise interference power is characterized by a second mean value; the first mean value is: the mean value of the modulus values of the non-diagonal elements of the interference covariance matrices of the i-th REG bundle and the M historical REG bundles; the second mean value is: the mean value of the diagonal elements of the interference covariance matrices of the i-th REG bundle and the M historical REG bundles.

[0010] Optionally, the determining the switching threshold based on the current inter-antenna noise interference correlation and the current noise interference power includes: determining the switching threshold based on the ratio of the current inter-antenna noise interference correlation to the current noise interference power.

[0011] Optionally, determining the handover threshold based on the ratio of the current inter-antenna noise interference correlation to the current noise interference power includes: when the current inter-antenna noise interference correlation is greater than a first product, determining the handover threshold as a preset first threshold; when the current inter-antenna noise interference correlation is less than or equal to a second product, determining the handover threshold as a preset third threshold; when the current inter-antenna noise interference correlation is between the first product and the second product, determining the handover threshold as a preset second threshold; wherein the first threshold is less than the second threshold, and the second threshold is less than the third threshold; the first product is the product of the current noise interference power and a first factor, the second product is the product of the current noise interference power and a second factor, and the first factor is greater than or equal to the second factor.

[0012] Based on the current inter-antenna noise interference correlation and the current noise interference power, determine the corresponding handover threshold. If the current inter-antenna noise interference correlation is large, a smaller handover threshold can be selected, and then it is easier to select the interference suppression combining algorithm as the target interference cancellation algorithm; if the current inter-antenna noise interference correlation is small, a larger handover threshold can be selected, and then it is easier to select the maximum ratio combining algorithm as the target interference cancellation algorithm. Thus, the target interference cancellation algorithm is adaptively switched to improve the accuracy of interference detection.

[0013] Optionally, the first factor is inversely correlated with the value of M + 1, and the second factor is positively correlated with the value of M + 1.

[0014] Optionally, the first threshold is inversely correlated with the value of M + 1, and the third threshold is positively correlated with the value of M + 1.

[0015] Optionally, determining the target interference cancellation algorithm based on the handover threshold includes: determining the target interference covariance matrix based on the handover threshold; determining the target interference cancellation algorithm based on the handover threshold, the target inter-antenna noise interference correlation, and the target noise interference power; the target inter-antenna noise interference correlation is the inter-antenna noise interference correlation of the target interference covariance matrix, and the target noise interference power is the noise interference power of the target interference covariance matrix.

[0016] Optionally, determining the target interference cancellation algorithm based on the handover threshold, the target inter-antenna noise interference correlation, and the target noise interference power includes: when the product of the target noise interference power and the handover threshold is less than or equal to the target inter-antenna noise interference correlation, determining the target interference cancellation algorithm as the interference suppression combining algorithm; when the product of the target noise interference power and the handover threshold is greater than the target inter-antenna noise interference correlation, determining the target interference cancellation algorithm as the maximum ratio combining algorithm.

[0017] Optionally, determining the target interference covariance matrix based on the switching threshold includes: if the switching threshold is the first threshold, the target interference covariance matrix is: the mean of the interference covariance matrices corresponding to K1 resource blocks in the i-th REG bundle, where K1 is a positive integer; if the switching threshold is the second threshold, the target interference covariance matrix is: the mean of the interference covariance matrices corresponding to K2 resource blocks in the i-th REG bundle, where K2 is a positive integer; if the switching threshold is the third threshold, the target interference covariance matrix is: the mean of the interference covariance matrices corresponding to K3 resource blocks in the i-th REG bundle, where K3 is a positive integer, and K1 ≤ K2 ≤ K3.

[0018] If the correlation of the noise interference between the current antennas is relatively large, then with a smaller granularity, such as at the resource block granularity, based on the interference covariance matrix with a smaller granularity and the first threshold, determine the target interference cancellation algorithm; if the power of the noise interference of the current antennas is relatively large, then with a larger granularity, such as at the REG bundle granularity, based on the interference covariance matrix with a larger granularity and the third threshold, determine the target interference cancellation algorithm. Thus, the target interference cancellation algorithm can be determined more accurately.

[0019] Optionally, determining the interference covariance matrix of the i-th REG bundle includes: taking the arithmetic mean of the interference covariance matrices of each resource block in the i-th REG bundle as the interference covariance matrix of the i-th REG bundle.

[0020] In a second aspect, the present invention further provides a signal processing apparatus, including: a first acquisition unit configured to acquire the interference covariance matrix of the i-th resource unit group bundle (REG bundle) in the current time slot; i is a positive integer and 1 ≤ i ≤ N, where N is the total number of REG bundles in the current time slot; a second acquisition unit configured to acquire the current correlation of the noise interference between the antennas and the current noise interference power based on the interference covariance matrix of the i-th REG bundle; the historical REG bundle is the REG bundle in the current time slot that is before the i-th REG bundle, M is a positive integer and M < i; a first determination unit configured to determine a switching threshold based on the current correlation of the noise interference between the antennas and the current noise interference power; a second determination unit configured to determine a target interference cancellation algorithm based on the switching threshold, and the target interference cancellation algorithm includes any one of the following: maximum ratio combining algorithm, interference suppression combining algorithm.

