WO2021068711A1

WO2021068711A1 - Method for optimizing mu-mimo beam overlap, communication device and system

Info

Publication number: WO2021068711A1
Application number: PCT/CN2020/115058
Authority: WO
Inventors: 李云
Original assignee: 中兴通讯股份有限公司
Priority date: 2019-10-09
Filing date: 2020-09-14
Publication date: 2021-04-15
Also published as: CN112653494A

Abstract

A method for optimizing MU-MIMO beam overlap, a communication device and a system. The optimization method comprises: when a correlation degree between original channel matrices corresponding to second communication devices is greater than a preset threshold, a first communication device adjusting, according to a preset deflection angle, the original channel matrices corresponding to the second communication devices, to obtain new channel matrices, and sending the new channel matrices to the corresponding second communication devices; each second communication device receiving the new channel matrix sent by the first communication device, and performing decoding according to the new channel matrix to generate spatial stream data.

Description

MU-MIMO beam overlapping optimization method, communication equipment and system

Cross-references to related applications

This application is based on a Chinese patent application with an application number of 201910955583.6 and an application date of October 9, 2019, and claims the priority of the Chinese patent application. The entire content of the Chinese patent application is hereby incorporated into this application by way of introduction.

Technical field

The embodiments of the present application relate to, but are not limited to, the field of wireless communication technology. Specifically, they relate to, but are not limited to, a method for optimizing beam overlap for multi-user, multi-input and multi-output (Multi-user, Multi-input Multi-Output, MU-MIMO) , The first communication device, the second communication device and the system.

Background technique

The traditional 802.11 technology uses the Carrier Sense Multiple Access with Collision Detectio (CSMA/CD) mechanism, which is a competitive time/frequency domain multiple access. When there are multiple devices In the case of simultaneous access to the network, channels need to be used alternately with each other to avoid conflicts, so bandwidth utilization is low. MU-MIMO is one of the important features of the WiFi technology standards 802.11ac and 802.11ax. MU-MIMO is a Spatial Division Multiple Access (SDMA) technology used for spatial multiplexing, through the use of beamforming technology , Allocate beams with different directions for each user, so that the signals of each user do not interfere with each other, avoiding channel competition, thus improving channel utilization, and improving the throughput of multi-user scenarios.

MU-MIMO is a kind of spatial multiplexing, but when multiple stations (stations, STAs) are very close in space or they are in the same straight line with the access point (AP), or more broadly They have a similar multipath environment. At this time, the channel matrix between the multiple STAs and the AP has a high correlation. The main lobes of these multiple beams will overlap, and their signals are sent at the same time, which inevitably Mutual interference not only does not play the role of MU-MIMO, but will affect each other. In practical applications, it has also been found that MU-MIMO is more sensitive to STA antennas and STA placement positions.

When the above situation occurs, a feasible method is to add two STAs that interfere with each other into two different MU-MIMO groups, and still use the traditional CSMA/CD for time sharing, but this method is lost The advantages of MU-MIMO spatial multiplexing. It can be seen that, in some cases, the problem of beam overlap in a multi-user environment cannot be solved well.

Summary of the invention

The MU-MIMO beam overlap optimization method, communication device, and system provided in the embodiments of the present application.

The embodiment of the present application provides a method for optimizing MU-MIMO beam overlap, including: when the correlation between the original channel matrices corresponding to each second communication device is greater than a preset threshold, adjusting each second communication device according to a preset deflection angle The original channel matrix corresponding to the communication device obtains a new channel matrix; and each of the new channel matrixes is sent to the corresponding second communication device.

An embodiment of the present application also provides a method for optimizing MU-MIMO beam overlap, including: receiving a new channel matrix sent by a first communication device; decoding according to the new channel matrix to generate spatial stream data.

The embodiment of the present application also provides a method for optimizing MU-MIMO beam overlap, including: when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold, the first communication device deflects according to the preset Adjust the original channel matrix corresponding to each second communication device to obtain a new channel matrix, and send each new channel matrix to the corresponding second communication device; the second communication device receives the new channel matrix sent by the first communication device , Performing decoding according to the new channel matrix to generate spatial stream data.

An embodiment of the present application also provides a first communication device. The first communication device includes an adjustment module and a first sending module; the adjustment module is used for the correlation between the original channel matrixes corresponding to each second communication device. When the degree is greater than the preset threshold, the original channel matrix corresponding to each second communication device is adjusted according to the preset deflection angle to obtain a new channel matrix; the first sending module is configured to send each of the new channel matrices to the corresponding second communication device.

