Multi-input multi-output communication method and system based on orthogonal time-frequency air conditioning

Abstract

The invention relates to the technical field of mobile communication, and discloses a multiple-input-multiple-output communication method and system based on orthogonal time-frequency air conditioning, and the method comprises the steps: obtaining spatial feature information in a channel of each user when the user requests a data sequence from a base station; distributing similar users into the same group based on the spatial feature information; adding the data sequences requested from the base station by the users in the same group to obtain common data; processing the common data by using the same radio frequency chain by using an orthogonal time-frequency modulation technology so as to determine an equivalent channel of the system; designing an optimal precoding of each group according to the equivalent channel to obtain an optimal precoding matrix; and pre-coding the common data of each group by using the pre-coding matrix, and transmitting the pre-coded common data to a target antenna of a corresponding user through a time-varying channel in a linear array form. The method and the device have the effects of reducing interference, improving communication efficiency and reducing communication cost.

Description

Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a multi-input multi-output communication method and system based on orthogonal time-frequency air modulation. Background Art

[0002] With the rapid development of technologies such as high-speed rail, drones, and new energy vehicles, high-speed scene communications in the next generation of mobile communication networks are becoming more and more common. Since the current mobile network is mainly based on orthogonal frequency division multiplexing (OFDM) technology, its performance in high-speed environments is not satisfactory. OFDM modulation technology divides the frequency band into several mutually orthogonal sub-bands, and avoids interference between frequency bands by using matching filters at the receiving end to achieve a higher total transmission rate. However, this method has extremely high requirements for the orthogonality between frequency bands. Literature has shown that even a frequency band overlap of only one percent can cause high mutual interference. Under the combined influence of Doppler frequency shift and multipath effects caused by high-speed movement, complex mutual superposition phenomena will occur between OFDM frequency bands, causing interference, greatly reducing communication efficiency.

[0003] To solve this problem, the current measures commonly adopted by operators are to reduce the center frequency of the carrier to minimize the impact of the Doppler effect. At the same time, frequency compensation technology is used to offset the frequency shift generated by each path to restore the orthogonality between each sub-band. However, these solutions reduce the available frequency band resources and cannot meet the requirements of high-speed communication. Summary of the invention

[0004] In order to reduce interference and improve communication efficiency, the present application provides a multiple-input multiple-output communication method and system based on orthogonal time-frequency air modulation.

[0005] In a first aspect, the present application provides a multiple-input multiple-output communication method based on orthogonal time-frequency air modulation.

[0006] This application is achieved through the following technical solutions:

[0007] A multiple-input multiple-output communication method based on orthogonal time-frequency air modulation comprises the following steps:

[0008] When a user requests a data sequence from the base station, spatial feature information in the channel of each user is obtained;

[0009] Based on the spatial feature information, similar users are assigned to the same group;

[0010] Performing an addition operation on the data sequences requested by users in the same group from the base station to obtain common data;

[0011] Using orthogonal time-frequency-air modulation technology, using the same radio frequency chain to process the common data to determine an equivalent channel of the system;

[0012] Designing an optimal precoding matrix for each group according to the equivalent channel to obtain an optimal precoding matrix;

[0013] After the common data of each group is precoded by using the precoding matrix, it is transmitted to the target antenna of the corresponding user via a time-varying channel in the form of a linear array.

[0014] In a preferred example, the present application may be further configured as follows: after the step of using the precoding matrix to precode the data sequence requested by the user to the base station, the step further includes:

[0015] Construct an optimal power allocation model;

[0016] Based on the total network transmission rate and in combination with the constraint that the lower the channel strength, the greater the transmission power allocated to the user, the optimal power allocation model is solved to obtain the maximum transmission rate matching the corresponding user;

[0017] After the common data of each group is precoded by using the precoding matrix, it is transmitted to the target antenna of the corresponding user in the form of a linear array through a time-varying channel at a maximum transmission rate matching the corresponding user.

