Channel estimation method and device based on MU-MIMO communication system

Abstract

The invention discloses a channel estimation method and device based on an MU-MIMO communication system, which are used for improving the accuracy of channel estimation in an MU-MIMO communication scene in which a plurality of terminal devices with different time bias communicate at the same time. The method is applied to network side equipment, the network side equipment is connected with multiple pieces of terminal equipment UE, and the multiple pieces of UE multiplex the same time-frequency resource. The method comprises the following steps: performing channel estimation based on a signal received on a time-frequency resource to determine an initial channel matrix, and determining a time offset value of each UE based on the signal; performing time offset correction on the initial filter according to the time offset value of the first UE, and determining a target filter of the first UE; the first UE is any UE in the plurality of UEs; and filtering the initial channel matrix by using a target filter of the first UE to obtain a target channel matrix of the first UE.

Description

Technical Field

[0001] The present application relates to the field of MU-MIMO communication technology, and in particular to a channel estimation method and device based on a MU-MIMO communication system. Background Art

[0002] In a traditional communication system, the network side equipment can perform channel estimation on the signal from the terminal equipment (User Equipment, UE) to determine the channel matrix, and use the UE's time offset to correct the estimated channel matrix to obtain an accurate channel matrix. However, in a multi-user multiple input multiple output (Multi-User Multiple Input Multiple Output, MU-MIMO) communication system, multiple UEs can be multiplexed on the same time-frequency resources. If there is no time offset or the time offsets of each UE are the same, the air interface code division orthogonality can be solved by odd-even cancellation to obtain the channel matrix of each UE. However, in actual scenarios, the time offsets of each UE are different, so it is impossible to accurately obtain the channel matrix of each UE.

[0003] In order to solve the above problem, the relevant technology proposes to first use the odd-even cancellation method to perform initial de-orthogonalization processing on the estimated channel matrix, and then perform time offset compensation on the multiple channel matrices obtained after the de-orthogonalization processing. This method has many calculation steps, resulting in high channel estimation delay, and in scenarios that are sensitive to time offset, such as high modulation order or low signal-to-noise ratio, once the time offset estimation is wrong, it will lead to large channel matrix errors. Summary of the invention

[0004] The present application provides a channel estimation method and device based on a MU-MIMO communication system, so as to implement channel estimation in a MU-MIMO communication scenario.

[0005] In a first aspect, the present application proposes a channel estimation method based on a MU-MIMO communication system, the method being applied to a network side device, the network side device being connected to a plurality of terminal devices UE, the plurality of UEs multiplexing the same time-frequency resources, the method comprising:

[0006] Performing channel estimation based on the signal received on the time-frequency resource to determine an initial channel matrix, and determining a time offset value for each UE based on the signal;

[0007] Performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE; the first UE is any one of the multiple UEs;

[0008] The initial channel matrix is ​​filtered using a target filter of the first UE to obtain a target channel matrix of the first UE.

[0009] The initial filter is used to eliminate noise generated during the signal transmission process, and to identify the initial channel matrix corresponding to each UE from the initial channel matrix.

[0010] Based on the above scheme, there is no need to compensate the channel matrix of each terminal device for time offset. The time offset is embedded in the initial filter, so that the target filter obtained is a filter after time offset correction. Not only can the channel matrix of each terminal device be accurately separated from the initial channel matrix, but also noise filtering can be accurately performed to obtain an accurate channel matrix corresponding to each terminal device with noise removed. And because the scheme of the present application does not compensate the channel matrix of each terminal device for time offset, the step of time offset inversion can be omitted, and the obtained channel matrix can be directly used for equalization processing, which improves the efficiency of channel estimation.

[0011] In some embodiments, before performing time offset correction on the initial filter according to the time offset value of the first UE, the method further includes:

[0012] A preset window filter and a frequency domain filter are obtained, and the window filter and the frequency filter are synthesized to obtain the initial filter.