An embodiment of the present application also provides a second communication device. The second communication device includes a second receiving module and a decoding module; the second receiving module is configured to receive a new channel matrix sent by the second communication device; The decoding module is used for decoding according to the new channel matrix to generate spatial stream data.

An embodiment of the present application also provides a system, which includes a first communication device and at least two second communication devices; the first communication device is used to communicate between the original channel matrixes corresponding to each second communication device When the correlation is greater than the preset threshold, adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix, and send each new channel matrix to the corresponding second communication device; The communication device is configured to receive a new channel matrix sent by the first communication device, and perform decoding according to the new channel matrix to generate spatial stream data.

Other features of this application and corresponding beneficial effects are described in the latter part of the specification, and it should be understood that at least part of the beneficial effects will become apparent from the description in the specification of this application.

Description of the drawings

The application will be further described below in conjunction with the accompanying drawings and embodiments. In the accompanying drawings:

FIG. 1 is a schematic diagram 1 of the basic flow of the method for optimizing MU-MIMO beam overlap provided in the first embodiment of this application;

2 is a schematic diagram 1 of the basic process before adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix according to the first embodiment of the application;

3 is a schematic diagram 2 of the basic process before adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix according to the first embodiment of the application;

4 is a schematic diagram of the basic flow of adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix according to the first embodiment of the application;

FIG. 5 is a schematic diagram of the basic flow after each new channel matrix is sent to the corresponding second communication device according to the first embodiment of the application; FIG.

6 is a schematic diagram 2 of the basic flow of the method for optimizing MU-MIMO beam overlap provided in the first embodiment of the application;

FIG. 7 is a schematic diagram of the basic flow before receiving a new channel matrix sent by a first communication device according to Embodiment 1 of the application; FIG.

FIG. 8 is a schematic diagram of a basic flow chart of generating spatial stream data by decoding according to a new channel matrix according to Embodiment 1 of the application; FIG.

FIG. 9 is a schematic diagram of the basic flow of the method for optimizing MU-MIMO beam overlap provided in the second embodiment of the application;

FIG. 10 is a schematic diagram of the basic flow of a specific method for optimizing MU-MIMO beam overlap provided in the third embodiment of the application; FIG.

FIG. 11 is a first structural diagram of a first communication device provided in Embodiment 4 of this application;

12 is a schematic diagram 2 of the structure of the first communication device provided in the fourth embodiment of the application;

FIG. 13 is a third structural diagram of the first communication device provided in the fourth embodiment of this application;

FIG. 14 is a fourth structural schematic diagram of the first communication device provided by the fourth embodiment of this application;

15 is a schematic structural diagram 1 of a second communication device provided in Embodiment 4 of this application;

FIG. 16 is a second structural diagram of a second communication device according to Embodiment 4 of this application;

FIG. 17 is a third structural diagram of a second communication device according to Embodiment 4 of this application;

FIG. 18 is a schematic structural diagram of a system provided by Embodiment 5 of this application;

FIG. 19 is a schematic structural diagram of a router provided in Embodiment 6 of this application;

FIG. 20 is a schematic structural diagram of a terminal provided in Embodiment 5 of this application.

Detailed ways

In order to make the objectives, technical solutions, and advantages of the present application clearer, the following further describes the embodiments of the present application in detail through specific implementations in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the application, and not used to limit the application.

Example one:

In order to solve the problem of beam overlap in a multi-user environment that cannot be well resolved in some situations, an optimization method for MU-MIMO beam overlap is provided in an embodiment of the present application. When the correlation between the channel matrices is greater than the preset threshold, the first communication device adjusts the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix, and sends each new channel matrix to the corresponding second communication device. Communication equipment; please refer to FIG. 1, which is a schematic diagram of the basic flow of an optimization method for MU-MIMO beam overlap provided by an embodiment of this application.

S101: When the correlation between the original channel matrices corresponding to each second communication device is greater than a preset threshold, adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix.

In an embodiment, the original channel matrix corresponding to each second communication device is adjusted according to the preset deflection angle to obtain the new channel matrix, including at least the following two situations:

Case 1, please refer to Figure 2:

S201: Send a detection message to each second communication device respectively.

S202: Receive a channel state indication sent by each second communication device, where the channel state indication includes the original channel matrix of the second communication device.