[0021] In a third aspect, the present invention further provides a computer-readable storage medium, which is a non-volatile storage medium or a non-transitory storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the steps of any one of the above-mentioned signal processing methods.

[0022] In a fourth aspect, the present invention further provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, they implement the steps of the signal processing method provided in any one of the above embodiments.

[0023] In a fifth aspect, the present invention further provides another signal processing device, including a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor runs the computer program, it executes the steps of any one of the above-mentioned signal processing methods. Description of the Drawings

[0024] Figure 1 is a flowchart of a signal processing method in an embodiment of the present invention;

[0025] Figure 2 is a flowchart of another signal processing method in an embodiment of the present invention;

[0026] Figure 3 is a schematic structural diagram of a signal processing device in an embodiment of the present invention. Detailed Embodiments

[0027] In the prior art, usually based on the interference covariance matrix of a single REG bundle, the determined target interference cancellation algorithm is the maximum ratio combining algorithm or the interference suppression combining algorithm. However, when the size of a single REG bundle is small, there is a large error in the obtained interference covariance matrix, which in turn leads to the determination of an incorrect target interference cancellation algorithm, and the accuracy of interference detection is poor.

[0028] In the embodiments of the present invention, based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles, the current inter-antenna noise interference correlation and the current noise interference power are obtained, and then the switching threshold is determined. Based on the switching threshold, the target interference cancellation algorithm is determined. By determining the switching threshold through the interference covariance matrices corresponding to M + 1 REG bundles, the influence of the error of the interference covariance matrix corresponding to a single REG bundle on the determination of the target interference cancellation algorithm can be reduced, the accuracy of interference detection can be improved, and thus the performance of multi-receive antenna combining can be improved.

[0029] To make the above objects, features, and beneficial effects of the present invention more obvious and understandable, the following provides a detailed description of specific embodiments of the present invention with reference to the accompanying drawings.

[0030] The terminal device described in the embodiments of the present application is a device with wireless communication capabilities, and can also be referred to as a terminal, mobile station (MS), mobile terminal (MT), access terminal device, in-vehicle terminal device, industrial control terminal device, user equipment (UE) unit, UE station, mobile station, remote station, remote terminal device, mobile device, wireless communication device, UE agent, or UE device, etc. The UE can be fixed or mobile. It should be noted that the UE can support at least one wireless communication technology, such as LTE, NR, etc. Exemplarily, the UE can be a mobile phone, tablet (pad), desktop computer, laptop computer, all-in-one computer, in-vehicle terminal, virtual reality (VR) UE, augmented reality (AR) UE, wireless terminal in industrial control, wireless terminal in self-driving, wireless terminal in remote medical surgery, wireless terminal in smart grid, wireless terminal in transportation safety, wireless terminal in smart city, wireless terminal in smart home, cellular phone, cordless phone, session initiation protocol (SIP) phone, wireless local loop (WLL) station, personal digital assistant (PDA), handheld device with wireless communication capabilities, computing device, or other processing devices connected to a wireless modem, wearable device, UE in a future mobile communication network, or UE in a future evolved public land mobile network (PLMN), etc. In some embodiments of the present application, the UE can also be a device with transceiver capabilities, such as a chip system. Among them, the chip system can include a chip and can also include other discrete devices.

[0031] In the embodiments of the present application, a network device is a device that provides wireless communication functions for terminal devices, and can also be referred to as a radio access network (RAN) device, or an access network element, an access network device, etc. Among them, the network device can support at least one wireless communication technology, such as LTE, NR, etc. Exemplarily, the network device includes, but is not limited to: the next-generation base station (generation node B, gNB) in 5G, evolved node B (eNB), radio network controller (RNC), node B (NB), base station controller (BSC), base transceiver station (BTS), home base station (e.g., home evolved node B, or home node B, HNB), baseband unit (BBU), transmitting and receiving point (TRP), transmitting point (TP), mobile switching center, etc. The network device can also be a wireless controller, a centralized unit (CU), and / or a distributed unit (DU) in a cloud radio access network (CRAN) scenario, or the network device can be a relay station, an access point, a vehicle-mounted device, a terminal device, a wearable device, and a network device in future mobile communications or a network device in a future evolved PLMN, etc. In some embodiments, the network device can also be a device with the function of providing wireless communication for terminal devices, such as a chip system. Exemplarily, the chip system can include a chip and can also include other discrete devices.

[0032] In some embodiments, the network device can also communicate with an Internet Protocol (IP) network, such as the Internet, a private IP network, or other data networks, etc.

[0033] Embodiments of the present invention provide a signal processing method. Refer to Figure 1 , and the following will be described in detail through specific steps.

[0034] In a specific implementation, the signal processing method provided in the following steps 101 to 104 can be executed by a chip with data processing capabilities in the terminal device (such as a baseband chip, etc.), or by a chip module with data processing capabilities in the terminal device (such as a baseband chip module, etc.), or by the terminal device. The following takes the terminal device executing the signal processing method provided in steps 101 to 104 as an example for illustration.

[0035] Step 101: Obtain the interference covariance matrix of the i-th REG bundle in the current time slot.