[0018] In a preferred example, the present application may be further configured as follows: the step of assigning similar users to the same group based on the spatial feature information includes:

[0019] Preset number of groups;

[0020] Randomly select a user from all users, assign the user to the first group, and use the user as the center of the first group to determine the current center user;

[0021] S: Randomly select a target user from the remaining users, calculate the correlation between the channel of the target user and the channel of the current center user, until the correlation between the corresponding channels of all the remaining users and the channel of the current center user is determined, divide the target user with the smallest correlation into the next group as the center of the next group, and update the current center user;

[0022] Repeat step S until the centers of all groups are determined and all center users are obtained;

[0023] Based on the spatial feature information of the central user, construct an important feature base for each group, and based on the spatial feature information of the target user, construct a target feature base;

[0024] The chord distance between the target feature base of any target user and each of the important feature bases is calculated, and the target user is divided into a group with the shortest chord distance until all the remaining users are grouped.

[0025] In a preferred example, the present application can be further configured as follows: the step of using the orthogonal time-frequency-space modulation technology and using the same radio frequency chain to process the common data to determine the equivalent channel of the system includes:

[0026] converting the common data in the delay-Doppler domain into the frequency-time domain by discrete Fourier transform;

[0027] Using Zach transform, the common data in the frequency-time domain is converted from the frequency domain to the time domain to obtain a time series signal;

[0028] Superimpose the time series signals of all groups to obtain the requested data matrix;

[0029] Based on the request data matrix, an equivalent channel of the system is determined.

[0030] In a preferred example, the present application may be further configured as follows: after the step of superimposing all groups of time series signals to obtain the requested data matrix, the step further includes:

[0031] A cyclic prefix of a preset length is added to each element in the request data matrix, and the request data matrix is ​​updated, wherein the preset length is greater than the maximum delay of the system.

[0032] In a preferred example, the present application may be further configured as follows: the step of designing the optimal precoding of each group according to the equivalent channel to obtain the optimal precoding matrix includes:

[0033] Acquire the signal strengths of other groups of signals received by the same group of users, and construct a channel representation based on statistical features for each group in combination with the equivalent channel, including a channel feature dimension and a background noise feature dimension;

[0034] Based on the channel representation, obtaining an important feature set for each group;

[0035] The intersection of the important feature basis matrix in the important feature set and the null space feature basis matrix is ​​calculated to determine the optimal precoding for each group.

[0036] In a second aspect, the present application provides a multiple-input multiple-output communication system based on orthogonal time-frequency air modulation.

[0037] This application is achieved through the following technical solutions:

[0038] A multiple-input multiple-output communication system based on orthogonal time-frequency air modulation, comprising:

[0039] A spatial feature module, used to obtain spatial feature information in the channel of each user when the user requests a data sequence from the base station;

[0040] A grouping module, used for allocating similar users into the same group based on the spatial feature information;

[0041] A data superposition module is used to perform an addition operation on the data sequences requested by users in the same group from the base station to obtain common data;

[0042] A modulation module, used for using an orthogonal time-frequency-space modulation technique to process the common data using a same radio frequency chain to determine an equivalent channel of the system;

[0043] An optimal precoding module, used to design an optimal precoding for each group according to the equivalent channel to obtain an optimal precoding matrix;

[0044] The communication module is used to precode the common data of each group using the precoding matrix, and then transmit the precoding data to the target antenna of the corresponding user via a time-varying channel in a linear array form.

[0045] In a third aspect, the present application provides a computer device.

[0046] This application is achieved through the following technical solutions:

[0047] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned multiple-input multiple-output communication methods based on orthogonal time-frequency-air modulation are implemented.

[0048] In a fourth aspect, the present application provides a computer-readable storage medium.

[0049] This application is achieved through the following technical solutions:

[0050] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of any one of the above-mentioned multiple-input multiple-output communication methods based on orthogonal time-frequency and air-modulation.

[0051] In a fifth aspect, the present application provides a computer program product.

[0052] This application is achieved through the following technical solutions:

[0053] A computer program product comprises a computer program, wherein when the computer program is executed by a processor, the computer program implements the steps of any one of the above-mentioned multiple-input multiple-output communication methods based on orthogonal time-frequency-air modulation.