S203: Calculate the correlation between the original channel matrices, and when the correlation is greater than a preset threshold, determine that each second communication device has a similar multipath environment.

It should be understood that, in this embodiment of the application, when it is determined that the correlation between the original channel matrix corresponding to each second communication device is greater than the preset threshold, that is, when the beams of each second communication device have overlapping areas, it is necessary to check at this time. The original channel matrix of one or more of the second communication devices with overlapping beam beams is adjusted. In fact, it is only necessary to adjust the original channel matrix of one or more of the second communication devices so that the The beam overlap area can be reduced or eliminated. In practical applications, it can be flexibly adjusted according to specific application scenarios.

It should be understood that, in actual applications, the preset threshold is flexibly set by the developer based on experiments or experience.

Situation two, please refer to Figure 3:

S301: Acquire system parameters set by each second communication device and the first communication device.

In one embodiment, in accordance with the requirements of the 802.11 protocol, each second communication device and the first communication device will set system parameters, where the system parameters include but are not limited to throughput, modulation and coding scheme (Modulation and Coding Scheme, MCS) , Rate, bit error rate, etc.

S302: Input various system parameters into the deep learning network, and the deep learning network outputs various deflection angles.

In an embodiment, adjusting the original channel matrix corresponding to each second communication device according to a preset deflection angle to obtain a new channel matrix includes: correspondingly adjusting the original channel matrix corresponding to each second communication device according to each deflection angle to obtain a new channel matrix.

In one embodiment, the deep learning network trains the weight of the system according to the principle of gradient descent. After multiple iterations, the overall performance of the system tends to be optimal. When the set threshold is reached, the training is stopped. At this time, the output deflection angle is Optimal deflection angle. It should be understood that the output deflection angle will have an impact on the system performance, which can be directly reflected in the changes in parameters such as throughput, MCS, rate, and bit error rate.

In one embodiment, the deep learning network includes Convolutional Neural Networks (CNN), Recurrent Neural Network (RNN), and Deep Belief Network (DBN). It is worth noting that the ones listed here are just a few common deep learning networks. In actual applications, they can be flexibly adjusted according to specific application scenarios.

For a better understanding, here is an example for illustration.

For example, suppose that the first communication device is A, and the second communication device includes two, namely B1 and B2, where the system parameters set by the second communication device B1 and the first communication device A are b1, and the second communication device B2 and The system parameter set by the first communication device A is b2. At this time, the system parameter b1 is input into the deep learning network, the deflection angle r1 is output, and the system parameter b2 is input into the deep learning network, and the deflection angle r2 is output. The angle r1 adjusts the original channel matrix of the second communication device B1 to obtain a new channel matrix, and adjusts the original channel matrix of the second communication device B2 according to the deflection angle r2 to obtain the new channel matrix.

It should be understood that the above examples are only two common situations, and the two can be executed in combination with each other or executed separately, and this application does not specifically limit this.

In an embodiment, adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain the new channel matrix includes at least the following steps, as shown in FIG. 4:

S401: Generate a corresponding spatial mapping matrix for the transmitting antenna of each second communication device according to the preset deflection angle.

S402: Use each generated spatial mapping matrix to transform the original channel matrix of each second communication device to obtain each new channel matrix.

S102: Send each new channel matrix to the corresponding second communication device.

For a better understanding, here is an example for illustration.

For example, also suppose that the first communication device is A, and the second communication device includes two, namely B1 and B2, where the system parameters set by the second communication device B1 and the first communication device A are b1, and the second communication device B2 The system parameter set with the first communication device A is b2. At this time, the system parameter b1 is input into the deep learning network, and the deflection angle r1 is output, and the system parameter b2 is input into the deep learning network, and the deflection angle r2 is output; The angle r1 is the space mapping matrix generated by the transmitting antenna of the second communication device B1, and further, the original channel matrix of the second communication device B1 is transformed by the generated space mapping matrix to obtain a new channel matrix. Similarly, according to the deflection angle r2, The transmitting antenna of the second communication device B2 generates a spatial mapping matrix, and further, using the generated spatial mapping matrix to transform the original channel matrix of the second communication device B2 to obtain a new channel matrix.

In an embodiment, after each new channel matrix is sent to the corresponding second communication device, it further includes at least the following steps, as shown in FIG. 5:

S501: Perform singular value decomposition on each new channel matrix, and calculate each precoding matrix.