[0013] In some embodiments, the filtering the initial channel matrix using the target filter of the first UE to obtain the target channel matrix of the first UE includes:

[0014] Filtering the initial channel matrix using a window filter included in the target filter to obtain an initial channel matrix corresponding to the first UE;

[0015] An initial channel matrix corresponding to the first UE is filtered using a frequency domain filter included in the target filter to obtain a target channel matrix of the first UE.

[0016] In some embodiments, determining the time offset value of each UE based on the signal includes:

[0017] A pilot sequence of the first UE is obtained, and a correlation calculation is performed between the pilot sequence and the sequence of the signal to eliminate the pilot, so as to determine a time offset value of the first UE.

[0018] In some embodiments, performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE includes:

[0019] Determine an impulse response of a channel corresponding to the first UE based on the time offset value of the first UE;

[0020] A time offset correction is performed on the filter coefficient of the initial filter according to the impulse response to obtain a target filter corresponding to the first UE.

[0021] In some embodiments, the method includes: synthesizing the window filter and the frequency filter to obtain the initial filter, including:

[0022] The window filter and the frequency filter are synthesized to obtain a synthesized filter;

[0023] The filter coefficient of the synthesizer is set according to the signal transmission frequency of the first UE and the preset sampling frequency of the network side device to obtain the initial filter.

[0024] In some embodiments, synthesizing the window filter and the frequency filter to obtain a synthesized filter includes:

[0025] The frequency domain filter is convolved with the window filter to obtain the synthesis filter.

[0026] In a second aspect, the present application proposes a channel estimation device based on a MU-MIMO communication system, the device is applied to a network side device, or the device is the network side device, the device is connected to multiple UEs, and the multiple UEs multiplex the same time-frequency resources, and the device includes:

[0027] a communication unit, configured to receive signals from the plurality of UEs on the time-frequency resources;

[0028] A processing unit configured to perform:

[0029] Performing channel estimation based on the signal received on the time-frequency resource to determine an initial channel matrix, and determining a time offset value for each UE based on the signal;

[0030] Performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE; the first UE is any one of the multiple UEs;

[0031] The initial channel matrix is ​​filtered using a target filter of the first UE to obtain a target channel matrix of the first UE.

[0032] In some embodiments, the processing unit is further configured to:

[0033] A preset window filter and a frequency domain filter are obtained, and the window filter and the frequency filter are synthesized to obtain the initial filter.

[0034] The processing unit is specifically used for:

[0035] Filtering the initial channel matrix using a window filter included in the target filter to obtain an initial channel matrix corresponding to the first UE;

[0036] An initial channel matrix corresponding to the first UE is filtered using a frequency domain filter included in the target filter to obtain a target channel matrix of the first UE.

[0037] In some embodiments, the processing unit is specifically configured to:

[0038] A pilot sequence of the first UE is obtained, and a correlation calculation is performed between the pilot sequence and the sequence of the signal to eliminate the pilot, so as to determine a time offset value of the first UE.

[0039] In some embodiments, the processing unit is specifically configured to:

[0040] Determine an impulse response of a channel corresponding to the first UE based on the time offset value of the first UE;

[0041] A time offset correction is performed on the filter coefficient of the initial filter according to the impulse response to obtain a target filter corresponding to the first UE.

[0042] In some embodiments, the processing unit is specifically configured to:

[0043] The window filter and the frequency filter are synthesized to obtain a synthesized filter;

[0044] The filter coefficient of the synthesizer is set according to the signal transmission frequency of the first UE and the preset sampling frequency of the network side device to obtain the initial filter.

[0045] In some embodiments, the processing unit is specifically configured to:

[0046] The frequency domain filter is convolved with the window filter to obtain the synthesis filter.

[0047] In a third aspect, an electronic device is provided, the electronic device comprising a controller and a memory. The memory is used to store computer-executable instructions, and the controller executes the computer-executable instructions in the memory to use hardware resources in the controller to perform the operation steps of any possible implementation method of the first aspect.