[0054] In summary, compared with the prior art, the technical solution provided by this application has at least the following beneficial effects:

[0055] When a user requests a data sequence from the base station, the spatial feature information of each user's channel is obtained, and similar users are assigned to the same group based on the spatial feature information, which is beneficial for simultaneously feeding back the request data of similar users and improving the utilization rate of frequency band resources; the data sequences requested by users in the same group from the base station are added to obtain common data, and the orthogonal time-frequency-space (OTFS) modulation technology is used to process the common data with the same radio frequency chain to determine the equivalent channel of the system, and the optimal precoding of each group is designed according to the equivalent channel to obtain the optimal precoding matrix, and the data sequence requested by the user from the base station is precoded by the precoding matrix and then transmitted through the time-varying channel in the form of a linear array. Transmitted to the target antenna of the corresponding user; through the use of channel spatial information, combined with the multiple-input multiple-output (MIMO) architecture, the signal is separated in space, similar users are assigned to the same group, and their request data sequences are modulated in the form of common data using the same RF chain, thereby reducing interference between users and improving the utilization rate of frequency band resources; and because the channel of the OTFS system is highly correlated with the spatial information of the signal propagation path, even in a high-speed mobile environment, the change of spatial information is on the order of tens of milliseconds, which is much longer than the coherence time of the orthogonal frequency division multiplexing (OFDM) channel under the same conditions, there is no need to frequently update the channel information, which improves communication efficiency and reduces communication costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A flowchart of a multiple-input multiple-output communication method based on orthogonal time-frequency and air-frequency modulation is provided for an exemplary embodiment of the present application.

[0057] Figure 2 A schematic diagram of the architecture of a multiple-input multiple-output communication system based on orthogonal time-frequency and air-frequency modulation is provided for an exemplary embodiment of the present application.

[0058] Figure 3 A structural block diagram of a multiple-input multiple-output communication system based on orthogonal time-frequency and air-frequency modulation is provided as an exemplary embodiment of the present application.

[0059] Description of reference numerals:

[0060] 101. Data sequence requested by any user to the base station; 102. User grouping; 103. Common data matrix; 104. OTFS modulation; 105. Request data matrix; 106. Precoding matrix; 107. Linear array antenna; 108. Time-varying channel; 109. Single antenna user. DETAILED DESCRIPTION

[0061] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make modifications to the present embodiment without any creative contribution as needed, but such modifications are protected by the patent law as long as they are within the scope of the claims of the present application.

[0062] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0063] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0064] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0065] Reference Figure 1 An embodiment of the present application provides a multi-input multi-output communication method based on orthogonal time-frequency and air-conditioning modulation, and the main steps of the method are described as follows.

[0066] S1: When a user requests a data sequence from the base station, the spatial feature information in the channel of each user is obtained;

[0067] S2: Based on the spatial feature information, similar users are assigned to the same group;

[0068] S3: performing an addition operation on the data sequences requested by users in the same group from the base station to obtain common data;

[0069] S4: using orthogonal time-frequency-air modulation technology and using the same radio frequency chain to process the common data to determine an equivalent channel of the system;

[0070] S5: designing an optimal precoding matrix for each group according to the equivalent channel to obtain an optimal precoding matrix;

[0071] S6: After precoding the common data of each group using the precoding matrix, the data is transmitted to the target antenna of the corresponding user in the form of a linear array via a time-varying channel.

[0072] In one embodiment, after the step of using the precoding matrix to precode the data sequence requested by the user to the base station, the method further includes:

[0073] Construct an optimal power allocation model;

[0074] Based on the total network transmission rate and in combination with the constraint that the lower the channel strength, the greater the transmission power allocated to the user, the optimal power allocation model is solved to obtain the maximum transmission rate matching the corresponding user;

[0075] After the common data of each group is precoded by using the precoding matrix, it is transmitted to the target antenna of the corresponding user in the form of a linear array through a time-varying channel at a maximum transmission rate matching the corresponding user.