S502: Generate each MU-MIMO data message according to each precoding matrix, and send each MU-MIMO data message to the corresponding second communication device.

In order to solve the problem of beam overlap in a multi-user environment that cannot be well resolved in some situations, an optimization method for MU-MIMO beam overlap is provided in an embodiment of the present application. The second communication device receives the transmission from the first communication device. The new channel matrix is decoded according to the new channel matrix to generate spatial stream data; please refer to FIG. 6, which is a schematic diagram of the basic flow of the method for optimizing MU-MIMO beam overlap provided by an embodiment of this application.

S601: Receive a new channel matrix sent by the first communication device.

It should be understood that when the second communication device receives the new channel matrix sent by the first communication device, it will save it at the local end, so that the new channel matrix can be used for subsequent decoding.

In an embodiment, before receiving the new channel matrix sent by the first communication device, at least the following steps are further included, as shown in FIG. 7:

S701: Receive a detection message sent by the first communication device.

S702: Send a channel state indication to the first communication device, where the channel state indication includes the original channel matrix of the second communication device.

It should be understood that when the second communication device receives the detection message sent by the first communication device, it calculates its channel matrix, which is referred to herein as the original channel matrix, and feeds it back to the first communication device through the channel state indicator.

S602: Perform decoding according to the new channel matrix to generate spatial stream data.

In an embodiment, before decoding according to the new channel matrix and generating spatial stream data, the method further includes: receiving a MU-MIMO data message sent by the first communication device; decoding according to the new channel matrix to generate spatial stream data, including at least The following steps are shown in Figure 8:

S801: Calculate the new channel matrix to obtain the channel inverse matrix.

It should be understood that when the first communication device decodes the MU-MIMO data message, it first takes out the new channel matrix saved at the local end, and calculates the new channel matrix to obtain the channel inverse matrix required for decoding; Yes, when the first communication device does not save the new channel matrix, the original channel matrix is calculated to obtain the channel inverse matrix, and further, decoding is performed according to the obtained channel inverse matrix.

S802: Calculate the channel inverse matrix according to the standard receiver algorithm, filter signals of other second communication devices except the second communication device itself, and generate spatial stream data.

In an embodiment, standard receiver algorithms include but are not limited to zero-forcing ZF or minimum mean square error MMSE.

The method for optimizing MU-MIMO beam overlap provided by the embodiment of the present application adopts that when the correlation between the original channel matrices corresponding to each second communication device is greater than a preset threshold, the first communication device adjusts each second communication device according to the preset deflection angle. Second, the original channel matrix corresponding to the communication device obtains the new channel matrix, and sends each new channel matrix to the corresponding second communication device; the second communication device receives the new channel matrix sent by the first communication device, and decodes according to the new channel matrix, Generate spatial stream data; solve the problem of beam overlap in a multi-user environment that is not well resolved in some situations. That is, the method for optimizing MU-MIMO beam overlap provided by the embodiment of the present application has at least the following advantages:

First: Compared with adding users to different groups for time-division multiplexing, the embodiment of the present application still processes signals in the spatial domain, avoiding MU-MIMO failure and making full use of bandwidth.

Second: By adjusting the beam direction to avoid beam overlap, it avoids the phenomenon of sensitivity to user location in MU-MIMO applications.

Third: The process is simple and easy to implement.

Fourth: Using a deep learning network to iteratively calculate the deflection angle, so that the overall performance is kept at the optimal level, and can be updated in time when the network environment changes, and it has better adaptability to changes in the WiFi network.

Embodiment two:

In order to solve the problem of beam overlap in a multi-user environment that cannot be well resolved in some situations, an optimization method for MU-MIMO beam overlap is provided in an embodiment of the present application, as shown in FIG. 9, as shown in FIG. 9. This is a schematic diagram of the basic flow of the method for optimizing MU-MIMO beam overlap provided in an embodiment of this application.

S901: When the correlation between the original channel matrices corresponding to each second communication device is greater than a preset threshold, the first communication device adjusts the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix;

S902: The first communication device sends each new channel matrix to the corresponding second communication device;

S903: The second communication device receives the new channel matrix sent by the first communication device;

S904: The second communication device performs decoding according to the new channel matrix to generate spatial stream data.

It is worth noting that, in order not to cumbersome descriptions, all the examples in the first embodiment are not fully described in the embodiments of the present application. It should be clear that all the examples in the first embodiment are applicable to the embodiments of the present application.