[0036] In a specific implementation, a resource element group bundle (REG bundle) may include 2, 3, or 6 resource element groups (REGs). A REG may include 12 resource elements (REs), that is, a REG is composed of 12 subcarriers in the frequency domain and one symbol in the time domain. An RE is the smallest resource unit in wireless communication and is composed of one subcarrier in the frequency domain and one symbol in the time domain.

[0037] In an embodiment of the present invention, when the terminal device receives the physical downlink control channel (PDCCH) data of the i-th REG bundle in the current time slot, it can obtain the interference covariance matrix of the i-th REG bundle.

[0038] In an embodiment of the present invention, i is a positive integer and N≥i>0. That is to say, the value of the above-mentioned i starts from 1.

[0039] In other words, the first REG bundle in the current time slot is the first received REG bundle in the current time slot, and the identifier of the first REG bundle is 1, that is, the first REG bundle can be represented as REG bundle 1. Correspondingly, the second REG bundle in the current time slot is the second received REG bundle in the current time slot, and so on.

[0040] In a specific implementation, the terminal device can calculate the interference covariance matrix of each resource block (RB) in the i-th REG bundle. Calculate the arithmetic mean of the average covariance matrices corresponding to all RBs in the i-th REG bundle as the interference covariance matrix of the i-th REG bundle.

[0041] For the interference covariance matrix of the m-th RB in the i-th REG bundle It can be:

[0042] ; (1)

[0043] Wherein, is the receiving antenna index, 0 ≤ < , is the total number of receiving antennas.

[0044] Specifically, the interference covariance matrix of the m-th RB can also be characterized by the following formula (2):

[0045] ; (2)

[0046] Wherein, is the number of receiving antennas of the terminal device, is the number of orthogonal frequency division multiplexing (OFDM) symbols occupied by the PDCCH channel, is the number of subcarriers occupied by the demodulation reference signal (DMRS) in one RB, is the received noise interference vector on the k-th DMRS RE and the l-th OFDM symbol in the m-th RB, is the complex conjugate transpose of.

[0047] The specific arithmetic expressions for determining the interference covariance matrix of the i-th REG bundle and the m-th RB can refer to the prior art, and the present invention does not improve the specific acquisition algorithm for the interference covariance matrix of the m-th RB in the i-th REG bundle.

[0048] Based on the above (1) and (2), the interference covariance matrices of all RBs in the i-th REG bundle can be obtained. The interference covariance matrix of the i-th REG bundle is obtained based on the arithmetic mean of the interference covariance matrices of all RBs in the i-th REG bundle.

[0049] In some embodiments, the interference covariance matrix of the i-th REG bundle obtained based on the arithmetic mean of the interference covariance matrices of all RBs in the i-th REG bundle is expressed as: .

[0050] Step 102, based on the interference covariance matrix of the i-th REG bundle, obtain the current inter-antenna noise interference correlation and the current noise interference power.

[0051] In an embodiment of the present invention, the terminal device may obtain the current inter-antenna noise interference correlation and the current noise interference power corresponding to the current time slot based on the interference covariance matrix of the i-th REG bundle in the current time slot.

[0052] In a specific implementation, the terminal device may determine the current inter-antenna noise interference correlation and the current noise interference power based on the interference covariance matrices of M historical REG bundles and the interference covariance matrix of the i-th REG bundle.

[0053] The above-mentioned historical REG bundles may refer to: the REG bundles before the i-th REG bundle in the current time slot. M is a positive integer and M < i. The M historical REG bundles are the M REG bundles received before obtaining the i-th REG bundle.

[0054] That is to say, the terminal device may obtain the current inter-antenna noise interference correlation and the current noise interference power based on the interference covariance matrices of M + 1 REG bundles in the current time slot.

[0055] For example, in the current time slot, the PDCCH data of the 3rd REG bundle is received. The interference covariance matrix of the 3rd REG bundle and the interference covariance matrix of the 2nd REG bundle previously obtained in the current time slot are used to determine the current inter-antenna noise interference correlation and the current noise interference power by adopting Step 101.

[0056] Those skilled in the art can understand that the above-mentioned historical REG bundles are relative to the current i-th REG bundle. When i = 1, there is no historical REG bundle for the i-th REG bundle. When i = 2, the historical REG bundle corresponding to the i-th REG bundle is the 1st REG bundle. And so on.

[0057] In a specific implementation, the above-mentioned M historical REG bundles may be: the first i REG bundles in the current time slot. That is to say, the current inter-antenna noise interference correlation and the current noise interference power are determined based on the interference covariance matrices of the 1st REG bundle to the i-th REG bundle in the current time slot.

[0058] For example, in the current time slot, for the 4th REG bundle, the historical REG bundles are the 1st, 2nd, and 3rd REG bundles in the current time slot.

[0059] In the embodiments of the present invention, the current inter-antenna noise interference correlation can be characterized by a first mean value, and the current noise interference power can be characterized by a second mean value, where:

[0060] The first mean value can be: the mean value of the modulus of the non-diagonal elements of the interference covariance matrix of the i-th REG bundle and M historical REG bundles;

[0061] The second mean value can be: the mean value of the diagonal elements of the interference covariance matrix of the i-th REG bundle and M historical REG bundles.