[0076] In one embodiment, the step of assigning similar users to the same group based on the spatial feature information includes:

[0077] Preset number of groups;

[0078] Randomly select a user from all users, assign the user to the first group, and use the user as the center of the first group to determine the current center user;

[0079] S: Randomly select a target user from the remaining users, calculate the correlation between the channel of the target user and the channel of the current center user, until the correlation between the corresponding channels of all the remaining users and the channel of the current center user is determined, divide the target user with the smallest correlation into the next group as the center of the next group, and update the current center user;

[0080] Repeat step S until the centers of all groups are determined and all center users are obtained;

[0081] Based on the spatial feature information of the central user, construct an important feature base for each group, and based on the spatial feature information of the target user, construct a target feature base;

[0082] The chord distance between the target feature base of any target user and each of the important feature bases is calculated, and the target user is divided into the group with the shortest chord distance until all the remaining users are grouped.

[0083] In one embodiment, the step of using the orthogonal time-frequency-space modulation technique and using the same radio frequency chain to process the common data to determine the equivalent channel of the system includes:

[0084] converting the common data in the delay-Doppler domain into the frequency-time domain by discrete Fourier transform;

[0085] Using Zach transform, the common data in the frequency-time domain is converted from the frequency domain to the time domain to obtain a time series signal;

[0086] Superimpose the time series signals of all groups to obtain the requested data matrix;

[0087] Based on the request data matrix, an equivalent channel of the system is determined.

[0088] In one embodiment, after the step of superimposing all groups of time series signals to obtain the requested data matrix, the step further includes:

[0089] A cyclic prefix of a preset length is added to each element in the request data matrix, and the request data matrix is ​​updated, wherein the preset length is greater than the maximum delay of the system.

[0090] In one embodiment, the step of designing the optimal precoding of each group according to the equivalent channel to obtain the optimal precoding matrix includes:

[0091] Acquire the signal strengths of other groups of signals received by the same group of users, and construct a channel representation based on statistical features for each group in combination with the equivalent channel, including a channel feature dimension and a background noise feature dimension;

[0092] Based on the channel representation, obtaining an important feature set for each group;

[0093] The intersection of the important feature basis matrix in the important feature set and the null space feature basis matrix is ​​calculated to determine the optimal precoding for each group.

[0094] A multiple-input multiple-output communication method based on orthogonal time-frequency air modulation provides a precoding method based on spatial information for the next generation mobile communication network. According to the spatial information of each group, the optimal precoding matrix corresponding to each group is calculated to reduce inter-group interference.

[0095] A multiple-input multiple-output communication method based on orthogonal time-frequency air modulation extracts user spatial information based on eigenvalue decomposition to group users with similar channel information into the same group, and models the communication channel in a high-speed environment for the OTFS system, calculates the common eigenspace and optimal precoding matrix of each group, reduces interference between users, improves time slot resource utilization, and has lower communication costs.

[0096] Furthermore, in order to achieve a higher total network transmission rate, an optimal power allocation method based on OTFS modulation is innovatively designed to further suppress the intra-group interference of each group of users.

[0097] The detailed description of the above embodiments is as follows.

[0098] Reference Figure 2, it is assumed that the base station of the target mobile network is equipped with a uniform linear array antenna 107 (Uniform Linear Array), and the number of antenna units is M. There are K single-antenna users 109 in the network. The multi-antenna base station in the system supports multiple single antennas at the same time and is equipped with a preset number of RF chains.

[0099] There is a strong spatial correlation in the channels of high-speed mobile users, so the spatial feature information in the channels of each user is collected for subsequent user grouping 102 and non-orthogonal multiple access methods.

[0100] The data sequence 101 requested by any user to the base station will first be source coded and channel coded, and then modulated. In this embodiment, the data sequence requested by the kth user to the base station is taken as an example, and quaternary quadrature amplitude modulation (4QAM) can be used for modulation.

[0101] The system uses a multiple-input multiple-output MIMO architecture, which includes multiple RF chains to support the simultaneous communication needs of multiple users and improve the utilization of time slot resources.

[0102] The modulated symbols are put into resource units in the delay-Doppler domain to form data blocks. Such data blocks are represented as: k DD ∈C L×D , where C represents the complex space, L and D represent the length of the data block in the delay and Doppler domains, respectively.