Example three:

On the basis of the first and second embodiments, the embodiments of this application provide a specific method for optimizing MU-MIMO beam overlap, as shown in FIG. 10:

The embodiment of the present application uses two second communication devices as an example.

S1001: The first communication device sends a detection message to each second communication device respectively.

S1002: The second communication device receives the detection message sent by the first communication device, and sends a channel state indicator to the first communication device, where the channel state indicator includes the original channel matrix of the second communication device.

S1003: The first communication device receives the channel state indication sent by each second communication device, calculates the correlation degree between the original channel matrices, and when the correlation degree is greater than a preset threshold, determines that each second communication device has a similar profile. PATH environment.

S1004: The first communication device generates a corresponding spatial mapping matrix for the transmitting antenna of each second communication device according to the preset deflection angle.

S1005: The first communication device transforms the original channel matrix of each second communication device by using each generated spatial mapping matrix to obtain each new channel matrix.

S1006: The first communication device sends each new channel matrix to the corresponding second communication device.

S1007: The second communication device receives and saves the new channel matrix sent by the first communication device.

S1008: The first communication device performs singular value decomposition on each new channel matrix, and calculates each precoding matrix.

S1009: The first communication device generates each MU-MIMO data message according to each precoding matrix.

S1010: The first communication device sends each MU-MIMO data packet to the corresponding second communication device.

S1011: When receiving the MU-MIMO data message sent by the first communication device, the second communication device calculates the new channel matrix to obtain the channel inverse matrix.

S1012: The second communication device calculates the channel inverse matrix according to the standard receiver algorithm, filters signals of other second communication devices except the second communication device itself, and generates spatial stream data.

The MU-MIMO beam overlap optimization method provided by the embodiment of the application adjusts the angle of each beam according to the deflection angle by combining the multipath environment of multiple users to regenerate a new beam direction, avoiding users with overlapping beams in the original space Mutual interference between.

Embodiment four:

In order to solve the problem of beam overlap in a multi-user environment in some situations, a first communication device is provided in an embodiment of this application. Please refer to FIG. 11, which is an implementation of this application. The example provides a schematic diagram of the structure of the first communication device.

The first communication device includes an adjustment module 1101 and a first sending module 1102, wherein:

The adjustment module 1101 is configured to adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold;

The first sending module 1102 is configured to send each new channel matrix to the corresponding second communication device.

In an embodiment, referring to FIG. 12, the first communication device further includes a first receiving module 1103 and a multipath environment determining module 1104, where:

The first sending module 1102 is also configured to send detection messages to each second communication device respectively;

The first receiving module 1103 is configured to receive a channel state indicator sent by each second communication device, where the channel state indicator includes the original channel matrix of the second communication device;

The multipath environment determination module 1104 is configured to calculate the correlation between the original channel matrices, and when the correlation is greater than a preset threshold, determine that each second communication device has a similar multipath environment.

It should be understood that in this embodiment of the application, when it is determined that the correlation between the original channel matrix corresponding to each second communication device is greater than the preset threshold, that is, when the beams of each second communication device have overlapping areas, it is necessary to check The original channel matrix of one or more of the second communication devices with overlapping beam beams is adjusted. In fact, it is only necessary to adjust the original channel matrix of one or more of the second communication devices so that the The beam overlap area can be reduced or eliminated. In practical applications, it can be flexibly adjusted according to specific application scenarios.

In an embodiment, as shown in FIG. 13, the first communication device further includes a deflection angle determination module 1105, where:

The deflection angle determination module 1105 is used to obtain the system parameters set by each second communication device and the first communication device; input each system parameter into the deep learning network, and the deep learning network outputs each deflection angle.

In an embodiment, the adjustment module 1101 correspondingly adjusts the original channel matrix corresponding to each second communication device according to each deflection angle to obtain a new channel matrix.

In one embodiment, according to the requirements of the 802.11 protocol, each second communication device and the first communication device will set system parameters, where the system parameters include but are not limited to throughput, modulation and coding scheme (Modulation and Coding Scheme, MCS) , Rate, bit error rate, etc.

In one embodiment, the deep learning network trains the weight of the system according to the principle of gradient descent. After multiple iterations, the overall performance of the system tends to be optimal. When the set threshold is reached, the training is stopped. At this time, the output deflection angle is Optimal deflection angle. It should be understood that the output deflection angle will have an impact on the performance of the system, which can be directly reflected in the changes in parameters such as throughput, MCS, rate, and bit error rate.