[0062] Specifically, based on the interference covariance matrix of the i-th REG bundle, the mean value of the modulus of the non-diagonal elements of the interference covariance matrix of the i-th REG bundle can be calculated; and based on the interference covariance matrices of M historical REG bundles, the mean values of the modulus of the non-diagonal elements of the interference covariance matrices of M historical REG bundles can be calculated respectively. Thus, the moduli of the non-diagonal elements of M + 1 interference covariance matrices are obtained. Furthermore, the arithmetic mean value of the moduli of the non-diagonal elements of M + 1 interference covariance matrices is the above-mentioned first mean value.

[0063] Correspondingly, based on the interference covariance matrix of the i-th REG bundle, the diagonal elements of the interference covariance matrix of the i-th REG bundle can be calculated; correspondingly, based on the interference covariance matrices of M historical REG bundles, the diagonal elements of the interference covariance matrices of M historical REG bundles can be calculated; furthermore, the arithmetic mean value of the diagonal elements of M + 1 interference covariance matrices is the above-mentioned second mean value.

[0064] For example, the terminal device receives PDCCH data of the 3rd REG bundle in the current time slot. The 2 historical REG bundles are the 2nd REG bundle in the current time slot and the 1st REG bundle in the current time slot. When the number of receiving antennas is 2, based on the modulus value P3 of the non - diagonal element of the interference covariance matrix of the 3rd REG bundle in the current time slot, the modulus value P2 of the non - diagonal element of the interference covariance matrix of the 2nd REG bundle in the current time slot, and the modulus value P1 of the non - diagonal element of the interference covariance matrix of the 1st REG bundle in the current time slot, the first mean value is obtained as (P1 + P2 + P3) / 3, which is the current inter - antenna noise interference correlation; correspondingly, based on the diagonal elements of the interference covariance matrix of the 3rd REG bundle in the current time slot, the diagonal elements of the interference covariance matrix of the 2nd REG bundle in the current time slot, and the diagonal elements of the interference covariance matrix of the 1st REG bundle in the current time slot, the second mean value is obtained, which is the current noise interference power.

[0065] In some embodiments, when the M historical REG bundles are the first i REG bundles in the current time slot, the current inter - antenna noise interference correlation is:

[0066] ; (3)

[0067] The current noise interference power is:

[0068] ; (4)

[0069] Thus, the current inter - antenna noise interference correlation and the current noise interference power are obtained.

[0070] Step 103: Determine the handover threshold based on the current inter - antenna noise interference correlation and the current noise interference power.

[0071] In the embodiments of the present invention, the terminal device can determine the handover threshold based on the interference intensity. For different interference intensities, corresponding handover thresholds can be determined. The handover thresholds corresponding to different interference intensities can be different. The above - mentioned handover threshold refers to the threshold for switching from the maximum ratio combining algorithm to the interference suppression combining algorithm, and / or the threshold for switching from the interference suppression combining algorithm to the maximum ratio combining algorithm.

[0072] In specific implementation, if it is detected that the correlation of the current inter-antenna noise interference is relatively large, a smaller handover threshold can be selected; if it is detected that the current noise interference power is relatively large, a larger handover threshold can be selected. The larger the handover threshold is, the easier it is for the target interference cancellation algorithm to be judged as the maximum ratio combining algorithm; correspondingly, the smaller the handover threshold is, the easier it is for the target interference cancellation algorithm to be judged as the interference rejection combining algorithm.

[0073] In specific implementation, the handover threshold can be determined based on the ratio of the current inter-antenna noise interference correlation to the current noise interference power. The ratio of the current inter-antenna noise interference correlation to the current noise interference power can be inversely correlated with the handover threshold.

[0074] Alternatively, the ratio of the current inter-antenna noise interference correlation to the current noise interference power can also be divided into multiple different value segments, and for each value segment, a corresponding handover threshold can be set. The handover thresholds corresponding to different value segments can all be different, or some can be different. For the value segment with a larger value, the corresponding handover threshold is not greater than that of the value segment with a smaller value.

[0075] For example, if three value segments are set, three handover thresholds can be correspondingly set. The minimum value of value segment 1 is the maximum value of value segment 2, and the minimum value of value segment 2 is the maximum value of value segment 3. The handover threshold corresponding to value segment 1 is not greater than the handover threshold corresponding to value segment 2; the handover threshold corresponding to value segment 2 is not greater than the handover threshold corresponding to value segment 3.

[0076] In some embodiments, if the current inter-antenna noise interference correlation is greater than the first product, the handover threshold can be determined as the preset first threshold; if the current inter-antenna noise interference correlation is not greater than the first product, the handover threshold can be determined as the preset second threshold, and the first threshold is not greater than the second threshold. The above-mentioned first product is the product of the current noise interference power and the first factor. The first factor can be preset.

[0077] For example, if > ×Th D_W1 , the handover threshold is determined as the first threshold Th D1 ; if ≤ ×T hD_W1 , the handover threshold is determined as the second threshold Th D2 ; Th D1 ≤Th D2 .