[0103] The delay resolution and Doppler resolution of the system can be expressed as and Where Δf and T s Represent the bandwidth and symbol length of each sub-band respectively, and meet the following conditions:

[0104] T s Δf=1

[0105] In order to reduce inter-group interference and implement non-orthogonal multiple access (NOMA), users are divided into groups of g number, that is, user grouping 102 is determined and a common covariance matrix of each group is obtained.

[0106] In the first step of user grouping 102, the system will randomly select a user from all users as the center of the first group. In the second step, the system will randomly select a user from the remaining users and calculate the correlation between its channel and the channels of all existing center users. The calculation of the correlation is shown in the following formula:

[0107]

[0108] Among them G ′Indicates the number of current center users.

[0109] In each round of central user selection, the user with the smallest φ value will be selected as the central user of the next group.

[0110] The second step will be repeated until all G user groups have centers.

[0111] After all the central users are determined, the system needs to divide the ordinary users into each group in order. Assuming the current user is k, user k will calculate the chord distance (Chordal distance) with the important feature base of each group.

[0112] Distance):

[0113]

[0114] in, Represents the average characteristic basis of the g-th group:

[0115]

[0116] Among them, eig(·) represents the extraction operation of important feature bases.

[0117] Based on the spatial information of each user, the central user of each group is randomly found, and then the distance between the remaining user channels and the center of each user is compared, and the remaining users are classified into the most matching group, and finally the user grouping is completed.

[0118] The data sequences in each group are added together and then processed and precoded by the same RF chain. The total number of common data sequences generated by each group is equal to the total number of RF chains equipped in the system.

[0119] The data block in the delay-Doppler domain can be converted to the frequency-time domain by discrete Fourier transform, which is calculated as follows:

[0120]

[0121] Among them, F D represents the discrete Fourier matrix; {·} H represents the conjugate transpose.

[0122] In order to form a time series signal that can be transmitted, the orthogonal frequency division multiplexing OFDM symbol in the time-frequency domain will be converted from the frequency domain to the time domain. The conversion can be expressed as:

[0123]

[0124] When the two transformations are combined, the change in data is equivalent to the Zak Transform expressed as follows, that is, OTFS modulation 104:

[0125]

[0126] S g After transposing each column of , we can get the signal emitted in the time series:

[0127]

[0128] Among them, (s g,1 ) represents S g The first column of (·) T represents the transpose operation, represents the Kronecker product of matrices, express Since the mobile communication system studied in this embodiment uses a MIMO architecture, the system contains multiple radio frequency chains to support the simultaneous communication needs of multiple users. Therefore, multiple groups of data sequences can be sent simultaneously by the antenna array. When we superimpose the data sequences of each group together, we can get:

[0129]

[0130] Wherein, S represents the requested data matrix 105 after superimposing the data sequences of all groups, X DD Indicated by each The common data matrix 103 after superposition. The elements in the common data matrix 103 are the common data of each group of superposition.

[0131] Among them, Orthogonal Time-Frequency-Space (OTFS) modulation is a modulation method with high performance in high-speed environments and is considered to have the potential to become the main coding method for the next generation of communication networks. Unlike OFDM, which spreads data in the time-frequency domain, OTFS puts data in the delay-Doppler domain. Since the wireless channel in the time-frequency domain has an extremely short coherence time, the OFDM system in a high-speed environment needs to update the channel information very frequently, which brings extremely high communication costs. The channel of the OTFS system is highly correlated with the spatial information of the signal propagation path. Even in a high-speed mobile environment, the change in spatial information is on the order of tens of milliseconds, which is much longer than the coherence time of the OFDM channel under the same conditions. Therefore, the OTFS system is more suitable for communications in a high-speed mobile environment.

[0132] When using orthogonal time-frequency air modulation, the data sequence requested by the user is first modulated into the delay-Doppler domain, then the Zacks transform is used to form a data sequence in the time dimension, and finally transmitted to the user through a time-varying channel.

[0133] In order to prevent inter-code interference, it is necessary to g Add a length of N CP The cyclic prefix (CP) of the system needs to be larger than the longest delay value in the system, that is, τ max Represents the longest delay in the system.