For a better understanding, here is an example for illustration.

In an embodiment, the adjustment module 1101 is configured to generate a corresponding spatial mapping matrix for the transmitting antenna of each second communication device according to a preset deflection angle; use the generated spatial mapping matrices to perform processing on the original channel matrix of each second communication device. Transform to obtain each new channel matrix; send each new channel matrix to the corresponding second communication device.

For a better understanding, here is an example for illustration.

In an embodiment, referring to FIG. 14, the first communication device further includes a precoding matrix calculation module 1106 and an encoding module 1107, where:

The precoding matrix calculation module 1106 is configured to perform singular value decomposition on each new channel matrix to calculate each precoding matrix;

The encoding module 1107 is configured to generate each MU-MIMO data message according to each precoding matrix.

It should be understood that the modules of the first communication device described above can be flexibly divided according to functions, and are not limited to the examples listed in the embodiments of this application. At the same time, the modules of the first communication device in the embodiments of this application Including but not limited to being implemented by a processor or other hardware devices.

In order to solve the problem of beam overlap in a multi-user environment that cannot be well resolved in some situations, a second communication device is provided in an embodiment of the present application. Please refer to FIG. 15 for an implementation of this application. The example provides a schematic diagram of the structure of the second communication device.

The second communication device includes a second receiving module 1501 and a decoding module 1502, where:

The second receiving module 1501 is configured to receive a new channel matrix sent by the second communication device;

The decoding module 1502 is used for decoding according to the new channel matrix to generate spatial stream data.

In an embodiment, referring to FIG. 16, the first communication device further includes a second sending module 1503, where:

The second receiving module 1501 is also configured to receive a detection message sent by the first communication device;

The second sending module 1503 is configured to send a channel state indicator to the first communication device, and the channel state indicator includes the original channel matrix of the second communication device.

In an embodiment, referring to FIG. 17, the first communication device further includes a channel matrix post-processing module 1504, where:

The second receiving module 1501 is also configured to receive MU-MIMO data packets sent by the first communication device;

The channel matrix post-processing module 1504 is configured to calculate the new channel matrix to obtain the channel inverse matrix;

The decoding module 1502 is used to calculate the channel inverse matrix according to the standard receiver algorithm, filter signals of other second communication devices except the second communication device itself, and generate spatial stream data.

It should be understood that the modules of the second communication device described above can also be flexibly divided according to functions, and are not limited to the examples listed in the embodiments of this application. At the same time, each module of the second communication device in the embodiments of this application Modules also include but are not limited to being implemented by processors or other hardware devices.

According to the first communication device and the second communication device provided by the embodiment of the present application, when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold, the first communication device adjusts each of them according to the preset deflection angle. The original channel matrix corresponding to the second communication device obtains a new channel matrix, and each new channel matrix is sent to the corresponding second communication device; the second communication device receives the new channel matrix sent by the first communication device, and decodes according to the new channel matrix , Generate spatial stream data; Solve the problem of beam overlap in a multi-user environment that is not well resolved in some situations. That is, the first communication device and the second communication device provided in the embodiments of the present application have at least the following advantages:

Third: The process is simple and easy to implement.

Embodiment five:

In order to solve the problem of beam overlap in a multi-user environment that cannot be well resolved in some situations, a system is provided in an embodiment of the present application. Please refer to FIG. 18, which is provided in an embodiment of this application. Schematic diagram of the system structure.

The system includes a first communication device 1801 and at least two second communication devices 1802, where:

The first communication device 1801 is configured to adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle when the correlation between the original channel matrix corresponding to each second communication device is greater than the preset threshold value, to obtain a new channel matrix , Sending each new channel matrix to the corresponding second communication device;

The second communication device 1802 is configured to receive the new channel matrix sent by the first communication device, perform decoding according to the new channel matrix, and generate spatial stream data.

It should be understood that in practical applications, the number of second communication devices included in the system can be flexibly adjusted according to specific application scenarios. For example, the number of second communication devices is 3, 4, or N, where N is greater than or equal to An integer of 2.

It is worth noting that, in order not to cumbersome descriptions, all the examples in the fourth embodiment are not fully described in the embodiments of the present application. It should be clear that all the examples in the fourth embodiment are applicable to the embodiments of the present application.