[0078] In some other embodiments, if the current inter-antenna noise interference correlation is greater than the first product, the handover threshold is determined as the preset first threshold Th D1If the current correlation of the noise interference between antennas is less than or equal to the second product, determine that the handover threshold is the preset third threshold Th D3 If the current correlation of the noise interference between antennas is between the first product and the second product, determine that the handover threshold is the preset second threshold Th D2 Th D1 ≤Th D2 ≤Th D3 .

[0079] Among them, the first product is the product of and the first factor Th D_W1 , and the second product is the product of and the second factor Th D_W2 , Th D_W1 ≥Th D_W2 .

[0080] Specifically, if > ×Th D_W1 , then determine that the handover threshold Th D is Th D1 ; if ≤ ×Th D_W2 , then determine that the handover threshold Th D is Th D3 ; if ×Th D_W2 < ≤ ×Th D_W1 , then determine that the handover threshold Th D is Th D2 .

[0081] In a specific implementation, the values of the above Th D_W1 , Th D_W2 , Th D1 , Th D2 and Th D3 can be associated with M or i.

[0082] In some embodiments, Th D1 , Th D2 and Th D3 can be fixed values. The first factor Th D_W1 is inversely correlated with M + 1, that is, as the value of M increases (correspondingly, the value of M + 1 also increases), the terminal device can select a smaller first factor Th D_W1 ; as the value of M decreases (correspondingly, the value of M + 1 also decreases), the terminal device can select a larger first factor Th D_W1 .

[0083] The second factor Th D_W2 is positively correlated with M + 1, that is, as the value of M increases, the terminal device can select a larger second factor Th D_W2 ; as the value of M decreases, the terminal device can select a smaller second factor Th D_W2 .

[0084] In some other embodiments, Th D1 is negatively correlated with M + 1, that is, when the value of M increases, the terminal device can select a smaller Th D1 ; when the value of M decreases, the terminal device can select a larger Th D1 . Th D3 is positively correlated with M + 1, that is, when the value of M increases, the terminal device can select a larger Th D3 ; when the value of M decreases, the terminal device can select a smaller Th D3 .

[0085] Step 104, determine the target interference cancellation algorithm based on the handover threshold.

[0086] In the embodiments of the present invention, the terminal device can select the target interference cancellation algorithm based on the determined handover threshold. The target interference cancellation algorithm can include any one of the following: maximum ratio combining algorithm, interference suppression combining algorithm.

[0087] In the embodiments of the present invention, the terminal device can determine the target interference covariance matrix based on the handover threshold. Further, the terminal device determines the inter-antenna noise interference correlation corresponding to the target interference covariance matrix (hereinafter simply referred to as the target inter-antenna noise interference correlation) and the noise interference power corresponding to the target interference covariance matrix (hereinafter simply referred to as the target noise interference power) based on the target interference covariance matrix. The terminal device determines the target interference cancellation algorithm based on the handover threshold, the target inter-antenna noise interference correlation, and the target noise interference power.

[0088] In specific implementation, if the product of the target noise interference power and the handover threshold is less than or equal to the target inter-antenna noise interference correlation, the terminal device can determine that the target interference cancellation algorithm is the interference suppression combining algorithm; if the product of the target noise interference power and the handover threshold is greater than the target inter-antenna noise interference correlation, the terminal device can determine that the target interference cancellation algorithm is the maximum ratio combining algorithm.

[0089] In the embodiments of the present invention, if the terminal device determines that the handover threshold is the third threshold, it means that the current colored interference power is relatively small, and a larger-granularity interference covariance matrix can be used as the target interference covariance matrix for determining the target interference cancellation algorithm.

[0090] In a specific implementation, the arithmetic mean of the interference covariance matrices of K3 RBs in the i-th REG bundle can be used as the target interference covariance matrix with a granularity of K3 RBs.

[0091] In some embodiments, with a granularity of REG bundle, the interference covariance matrix of the i-th REG bundle is used as the target interference covariance matrix.

[0092] When using the interference covariance matrix of the i-th REG bundle as the target interference covariance matrix with a granularity of REG bundle, a target interference cancellation algorithm corresponding to the i-th REG bundle is determined based on a third threshold, the current inter-antenna noise interference correlation, and the current noise interference power.

[0093] If the product of the current noise interference power and the third threshold is less than or equal to the current inter-antenna noise interference correlation, the target interference cancellation algorithm is determined to be the interference suppression combining algorithm; if the product of the current noise interference power and the third threshold is greater than the current inter-antenna noise interference correlation, the target interference cancellation algorithm is determined to be the maximum ratio combining algorithm.

[0094] In some embodiments, if the terminal device determines that the handover threshold is the first threshold, it means that the current colored interference power is relatively large, and a relatively small granularity interference covariance matrix can be used as the target interference covariance matrix.

[0095] For example, with a granularity of RB, the interference covariance matrix of the RB can be used as the target interference covariance matrix.

[0096] Alternatively, the arithmetic mean of the interference covariance matrices of K1 RBs in the i-th REG bundle can be used as the target interference covariance matrix with a granularity of K1 RBs in the i-th REG bundle. K1 ≤ K3. Both K1 and K3 are positive integers.