[0134] After adding CP, the size of the request data matrix sent can be expressed as:

[0135]

[0136] Assume that the number of RF chains available in the system is exactly equal to the number of grouped sets.

[0137] The request data matrix needs to be pre-coded before transmission, and the final transmitted signal can be expressed as:

[0138] Z=P RF P BB (S CP ) T

[0139] Among them, P RF and P BB denote the analog precoding matrix and the digital precoding matrix respectively, and the size of Z is

[0140]

[0141] The transmitted signal first passes through a time-varying channel 108 and then reaches the single-antenna user 109, where the time-varying channel 108 is represented as:

[0142] h k,p (q) = α k,p a(θ k,p )

[0143] Among them, α k,p represents the gain of the pth path, a(θ k,p ) represents the guidance vector of the path and can be specifically expressed as:

[0144]

[0145] Where z represents the spacing between antennas, η represents the carrier wavelength, and θ represents the transmission angle of the path.

[0146] At single-antenna user 109, the received signal can be expressed as:

[0147]

[0148] in,[·] LD It represents the remainder calculation. The received signal needs to remove the CP, and the final length is the same as the created request data matrix.

[0149] If all the above steps are combined together, we can get the equivalent signal transmission in time series, which can be expressed as:

[0150]

[0151] Among them, k,p represents the displacement matrix, Δ k,p Is a diagonal matrix, each non-zero element in the diagonal matrix represents the corresponding Doppler frequency shift, and z represents the vector form of Z.

[0152] After receiving the time series signal, the user needs to convert the time series signal back to the delay-Doppler domain. The converted signal can be expressed as:

[0153]

[0154] in,

[0155] After obtaining the expression of the signal in the delay-Doppler domain, the equivalent channel of the system can be obtained, and a reasonable precoding method can be designed according to the channel to improve the overall transmission rate of the channel, including:

[0156] according to The data transmission can be expressed in the form of a matrix, namely:

[0157]

[0158] Among them, μ l,d,g,k,p represents the gain of precoding on this path, and can be simply expressed as Pa(θ k,p ), P=P T BB P T RF .

[0159] Meanwhile, the inter-group interference is defined as the signal strength of other group signals received by the user. It is assumed that digital precoding is used for power control, and the analog precoding matrix is ​​used for inter-user interference control. Therefore, the design of the analog precoding matrix (precoding matrix) 106 includes:

[0160] First, calculate the covariance matrix of the user's time-varying channel. The specific steps are as follows:

[0161]

[0162] Where E(·) represents the expected calculation.

[0163] In order to extract the spatial information of the time-varying channel, the covariance matrix is ​​decomposed by the following eigenvalue:

[0164]

[0165] in, Represents a column vector R k The matrix of eigenvectors of ; Λ k represents a diagonal matrix, each diagonal element corresponds to the eigenvalue of the eigenvector. It is assumed that the statistical characteristics of the channel remain unchanged within the same transmission interval.

[0166] In reality, not every path has a high gain, which is reflected in the eigenvalue decomposition as the eigenvalues ​​with large numerical differences. Therefore, it is assumed that for the kth user, it has high-value feature dimensions, and the remaining The intensity of the dimension is close to the background noise. So we can k and Λ k Divided into two parts:

[0167]

[0168] in, Included An important feature base, corresponding to The higher value of the eigenvalue in ; Included A weaker eigenvalue, corresponding to The lower eigenvalue.

[0169] Therefore, the user's channel based on statistical characteristics is expressed as:

[0170]

[0171] Among them, w k represents an independently distributed complex vector

[0172] Therefore U * and It can accurately represent the spatial information of user channels. By using this information, user grouping and precoding matrix design can be completed, including:

[0173] First, assuming that the kth user is assigned to the gth group, the precoding for the gth group can be expressed as:

[0174]

[0175] Among them, b g,i Indicates B g The i-th column of B g It will be introduced in detail later.

[0176] Based on the spatial information of each user group, all important feature bases in the system that do not belong to the gth group can be collected:

[0177]

[0178] Among them, K g Represents the number of all users in the gth group.

[0179] Next, use To express Ξ g The important characteristic basis matrix and the null space characteristic basis matrix of and U g By finding the intersection, we can find the characteristic basis that has a strong gain and does not interfere with other groups.