Embodiment 6:

The embodiment of the present application also provides a router. As shown in FIG. 19, the router provided in the embodiment of the present application includes a first processor 1901, a first memory 1902, and a first communication bus 1903, in which:

In the embodiment of the present application, the first communication bus 1903 is used to realize the connection and communication between the first processor 1901 and the first memory 1902, and the first processor 1901 is used to execute one or more stored in the first memory 1902 Procedure to achieve the following steps:

When each terminal has a similar multipath environment, adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix;

Send each new channel matrix to the corresponding terminal.

The embodiment of the present application also provides a terminal. As shown in FIG. 20, the terminal provided in the embodiment of the present application includes a second processor 2001, a second memory 2002, and a second communication bus 2003, wherein:

The second communication bus 2003 in the embodiment of the present application is used to realize the connection and communication between the second processor 2001 and the second memory 2002, and the second processor 2001 is used to execute one or more items stored in the second memory 2002 Procedure to achieve the following steps:

Receive the new channel matrix sent by the router;

Decode according to the new channel matrix to generate spatial stream data.

It is worth noting that, in order not to cumbersome descriptions, all the examples in the first to third embodiments are not fully described in the embodiments of the present application. It should be clear that all the examples in the first to third embodiments are applicable to the embodiments of the present application.

The embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores one or more first programs, and the one or more first programs can be executed by one or more processors to achieve the above The steps of the method for optimizing MU-MIMO beam overlap corresponding to the first communication device in the first to third embodiments; or, the computer-readable storage medium stores one or more second programs, and the one or more second programs It may be executed by one or more processors to implement the steps of the method for optimizing MU-MIMO beam overlap corresponding to the second communication device in the first to third embodiments.

The computer-readable storage medium includes volatile or nonvolatile, removable or Non-removable media. Computer-readable storage media include but are not limited to RAM (Random Access Memory), ROM (Read-Only Memory, read-only memory), EEPROM (Electrically Erasable Programmable read only memory, charged Erasable Programmable Read-Only Memory) ), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, Or any other medium that can be used to store desired information and that can be accessed by a computer.

The method, communication device and system for optimizing MU-MIMO beam overlap provided by the embodiments of the present invention are adopted by the first communication device according to the preset when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold. The deflection angle is adjusted to the original channel matrix corresponding to each second communication device to obtain a new channel matrix, and each new channel matrix is sent to the corresponding second communication device; the second communication device receives the new channel matrix sent by the first communication device according to the new channel matrix. The channel matrix is decoded to generate spatial stream data; it solves the problem of beam overlap in a multi-user environment that cannot be well resolved in the prior art. That is, the MU-MIMO beam overlap optimization method, communication device, and system provided by the embodiments of the present invention adjust the angle of each beam according to the deflection angle by combining the multipath environment of multiple users to regenerate a new beam direction, avoiding the original There is interference between users with overlapping beams in space.

Obviously, those skilled in the art should understand that all or some of the steps in the method disclosed above, the functional modules/units in the system, and the device can be implemented as software (which can be implemented by the program code executable by the computing device) , Firmware, hardware and their appropriate combination. In the hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may consist of several physical components. The components are executed cooperatively. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit . Such software may be distributed on a computer-readable medium and executed by a computing device. In some cases, the steps shown or described may be executed in a different order than here. The computer-readable medium may include computer storage. Medium (or non-transitory medium) and communication medium (or temporary medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile data implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Sexual, removable and non-removable media.

In addition, as is well known to those of ordinary skill in the art, communication media usually contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as carrier waves or other transmission mechanisms, and may include any information delivery media. . Therefore, this application is not limited to any specific combination of hardware and software.

The above content is a further detailed description of the embodiments of the application in combination with specific implementations, and it cannot be considered that the specific implementations of the application are limited to these descriptions. For those of ordinary skill in the technical field to which this application belongs, a number of simple deductions or substitutions can be made without departing from the concept of this application, and they should all be regarded as belonging to the scope of protection of this application.