[0097] In other embodiments, if the terminal device determines that the handover threshold is the second threshold, the arithmetic mean of the interference covariance matrices of K2 RBs in the i-th REG bundle can be used as the target interference covariance matrix with a granularity of K2 RBs in the i-th REG bundle. K1 ≤ K2 ≤ K3.

[0098] The value of K3 can be the total number K of resource blocks in the i-th REG bundle, or can be less than the total number K of resource blocks in the i-th REG bundle, or can also be greater than the total number K of resource blocks in the i-th REG bundle.

[0099] The terminal device determines the target noise interference correlation between target antennas and the target noise interference power based on the target interference covariance matrix. The terminal device determines the target interference cancellation algorithm based on the first threshold, the target noise interference correlation between target antennas, and the target noise interference power.

[0100] Specifically, if the product of the target noise interference power and the first threshold is less than or equal to the target noise interference correlation between target antennas, the terminal device may determine that the target interference cancellation algorithm is the interference suppression combining algorithm; if the product of the target noise interference power and the first threshold is greater than the target noise interference correlation between target antennas, the terminal device may determine that the target interference cancellation algorithm is the maximum ratio combining algorithm.

[0101] In some embodiments, if the handover threshold is the third threshold, the arithmetic mean of the interference covariance matrices of K3 RBs in the i-th REG bundle may be used as the target interference covariance matrix with a granularity of K3 RBs. Alternatively, if the handover threshold is the first threshold, the arithmetic mean of the interference covariance matrices of K1 RBs in the i-th REG bundle may be used as the target interference covariance matrix with a granularity of K1 RBs.

[0102] When the handover threshold is the third threshold, the terminal device determines the target interference cancellation algorithm based on the third threshold, the target noise interference correlation between target antennas, and the target noise interference power.

[0103] In the embodiments of the present invention, after the terminal device determines the target interference cancellation algorithm, it can use the corresponding target interference cancellation algorithm to receive data.

[0104] The following uses examples to illustrate the signal processing method provided in the above steps 101 to 104.

[0105] Refer to Figure 2 , another signal processing method in the embodiments of the present invention is given, and the following is described in detail through specific steps.

[0106] Step 201, calculate the interference covariance matrix of each RB in the i-th REG bundle in the current time slot.

[0107] In specific implementation, the interference covariance matrix of each RB in the i-th REG bundle in the current time slot can be calculated with reference to the above formula (1) and formula (2).

[0108] Step 202, obtain the interference covariance matrix of the i-th REG bundle in the current time slot.

[0109] In a specific implementation, calculate the arithmetic mean of the interference covariance matrices of all RBs obtained in calculation step 201 as the interference covariance matrix of the i-th REG bundle in the current time slot.

[0110] Step 203, obtain the mean value of the modulus of the non-diagonal elements of the interference covariance matrices of the i REG bundles. And the mean value of the diagonal elements. .

[0111] In a specific implementation, the mean value of the modulus of the non-diagonal elements of the interference covariance matrices of the i REG bundles can be obtained as the current inter-antenna noise interference correlation; the mean value of the diagonal elements of the interference covariance matrices of the i REG bundles can be obtained as the current noise interference power.

[0112] Step 204, determine the first factor and the second factor.

[0113] In a specific implementation, based on the value of i, determine the first factor Th D_W1 and the second factor Th D_W2 . As the value of i increases, the value of the first factor Th D_W1 decreases accordingly, and the value of the second factor Th D_W2 increases accordingly.

[0114] In some embodiments, steps can be set for the first factor Th D_W1 and the second factor Th D_W2 respectively. When the value of i increases by 1, the value of the first factor increases by the first step Δ 1 , and the value of the second factor decreases by the second step Δ 2 . Both the first step Δ 1 and the second step Δ 2 are positive numbers.

[0115] For example, when i = 2, the value of the first factor Th D_W1 is A, and the value of the second factor Th D_W2 is B. When i = 3, the value of the first factor Th D_W1 is updated to A + Δ 1 , and the value of the second factor Th D_W2 is updated to B - Δ 2 .

[0116] Step 205, judge whether is greater than ×Th D_W1 .

[0117] In a specific implementation, if > ×ThD_W1 , step 206 is executed; otherwise, step 207 is executed.

[0118] Step 206, determine that the handover threshold is the first threshold Th D1 .

[0119] Step 207, judge whether it is less than or equal to × Th D_W2 .

[0120] In a specific implementation, if ≤ × Th D_W2 , step 208 is executed; otherwise, step 209 is executed.

[0121] Step 208, determine that the handover threshold is the third threshold Th D3 .

[0122] Step 209, determine that the handover threshold is the second threshold Th D2 .

[0123] The above first threshold Th D1 , second threshold Th D2 and third threshold Th D3 have the following magnitude relationship: Th D1 ≤ Th D2 ≤ Th D3 .

[0124] Step 210, determine the target interference covariance matrix.

[0125] In a specific implementation, if the handover threshold Th D is the first threshold, the target interference covariance matrix can be the interference covariance matrix of the i-th REG bundle; if the handover threshold Th D is the second threshold or the third threshold, the target interference covariance matrix is the interference covariance matrix of the j-th resource block of the i-th REG bundle.