[0180] Based on this idea, we continue to construct the following covariance matrix:

[0181]

[0182] By performing eigenvalue decomposition on this covariance matrix: B g can be calculated:

[0183]

[0184] Among them, G * g Represents G g The important feature base.

[0185] This embodiment calculates the covariance matrix of each user channel and performs eigenvalue decomposition; finds the important eigenvalue base sets of all remaining users and synthesizes them into a matrix; finds the null space basis of the matrix; then uses the null space basis and the important eigenvalue bases of the target user to generate a new covariance matrix; and calculates the important eigenvalue bases of the new covariance matrix.

[0186] In the above manner, the optimal precoding matrix 106 for the system can be calculated for each group. It is worth noting that the precoding matrix obtained in this manner cannot completely remove the interference caused by the g-th group to the other groups, because There may still be Similar characteristic bases, so the interference still exists. The eigenvalues ​​corresponding to the basis in are generally low, so the interference generated is also relatively limited and can be ignored.

[0187] When the common data of each group is precoded using the precoding matrix, a common subset of the important characteristic basis space of each group and the null space of all remaining groups is found, and the bases in all common subsets are added together to obtain a larger channel gain while reducing interference to other groups.

[0188] So far, the grouping of NOMA users and the precoding method based on spatial separation have been completed. The interference between each user group has been well controlled.

[0189] In order to further improve the overall transmission rate of the network, the transmission power of NOMA users needs to be well distributed to further suppress the interference within the group.

[0190] Specifically, in order to better analyze the intra-group interference, taking the g-th group as an example, the superimposed data block can be expressed as:

[0191]

[0192] Among them, γ k represents the power allocated to user k, K g represents the number of users in the gth group. For user k, the data it receives can be divided into two parts: the data originally sent to k and the interference from other users in the group:

[0193]

[0194] in, represents the intra-group interference suffered by user k.

[0195] In order to calculate the total transmission rate of the entire network, it is necessary to add up the independent transmission rates of each user, as shown below:

[0196]

[0197] Among them, Γ k represents the signal to noise interference ratio of user k: represents the noise energy.

[0198] Due to the power allocation requirements of the NOMA system, higher power needs to be allocated to users with lower channel strength, and the total power is limited to P g In order to obtain the optimal power allocation, the following problems need to be solved:

[0199]

[0200] stγ1+γ2+…+γ Kg =P g

[0201] Since this problem is a convex optimization problem, it can be solved using the Laplace equation, namely:

[0202]

[0203] Where λ represents the Laplace multiplier, which is obtained by Taking partial derivatives, we can get:

[0204]

[0205] By finding the γ when the partial derivative is equal to zero k Get the optimal solution.

[0206] The non-orthogonal multiple access method allocates power to data blocks in the delay-Doppler domain based on the channel information of the same group of users. Under the condition of the set maximum power sum, the Laplace equation is used to find the optimal solution that can maximize the transmission rate and complete the optimal power allocation.

[0207] In summary, a multi-input multi-output communication method based on orthogonal time-frequency-space modulation obtains spatial feature information in the channel of each user when a user requests a data sequence from a base station, and allocates similar users to the same group based on the spatial feature information, which is beneficial to simultaneously feedback the request data of similar users and to improve the utilization rate of frequency band resources; the data sequences requested by users in the same group from the base station are added to obtain common data, and the OTFS modulation technology is used to process the common data with the same radio frequency chain to determine the equivalent channel of the system, and the optimal precoding of each group is designed according to the equivalent channel to obtain the optimal precoding matrix, and the data sequence requested by the user from the base station is processed by using the precoding matrix. After precoding, it is transmitted to the target antenna of the corresponding user in the form of a linear array through a time-varying channel. By utilizing the channel spatial information and combining it with the MIMO architecture, the signal is separated in space, and similar users are assigned to the same group. Their request data sequences are modulated in the form of common data using the same RF chain, thereby reducing interference between users and improving the utilization rate of frequency band resources. Moreover, because the channel of the OTFS system is highly correlated with the spatial information of the signal propagation path, even in a high-speed mobile environment, the change in spatial information is on the order of tens of milliseconds, which is much longer than the coherence time of the OFDM channel under the same conditions. There is no need to frequently update the channel information, which improves communication efficiency and reduces communication costs.