Claims

An optimization method for MU-MIMO beam overlap, including:

When the correlation between the original channel matrices corresponding to each second communication device is greater than the preset threshold, adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix;

Sending each of the new channel matrices to the corresponding second communication device.
The method for optimizing MU-MIMO beam overlap according to claim 1, wherein the adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain the new channel matrix comprises:

Generating a corresponding spatial mapping matrix for the transmitting antenna of each second communication device according to the preset deflection angle;

The original channel matrix of each second communication device is transformed by using each generated spatial mapping matrix to obtain each new channel matrix.
The method for optimizing MU-MIMO beam overlap according to claim 1, wherein after the sending each of the new channel matrices to the corresponding second communication device, the method further comprises:

Performing singular value decomposition on each of the new channel matrices to calculate each precoding matrix;

Each MU-MIMO data message is generated according to each precoding matrix, and each MU-MIMO data message is sent to the corresponding second communication device.
The method for optimizing MU-MIMO beam overlap according to any one of claims 1 to 3, wherein the adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle, and before obtaining the new channel matrix, further comprises: :

Respectively sending a detection message to each of the second communication devices;

Receiving a channel state indication sent by each of the second communication devices, where the channel state indication includes the original channel matrix of the second communication device;

The correlation between the original channel matrices is calculated, and when the correlation is greater than a preset threshold, it is determined that each of the second communication devices has a similar multipath environment.
The method for optimizing MU-MIMO beam overlap according to any one of claims 1 to 3, wherein the adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle, and before obtaining the new channel matrix, further comprises: :

Acquiring system parameters set by each second communication device and the first communication device;

Inputting each of the system parameters into a deep learning network, and outputting each deflection angle from the deep learning network;

The adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain the new channel matrix includes:

The original channel matrix corresponding to each second communication device is adjusted correspondingly according to each said deflection angle to obtain a new channel matrix.
The MU-MIMO beam overlap optimization method of claim 5, wherein the deep learning network includes a convolutional neural network, a recurrent neural network, or a deep belief network.
An optimization method for MU-MIMO beam overlap, including:

Receiving a new channel matrix sent by the first communication device;

Perform decoding according to the new channel matrix to generate spatial stream data.
The method for optimizing MU-MIMO beam overlap according to claim 7, wherein before said receiving the new channel matrix sent by the first communication device, the method further comprises:

Receiving a detection message sent by the first communication device;

Send a channel state indicator to the first communication device, where the channel state indicator includes the original channel matrix of the second communication device.
8. The method for optimizing MU-MIMO beam overlap according to claim 7, wherein before said decoding according to said new channel matrix and generating spatial stream data, the method further comprises:

Receiving a MU-MIMO data message sent by the first communication device;

The decoding according to the new channel matrix to generate spatial stream data includes:

Calculating the new channel matrix to obtain a channel inverse matrix;

Calculate the channel inverse matrix according to the standard receiver algorithm, filter signals of other second communication devices except the second communication device itself, and generate spatial stream data.
An optimization method for MU-MIMO beam overlap, including:

When the correlation between the original channel matrices corresponding to each second communication device is greater than a preset threshold, the first communication device adjusts the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix, and Sending the new channel matrix to the corresponding second communication device;

The second communication device receives the new channel matrix sent by the first communication device, performs decoding according to the new channel matrix, and generates spatial stream data.
A first communication device, including an adjustment module and a first sending module;

The adjustment module is configured to adjust the original channel matrix corresponding to each second communication device according to the preset deflection angle to obtain a new channel matrix when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold;

The first sending module is configured to send each of the new channel matrices to the corresponding second communication device.
A second communication device, including a second receiving module and a decoding module;

The second receiving module is configured to receive a new channel matrix sent by a second communication device;

The decoding module is used for decoding according to the new channel matrix to generate spatial stream data.
A system including a first communication device and at least two second communication devices;

The first communication device is used for adjusting the original channel matrix corresponding to each second communication device according to the preset deflection angle when the correlation between the original channel matrix corresponding to each second communication device is greater than a preset threshold value, to obtain a new channel Matrix, sending each of the new channel matrices to the corresponding second communication device;

The second communication device is configured to receive a new channel matrix sent by the first communication device, perform decoding according to the new channel matrix, and generate spatial stream data.
A first communication device, comprising a memory and a processor; the memory stores a program, and when the program is read and executed by the processor, the MU-MIMO beam according to any one of claims 1 to 6 is realized Overlapping optimization methods.
A second communication device, comprising a memory and a processor; the memory stores a program, and when the program is read and executed by the processor, the MU-MIMO beam according to any one of claims 7 to 9 is realized Overlapping optimization methods.
A computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors, so as to implement claims 1 to 9 Any of the optimization methods for MU-MIMO beam overlap.