[0126] The mean of the non-diagonal elements of the target interference covariance matrix is , and the mean of the diagonal elements is .

[0127] Step 211, judge whether it is less than × Th D .

[0128] If < × Th D , step 212 is executed; if ≥ ×Th D , step 213 is then executed.

[0129] Step 212: Determine that the target interference cancellation algorithm is the maximum ratio combining algorithm.

[0130] Step 213: Determine that the target interference cancellation algorithm is the interference suppression combining algorithm.

[0131] In summary, based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles, the current inter-antenna noise interference correlation and the current noise interference power are obtained, and then the switching threshold is determined. Based on the switching threshold, the target interference cancellation algorithm is determined. By determining the switching threshold through the interference covariance matrices corresponding to M + 1 REG bundles, the influence of the error of the interference covariance matrix corresponding to a single REG bundle on determining the target interference cancellation algorithm can be reduced, the accuracy of interference detection can be improved, and thus the performance of multi-receiving antenna combining can be improved.

[0132] Refer to Figure 3 , a signal processing device 30 in an embodiment of the present invention is given, including: a first acquisition unit 301, a second acquisition unit 302, a first determination unit 303, and a second determination unit 304, where:

[0133] The first acquisition unit 301 is configured to acquire the interference covariance matrix of the i-th resource element group bundle (REG bundle) in the current time slot; i is a positive integer and 1 ≤ i ≤ N, and N is the total number of REG bundles in the current time slot;

[0134] The second acquisition unit 302 is configured to acquire the current inter-antenna noise interference correlation and the current noise interference power based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles; the historical REG bundle is the REG bundle before the i-th REG bundle in the current time slot, and M is a positive integer and M < i;

[0135] The first determination unit 303 is configured to determine a switching threshold based on the current inter-antenna noise interference correlation and the current noise interference power;

[0136] The second determination unit 304 is configured to determine a target interference cancellation algorithm based on the switching threshold, and the target interference cancellation algorithm includes any one of the following: the maximum ratio combining algorithm, the interference suppression combining algorithm.

[0137] In a specific implementation, the specific execution processes of the above-mentioned first acquisition unit 301, second acquisition unit 302, first determination unit 303, and second determination unit 304 may refer to steps 101 to 104 correspondingly, which will not be elaborated here.

[0138] In a specific implementation, the above-mentioned communication device 30 may correspond to a chip with data processing functions in a terminal device, or correspond to a chip module including a chip with data processing functions in a terminal device, or correspond to a terminal device.

[0139] In a specific implementation, for each module / unit included in each device and product described in the above embodiments, it may be a software module / unit, a hardware module / unit, or may be partially a software module / unit and partially a hardware module / unit.

[0140] For example, for each device and product applied to or integrated into a chip, each module / unit included therein may be implemented in a hardware manner such as a circuit, or at least some of the modules / units may be implemented in a software program manner, and the software program runs on a processor integrated inside the chip, and the remaining (if any) part of the modules / units may be implemented in a hardware manner such as a circuit; for each device and product applied to or integrated into a chip module, each module / unit included therein may be implemented in a hardware manner such as a circuit, and different modules / units may be located in the same component (such as a chip, a circuit module, etc.) or different components of the chip module, or at least some of the modules / units may be implemented in a software program manner, and the software program runs on a processor integrated inside the chip module, and the remaining (if any) part of the modules / units may be implemented in a hardware manner such as a circuit; for each device and product applied to or integrated into a terminal, each module / unit included therein may be implemented in a hardware manner such as a circuit, and different modules / units may be located in the same component (such as a chip, a circuit module, etc.) or different components inside the terminal, or at least some of the modules / units may be implemented in a software program manner, and the software program runs on a processor integrated inside the terminal, and the remaining (if any) part of the modules / units may be implemented in a hardware manner such as a circuit.

[0141] The embodiment of the present invention also provides a computer-readable storage medium, which is a non-volatile storage medium or a non-transitory storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the steps of the signal processing method provided in any of the above embodiments.

[0142] The embodiment of the present invention provides a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, they implement the steps of the signal processing method provided in any of the above embodiments.

[0143] An embodiment of the present invention further provides another signal processing device, including a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor runs the computer program, it executes the steps of the signal processing method provided in any of the above embodiments.

[0144] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium, and the storage medium can include: ROM, RAM, magnetic disk, optical disk, etc.

[0145] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention should be subject to the scope defined by the claims.

Claims

1. A signal processing method, characterized in that: include: Obtain the interference covariance matrix of the i-th resource unit group REG bundle in the current time slot; i is a positive integer and 1≤i≤N, N is the total number of REG bundles in the current time slot; Based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrices of M historical REG bundles, the current inter-antenna noise interference correlation and the current noise interference power are obtained; the historical REG bundle is the REG bundle before the i-th REG bundle in the current time slot, M is a positive integer and M <i; Determining a switching threshold based on the current inter-antenna noise interference correlation and the current noise interference power; Based on the switching threshold, a target interference cancellation algorithm is determined, and the target interference cancellation algorithm includes any one of the following: a maximum ratio combining algorithm and an interference suppression combining algorithm.