[0048] In a fourth aspect, a computer-readable storage medium is provided, wherein instructions are stored in the computer-readable storage medium, and when the computer-readable storage medium is run on the computer, the computer executes the above-mentioned methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A schematic diagram of the architecture of a communication system provided in an embodiment of the present application;

[0051] Figure 2 A schematic diagram of a channel estimation process;

[0052] Figure 3 A schematic diagram of a channel estimation method based on a MU-MIMO communication system provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the structure of a channel estimation device based on a MU-MIMO communication system provided in an embodiment of the present application;

[0054] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0056] It should be noted that the terms "first", "second", etc. in this application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0057] In order to facilitate understanding of the solution of this application, the technical terms involved in this application are first introduced below:

[0058] (1) MU-MIMO technology: a technology that enables multiple terminal devices to communicate with network devices at the same time. In the uplink MU-MIMO scenario, different terminal devices use the same time-frequency resources to send uplink data. From the perspective of the network device, the received data streams can be regarded as coming from different antennas of a terminal device, thus forming a virtual MIMO system. In the downlink MU-MIMO scenario, when the network device transmits multiple data streams to different terminal devices, it will use beamforming to separate the data streams belonging to different terminal devices in advance, thereby simplifying the receiving operation of the terminal device.

[0059] (2) Least Squares (LS) estimation: A channel estimation algorithm used to estimate the impulse response of the channel that the signal has passed through, and used for subsequent channel equalization processing. The principle of the LS estimation algorithm is to ensure that the sum of squares of the errors between the actual received signal and the estimated received signal is minimized, in which case the estimated channel matrix is ​​obtained.

[0060] (3) Linear Minimum Mean Squared Error (LMMSE): It can also be called the optimal linear estimation. It is a further optimization of the LS estimation algorithm. Its essence is to filter the LS estimation results using the correlation in the frequency domain to eliminate the influence of some noise.

[0061] (4) Window filter: Since the received signal sequence is often infinite and non-causal, a window filter is used to establish a filter window and a sampling window of a preset length. The function is to truncate the infinite length sequence through the window function to obtain a finite length sequence. Common window functions include rectangular window, Hanning window, Hamming window, etc.

[0062] (5) Pilot signal: In wireless communications, channel characteristics vary with time. In order to estimate the channel characteristics in a timely manner, a signal known to the receiving end can be transmitted at the same time as the useful signal. This signal is called a pilot signal.

[0063] (6) Impulse response: The zero-state response generated by the system when a unit impulse signal is used as the stimulus is called the impulse response.

[0064] (7) Power Delay Profile (PDP): The power level over the delay is obtained by averaging the channel impulse response in the time domain and then squaring it. According to the Wiener-Khinchin theorem, the PDP can be converted to the autocorrelation of the channel's time domain impulse response by Fourier transform.

[0065] (8) Channel equalization: refers to the equalization of channel characteristics, that is, the equalizer at the receiving end produces characteristics opposite to those of the channel to offset the interference between symbols caused by the time-varying multipath propagation characteristics of the channel. The equalization principle can be explained by the following formulas (1) and (2):

[0066]

[0067]

[0068] Among them, Y rs is the received pilot signal, X rs is the pilot signal, is the channel matrix, N is the noise; Y data is the received data signal, G is the estimated channel matrix Determined equalizer, is the equalized data signal.

[0069] (9) Gibbs effect: Also known as the Gibbs phenomenon, after the periodic function with discontinuities is expanded by Fourier series, a finite number of items are selected for synthesis. The more items are selected, the closer the peaks appearing in the synthesized waveform are to the discontinuities of the original signal. When the number of items selected is large, the peak value tends to a constant, which is approximately equal to 9% of the total jump value.

[0070] In order to facilitate understanding of the solution of the present application, the following first introduces the communication system to which the present application is applicable. Figure 1 , is a schematic diagram of the architecture of a communication system provided in an embodiment of the present application. It should be understood that the embodiment of the present application is not limited to Figure 1 In the system shown, in addition, Figure 1 The device in the structure can be hardware, or software divided according to its functions, or a combination of the two. Figure 1 As shown, the communication system proposed in the embodiment of the present application includes a network side device and multiple terminal devices. Figure 1 The communication system shown is a MU-MIMO architecture, that is, the network side device can communicate with multiple terminal devices at the same time.

[0071] Figure 1The terminal device shown in the figure may also be called a user terminal, a mobile station (English: Mobile Station, abbreviated: MS), a mobile terminal (English: Mobile Terminal, abbreviated: MT), etc., which is a device that provides voice and / or data connectivity to users, for example, a handheld device with wireless connection function, a vehicle-mounted device, etc. At present, some examples of terminals are: mobile phones, tablet computers, laptop computers, PDAs, mobile Internet devices (English: Mobile Internet Device, abbreviated: MID), wearable devices, virtual reality (English: Virtual Reality, abbreviated: VR) devices, augmented reality (English: Augmented Reality, abbreviated: AR) devices, wireless terminals in industrial control (Industrial Control), wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids (smart grid), wireless terminals in transportation safety (transportation safety), wireless terminals in smart cities (smart cities), wireless terminals in smart homes (smart homes), etc.

[0072] Figure 1 The network side devices shown can be base stations, access points AP in local area networks, access network devices, sub-6G receivers or 5G millimeter wave receivers and other devices. Among them, the sub-6G receiver is an indoor integrated small base station device based on 5G NR technology, which supports sub-6G frequency bands (2.6G / 3.5G) and supports Ethernet and optical port backhaul. AP can be an access point for terminal devices to enter a wired (or wireless) network. It is mainly deployed in homes, office buildings and parks, and the coverage range can be tens of meters to hundreds of meters. AP is equivalent to a bridge connecting wired networks and wireless networks, which is used to connect various wireless network clients together and then connect the wireless network to Ethernet. Exemplarily, AP can be a terminal or network device with a WiFi chip, such as a router and other devices. A base station is a public mobile communication base station, which is an interface device for a mobile terminal to access the Internet. Specifically, it can be an evolved base station (eNB or eNodeB) in a long-term evolution (LTE) system, or a next-generation base station (gNB) in a fifth-generation (5G) mobile communication system. This application does not limit this.

[0073] It should be noted that the present application does not limit the number of network side devices and terminal devices included in the communication system. Figure 1 Just as an example.

[0074] In a MU-MIMO communication system, multiple terminal devices can reuse the same time-frequency resources. When the network-side device performs channel estimation based on the received signal, it needs to fully consider the time deviation of the terminal device. Figure 2 , is a schematic diagram of a channel estimation process. Step 1: Perform LS estimation based on the received signal to obtain the initial channel matrix. It can be known that the initial channel matrix is ​​affected by the time offset of different terminal devices. Step 2: Perform orthogonal cover code (OCC) processing on the initial channel matrix. In step 2, the OCC solution generally includes performing a one-step parity cancellation on the initial channel matrix, and then performing time offset estimation to determine the timing advance (TA) of each terminal device. Further, the received signal is supplemented with TA and then parity cancellation is performed again to obtain the channel matrix corresponding to each terminal device. However, in the MU-MIMO communication system, the time offsets of different terminal devices are different, so it is difficult to eliminate the time offset effects of all terminal devices, resulting in a high error rate in the subsequent OCC solution results. In addition, this method has many calculation steps, resulting in high delay, and in scenarios that are sensitive to time offset, such as high modulation order or low signal-to-noise ratio, once the time offset estimation is wrong, the channel matrix error will be large, so this solution does not have anti-interference ability. In the related art, another method for solving OCC is: after performing an inverse fast Fourier transform (IFFT) on the initial channel matrix, perform time domain windowing, and then perform a fast Fourier transform (FFT). This method requires time-frequency conversion, has high computational complexity, and has a high implementation cost. Step three: TA compensation is performed on the channel matrices of multiple terminal devices obtained by solving OCC. Step four: Filter the channel matrices of multiple terminal devices obtained by solving OCC. Two filtering methods are commonly used in the related art. One is to transform the frequency domain signal to the time domain, perform windowing, and then transform it to the frequency domain to remove noise. This method requires high complexity of time-frequency conversion and destroys the white Gaussian characteristics of the noise, resulting in a low noise removal effect, and is very sensitive to time deviation, so it is not conducive to implementation. The other is to remove noise by LMMSE filtering and other methods. This solution requires that the time deviation has been accurately corrected in advance, and the result of solving OCC must be accurate. Step five: Time deviation counter compensation. Used for subsequent equalization processing, etc.