2. The signal processing method according to claim 1, characterized in that: The M historical REG bundles are: the M REG bundles received before obtaining the i-th REG bundle.

3. The signal processing method according to claim 1 or 2, characterized in that: The current inter-antenna noise interference correlation is characterized by a first mean value, and the current noise interference power is characterized by a second mean value; The first mean value is: the mean value of the module values ​​of the non-diagonal elements of the interference covariance matrix of the i-th REG bundle and the M historical REG bundles; The second mean value is: the mean value of the diagonal elements of the interference covariance matrix between the i-th REG bundle and the M historical REG bundles.

4. The signal processing method according to claim 1, characterized in that: The determining the switching threshold based on the current inter-antenna noise interference correlation and the current noise interference power includes: The switching threshold is determined based on a ratio of the current inter-antenna noise interference correlation to the current noise interference power.

5. The signal processing method according to claim 4, characterized in that: The determining the switching threshold based on the ratio of the current inter-antenna noise interference correlation to the current noise interference power includes: The current inter-antenna noise interference correlation is greater than the first product, and the switching threshold is determined to be a preset first threshold; The current inter-antenna noise interference correlation is less than or equal to the second product, and the switching threshold is determined to be a preset third threshold; The current inter-antenna noise interference correlation is between the first product and the second product, and the switching threshold is determined to be a preset second threshold; Among them, the first threshold is less than or equal to the second threshold, and the second threshold is less than or equal to the third threshold; the first product is the product of the current noise interference power and a first factor, the second product is the product of the current noise interference power and a second factor, and the first factor is greater than or equal to the second factor.

6. The signal processing method according to claim 5, characterized in that: The first factor is inversely correlated with the value of M+1, and the second factor is positively correlated with the value of M+1.

7. The signal processing method according to claim 5, characterized in that: The first threshold is inversely correlated with the value of M+1, and the third threshold is positively correlated with the value of M+1.

8. The signal processing method according to claim 5, characterized in that: The determining a target interference elimination algorithm based on the switching threshold includes: Based on the switching threshold, determining a target interference covariance matrix; Based on the switching threshold, the noise interference correlation between target antennas and the target noise interference power, a target interference elimination algorithm is determined; the noise interference correlation between target antennas is the noise interference correlation between antennas of the target interference covariance matrix, and the target noise interference power is the noise interference power of the target interference covariance matrix.

9. The signal processing method according to claim 8, characterized in that: The determining of a target interference elimination algorithm based on the switching threshold, the noise interference correlation between target antennas, and the target noise interference power includes: When the product of the target noise interference power and the switching threshold is less than or equal to the noise interference correlation between the target antennas, the target interference elimination algorithm is determined to be the interference suppression combining algorithm; when the product of the target noise interference power and the switching threshold is greater than the noise interference correlation between the target antennas, the target interference elimination algorithm is determined to be the maximum ratio combining algorithm.

10. The signal processing method according to claim 8 or 9, characterized in that: The determining of a target interference covariance matrix based on the switching threshold includes: If the switching threshold is the first threshold, the target interference covariance matrix is: the mean value of the interference covariance matrices corresponding to K1 resource blocks in the i-th REGbundle, where K1 is a positive integer; If the switching threshold is the second threshold, the target interference covariance matrix is: the mean value of the interference covariance matrices corresponding to K2 resource blocks in the i-th REGbundle, where K2 is a positive integer; If the switching threshold is the third threshold, the target interference covariance matrix is: the mean value of the interference covariance matrices corresponding to K3 resource blocks in the i-th REGbundle, K3 is a positive integer, and K1≤K2≤K3.

11. The signal processing method according to claim 1, characterized in that: The determining the interference covariance matrix of the i-th REG bundle includes: The arithmetic mean of the interference covariance matrix of each resource block in the i-th REG bundle is used as the interference covariance matrix of the i-th REG bundle.

12. A signal processing device, characterized in that: include: A first acquisition unit is used to acquire the interference covariance matrix of the i-th resource unit group REG bundle in the current time slot; i is a positive integer and 1≤i≤N, N is the total number of REG bundles in the current time slot; The second acquisition unit is used to obtain the current inter-antenna noise interference correlation and the current noise interference power based on the interference covariance matrix of the i-th REG bundle and the interference covariance matrix of M historical REG bundles; the historical REG bundle is the REG bundle located before the i-th REG bundle in the current time slot, M is a positive integer and M <i; A first determining unit, configured to determine a switching threshold based on the current inter-antenna noise interference correlation and the current noise interference power; The second determining unit is used to determine a target interference cancellation algorithm based on the switching threshold, where the target interference cancellation algorithm includes any one of the following: a maximum ratio combining algorithm and an interference suppression combining algorithm.

13. A computer-readable storage medium, wherein the computer-readable storage medium is a non-volatile storage medium or a non-transient storage medium, and a computer program is stored thereon, wherein: When the computer program is executed by a processor, the steps of the signal processing method according to any one of claims 1 to 11 are executed.

14. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the signal processing method according to any one of claims 1 to 11 are implemented.

15. A signal processing device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor runs the computer program, the steps of the signal processing method according to any one of claims 1 to 11 are performed.

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