[0075] Based on the various shortcomings of the above-mentioned traditional channel estimation schemes, this application proposes a channel estimation method for realizing channel estimation under MU-MIMO communication systems. This application corrects the frequency domain filter based on the time offset of different terminal devices, and combines the corrected frequency domain filter and window filter to form an integrated filter. Based on this integrated filter, it is possible to obtain the accurate channel matrix of each terminal device from the initial channel matrix, and the obtained channel matrix does not require time offset compensation and inverse compensation, which can effectively improve the efficiency and accuracy of channel estimation.

[0076] Next, combine Figure 1 The MU-MIMO communication system shown in the figure specifically introduces the channel estimation scheme proposed in this application. For example, see Figure 3 , is a schematic diagram of a channel estimation method based on a MU-MIMO communication system provided in an embodiment of the present application. Optionally, the method flow can be Figure 1 The communication system shown may be executed by a network side device included in the communication system, or may be implemented by specific components included in the network side device, and the present application does not limit this. Figure 3 The method flow shown specifically includes:

[0077] 301. A network-side device receives a signal on a time-frequency resource shared by multiple terminal devices, and performs channel estimation based on the received signal to determine an initial channel matrix.

[0078] The present application does not limit the algorithm used for channel estimation, for example, LS estimation, LMMSE estimation algorithm, etc. may be used.

[0079] 302. The network side device determines the time deviation value of each terminal device according to the received signal.

[0080] Exemplarily, the network-side device may perform correlation calculation based on known pilot sequences of each terminal device and a received signal sequence to eliminate the pilot and determine the time offset value of each terminal device.

[0081] 303. The network side device uses the time offset value of the first terminal device to perform time offset correction on the initial filter to obtain a target filter for the first terminal device.

[0082] The initial filter is used to eliminate noise generated by the signal sent by the first terminal device during the transmission process, and to identify the initial channel matrix corresponding to the first terminal device from the initial channel matrix. The first terminal device is any one of the multiple terminal devices that reuse the same time-frequency resources.

[0083] Exemplarily, the initial filter can be synthesized by a frequency domain filter and a window filter. For example, the window filter and the frequency domain filter can be synthesized to obtain a synthesized filter, and the filter coefficients of the synthesized filter are processed using the signal transmission frequency of the first terminal device and the sampling frequency of the preset network device to obtain the initial filter.

[0084] As an optional method, when synthesizing a frequency domain filter and a window filter, the filter coefficients of the frequency domain filter and the filter coefficients of the window filter can be synthesized by performing a time domain dot multiplication or a frequency domain convolution calculation to obtain a synthesized filter. Furthermore, the filter coefficients of the synthesized filter can be set to obtain an initial filter of the first terminal device. Furthermore, the network side device can control the filter coefficients of the initial filter to be offset in the time domain based on the time deviation value of the first terminal device to obtain a target filter. Thus, the target filter after time deviation correction not only has the function of separating the channel matrices of different terminal devices provided by the window filter, but also has the function of filtering the channel matrix to remove noise provided by the frequency domain filter.

[0085] 304. The network side device uses the target filter corresponding to the first terminal device to filter the initial channel matrix to obtain the target channel matrix of the first terminal device.

[0086] Based on the above scheme, the present application proposes that there is no need to compensate the channel matrix of each terminal device for time offset, but the time offset is embedded in the initial filter, so that the target filter obtained is a filter after time offset correction, which can not only accurately separate the channel matrix of each terminal device from the initial channel matrix, but also accurately perform noise filtering to obtain an accurate and noise-removed channel matrix corresponding to each terminal device. And because the channel matrix of each terminal device is not compensated for time offset, the step of time offset inversion can be omitted, and the obtained channel matrix can be directly used for equalization processing, which improves the efficiency of channel estimation.

[0087] Based on the equalization principle introduced in the above embodiment, it can be seen that when the received pilot signal (ie, Y in formula (1) rs ) When there is the influence of time offset, the corresponding estimated channel matrix There is also the influence of time offset. If the unbiased estimated channel is set to be unaffected by time offset, The pilot received signal that is not affected by the time offset is The actual pilot signal and the actual estimated channel matrix can be referred to in the following formulas (3) and (4):

[0088]

[0089]

[0090] Among them, ⊙ is the dot product symbol, Y rs is the pilot signal actually received, For the pilot reception signal that is not affected by the time offset, is the unbiased estimated channel when it is not affected by time offset, is the channel matrix with time offset influence, and T is the time offset compensation vector.

[0091] In some embodiments, in order to eliminate the influence of time offset in the initial channel matrix, the initial channel matrix can be first filtered through a window filter, and then the initial channel matrix can be filtered using a frequency domain filter after time offset correction, and the results of the two filtering processes are superimposed to obtain the channel matrix of each terminal device. However, due to the superposition of the Gibbs effect, some custom sequence values ​​will be introduced at the edge of the sequence during the window filtering process. For example, when the sampling window set in the window filter is not completely filled, it is necessary to generate some new sequence values ​​based on the average value of the sequence value in the current window to supplement the edge of the sequence, thereby increasing the unreliability of the edge channel estimation result and increasing the computational complexity. Based on this, the present application proposes to synthesize the two filters and then perform time offset correction, and filter the channel estimation result by the target filter obtained by the synthesis and time offset correction, thereby alleviating the Gibbs effect.

[0092] Exemplarily, when the target filter is used for filtering, the window filter contained therein can be used to filter the initial channel matrix obtained by LS estimation, and the initial channel matrices of different terminal devices can be separated to obtain the initial channel matrix corresponding to each terminal device. Furthermore, the frequency domain filter contained in the target filter can be used to filter the initial channel matrices corresponding to each terminal device respectively, and the noise in the initial channel matrix corresponding to each terminal device can be removed to obtain the target channel matrix corresponding to each terminal device.

[0093] Exemplarily, the synthesis method of the frequency domain filter and the window filter can refer to the following formula (5):

[0094]

[0095] in, is the convolution calculation symbol, W filt is the synthesis filter, W win is the window filter, W t is a frequency domain filter.

[0096] After obtaining the synthetic filter, the filter coefficient of the synthetic filter can be set using the signal transmission frequency and sampling frequency of each terminal device to obtain the initial filter corresponding to each terminal device. Furthermore, the initial filter can be time-corrected using the time deviation value of each terminal device one by one to obtain the target filter corresponding to each terminal device. In some embodiments, when the initial filter is time-corrected according to the time deviation value of each terminal device, the correction can be made according to the impulse response of the channel. Exemplarily, the process of correcting the initial filter is still introduced by taking the first terminal device as an example. The network side device can determine the impulse response of the channel corresponding to the first terminal device based on the time deviation value of the first terminal device. For example, refer to the following formula (6)-formula (7):

[0097]

[0098]

[0099] in, is the time domain impulse response of the actual channel matrix, is the time domain impulse response of the channel matrix without the influence of time offset, τ is the time offset value, is the autocorrelation of the channel time-domain impulse response without the influence of time offset, is the actual channel time domain impulse response autocorrelation.

[0100] After determining the time domain impulse response according to the time deviation value of the first terminal device, the initial filter can be corrected according to the time domain impulse response. Exemplarily, since the impulse response in the time domain is calculated, but the initial filter to be corrected includes a frequency domain filter, it is necessary to perform time-frequency conversion in advance. According to the introduction of the above technology, the frequency domain PDP and the time domain impulse response are a pair of Fourier transforms. Therefore, the frequency domain PDP can be expressed by the following formula (8):

[0101]

[0102] in, is the frequency domain PDP, F is the Fourier transform matrix, is the time domain impulse response, F H is the conjugate transpose of the Fourier transform matrix F.

[0103] Furthermore, the process of correcting the initial filter to obtain the target filter can be seen in the following formula (9):

[0104]

[0105] Among them, W T is the target filter, σ 2is the noise power on the received signal, I is the unit matrix, F is the Fourier transform matrix, is the time domain impulse response, F H is the conjugate transpose of the Fourier transform matrix F.

[0106] After obtaining the target filters corresponding to the respective terminal devices, the initial channel matrix may be sequentially input into the respective target filters to obtain the target channel matrix corresponding to each terminal device.

[0107] Based on the same concept as the above method, see Figure 4 , is a channel estimation device 400 based on a MU-MIMO communication system provided in an embodiment of the present application, the device 400 is used to perform each step in the above method, and in order to avoid repetition, it will not be described here. The device 400 includes: a communication unit 401 and a processing unit 402.

[0108] The communication unit 401 is configured to receive signals from the multiple UEs on the time-frequency resources;

[0109] The processing unit 402 is configured to execute:

[0110] Performing channel estimation based on the signal received on the time-frequency resource to determine an initial channel matrix, and determining a time offset value for each UE based on the signal;

[0111] Performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE; the first UE is any one of the multiple UEs;

[0112] The initial channel matrix is ​​filtered using a target filter of the first UE to obtain a target channel matrix of the first UE.

[0113] In some embodiments, the processing unit 402 is further configured to:

[0114] A preset window filter and a frequency domain filter are obtained, and the window filter and the frequency filter are synthesized to obtain the initial filter.

[0115] The processing unit 402 is specifically configured to:

[0116] Filtering the initial channel matrix using a window filter included in the target filter to obtain an initial channel matrix corresponding to the first UE;

[0117] An initial channel matrix corresponding to the first UE is filtered using a frequency domain filter included in the target filter to obtain a target channel matrix of the first UE.

[0118] In some embodiments, the processing unit 402 is specifically configured to:

[0119] A pilot sequence of the first UE is obtained, and a correlation calculation is performed between the pilot sequence and the sequence of the signal to eliminate the pilot, so as to determine a time offset value of the first UE.

[0120] In some embodiments, the processing unit 402 is specifically configured to:

[0121] Determine an impulse response of a channel corresponding to the first UE based on the time offset value of the first UE;

[0122] A time offset correction is performed on the filter coefficient of the initial filter according to the impulse response to obtain a target filter corresponding to the first UE.

[0123] In some embodiments, the processing unit 402 is specifically configured to:

[0124] The window filter and the frequency filter are synthesized to obtain a synthesized filter;

[0125] The filter coefficient of the synthesizer is set according to the signal transmission frequency of the first UE and the preset sampling frequency of the network side device to obtain the initial filter.

[0126] In some embodiments, the processing unit 402 is specifically configured to:

[0127] The frequency domain filter is convolved with the window filter to obtain the synthesis filter.

[0128] Figure 5 The electronic device 500 in the embodiment of the present application may further include a communication interface 503, such as a network port, through which the electronic device may transmit data, for example, the communication interface 503 may implement the functions of the communication unit 401 described in the above embodiment.

[0129] In the embodiment of the present application, the memory 502 stores instructions that can be executed by at least one controller 501. The at least one controller 501 can be used to execute each step in the above method by executing the instructions stored in the memory 502. For example, the controller 501 can implement the above Figure 4 The function of the processing unit 402 in.

[0130] Among them, the controller 501 is the control center of the electronic device, which can use various interfaces and lines to connect various parts of the entire electronic device, by running or executing instructions stored in the memory 502 and calling data stored in the memory 502. Optionally, the controller 501 may include one or more processing units, and the controller 501 may integrate an application controller and a modem controller, wherein the application controller mainly processes the operating system and application programs, etc., and the modem controller mainly processes wireless communications. It is understandable that the above-mentioned modem controller may not be integrated into the controller 501. In some embodiments, the controller 501 and the memory 502 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on independent chips.

[0131] The controller 501 may be a general controller, such as a central processing unit (CPU), a digital signal controller, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, which may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general controller may be a microcontroller or any conventional controller, etc. The steps performed by the network side device disclosed in the embodiments of the present application may be performed directly by a hardware controller, or may be performed by a combination of hardware and software modules in the controller.

[0132] The memory 502 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 502 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (English: Random Access Memory, abbreviated as RAM), a static random access memory (English: Static Random Access Memory, abbreviated as SRAM), a programmable read-only memory (English: Programmable Read Only Memory, abbreviated as PROM), a read-only memory (English: Read Only Memory, abbreviated as ROM), an electrically erasable programmable read-only memory (English: Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 502 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 502 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0133] By designing and programming the controller 501, for example, the code corresponding to the method introduced in the above embodiment can be solidified into the chip, so that the chip can execute the above method steps during operation. How to design and program the controller 501 is a technology well known to those skilled in the art and will not be repeated here.

[0134] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0135] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a controller of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the controller of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0136] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0137] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0138] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0139] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A channel estimation method based on a MU-MIMO communication system, characterized in that: The method is applied to a network side device, the network side device is connected to multiple terminal devices UE, and the multiple UEs multiplex the same time-frequency resources, and the method includes: Performing channel estimation based on the signal received on the time-frequency resource to determine an initial channel matrix, and determining a time offset value for each UE based on the signal; Performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE; the first UE is any one of the multiple UEs; The initial channel matrix is ​​filtered using a target filter of the first UE to obtain a target channel matrix of the first UE.

2. The method according to claim 1, characterized in that Before performing time offset correction on the initial filter according to the time offset value of the first UE, the method further includes: A preset window filter and a frequency domain filter are obtained, and the window filter and the frequency filter are synthesized to obtain the initial filter.

3. The method according to claim 2, characterized in that The filtering the initial channel matrix using the target filter of the first UE to obtain the target channel matrix of the first UE includes: Filtering the initial channel matrix using a window filter included in the target filter to obtain an initial channel matrix corresponding to the first UE; An initial channel matrix corresponding to the first UE is filtered using a frequency domain filter included in the target filter to obtain a target channel matrix of the first UE.

4. The method according to any one of claims 1 to 3, characterized in that: The determining the time offset value of each UE based on the signal includes: A pilot sequence of the first UE is obtained, and a correlation calculation is performed between the pilot sequence and the sequence of the signal to eliminate the pilot, so as to determine a time offset value of the first UE.

5. The method according to any one of claims 1 to 3, characterized in that: The performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE includes: Determine an impulse response of a channel corresponding to the first UE based on the time offset value of the first UE; A time offset correction is performed on the filter coefficient of the initial filter according to the impulse response to obtain a target filter corresponding to the first UE.

6. The method according to claim 2 or 3, characterized in that: The step of synthesizing the window filter and the frequency filter to obtain the initial filter comprises: The window filter and the frequency filter are synthesized to obtain a synthesized filter; The filter coefficient of the synthesizer is set according to the signal transmission frequency of the first UE and the preset sampling frequency of the network side device to obtain the initial filter.

7. The method according to claim 6, characterized in that The step of synthesizing the window filter and the frequency filter to obtain a synthesized filter comprises: The frequency domain filter is convolved with the window filter to obtain the synthesis filter.

8. A channel estimation device based on a MU-MIMO communication system, characterized in that: The device is applied to a network side device, or the device is the network side device, the device is connected to multiple UEs, the multiple UEs multiplex the same time-frequency resources, and the device includes: a communication unit, configured to receive signals from the plurality of UEs on the time-frequency resources; A processing unit configured to perform: Performing channel estimation based on the signal received on the time-frequency resource to determine an initial channel matrix, and determining a time offset value for each UE based on the signal; Performing time offset correction on the initial filter according to the time offset value of the first UE to determine the target filter of the first UE; the first UE is any one of the multiple UEs; The initial channel matrix is ​​filtered using a target filter of the first UE to obtain a target channel matrix of the first UE.

9. An electronic device, characterized in that: include: Memory and controller; A memory for storing program instructions; A controller is used to call the program instructions stored in the memory and execute the method according to any one of claims 1 to 7 according to the obtained program.

10. A computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are used to execute the method according to any one of claims 1-7.

Images