[0208] In addition, by integrating NOMA technology, after grouping users according to the spatial information of the channel, the optimal power is allocated to each user to reduce intra-group interference and further improve the overall network transmission rate.

[0209] A multiple-input multiple-output communication method based on orthogonal time-frequency air modulation can separate signals in space by utilizing channel spatial information, combining MIMO architecture and OTFS modulation, thereby reducing interference between users; by further integrating NOMA technology, it can support a large number of users at the same time and improve the overall transmission rate of the system network.

[0210] A multiple-input multiple-output communication method based on orthogonal time-frequency-air modulation is mainly used in multi-user systems based on OTFS modulation in high-speed environments. The users in the system have the characteristics of high-speed mobility, their channels change rapidly in the time dimension, and the coherence time is extremely short. The data of each user uses the same time and spectrum resources in transmission, first reducing inter-group interference through spatial separation, and then reducing intra-group interference through the continuous interference elimination method of non-orthogonal multiple access.

[0211] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0212] Reference Figure 3 The embodiment of the present application also provides a multi-input multi-output communication system based on orthogonal time-frequency air modulation, and the multi-input multi-output communication system based on orthogonal time-frequency air modulation corresponds one-to-one with a multi-input multi-output communication method based on orthogonal time-frequency air modulation in the above embodiment. The multi-input multi-output communication system based on orthogonal time-frequency air modulation includes:

[0213] A spatial feature module, used to obtain spatial feature information in the channel of each user when the user requests a data sequence from the base station;

[0214] A grouping module, used for allocating similar users into the same group based on the spatial feature information;

[0215] A data superposition module is used to perform an addition operation on the data sequences requested by users in the same group from the base station to obtain common data;

[0216] A modulation module, used for using an orthogonal time-frequency-space modulation technique to process the common data using a same radio frequency chain to determine an equivalent channel of the system;

[0217] An optimal precoding module, used to design an optimal precoding for each group according to the equivalent channel to obtain an optimal precoding matrix;

[0218] The communication module is used to precode the common data of each group using the precoding matrix, and then transmit the precoding data to the target antenna of the corresponding user via a time-varying channel in a linear array form.

[0219] Furthermore, a multiple-input multiple-output communication system based on orthogonal time-frequency modulation also includes:

[0220] The optimal power module is used to construct an optimal power allocation model; based on the total network transmission rate, combined with the constraint that the lower the channel strength, the greater the transmission power allocated to the user, the optimal power allocation model is solved to obtain the maximum transmission rate matching the corresponding user.

[0221] For the specific definition of a multiple-input multiple-output communication system based on orthogonal time-frequency air modulation, please refer to the definition of a multiple-input multiple-output communication method based on orthogonal time-frequency air modulation in the above text, which will not be repeated here.

[0222] Each module in the above-mentioned multi-input multi-output communication system based on orthogonal time-frequency air modulation can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0223] In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, any of the above-mentioned multi-input and multi-output communication methods based on orthogonal time-frequency and air modulation is implemented.

[0224] In one embodiment, a computer-readable storage medium is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any one of the above-mentioned multiple-input multiple-output communication methods based on orthogonal time-frequency-air modulation is implemented.

[0225] In one embodiment, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, any one of the above-mentioned multiple-input multiple-output communication methods based on orthogonal time-frequency and air-space modulation is implemented.

[0226] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. When the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0227] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A multiple-input multiple-output communication method based on orthogonal time-frequency modulation, characterized in that: The following steps are included: When a user requests a data sequence from the base station, spatial feature information in the channel of each user is obtained; Based on the spatial feature information, similar users are assigned to the same group; Performing an addition operation on the data sequences requested by users in the same group from the base station to obtain common data; Using orthogonal time-frequency-air modulation technology, using the same radio frequency chain to process the common data to determine an equivalent channel of the system; Designing an optimal precoding matrix for each group according to the equivalent channel to obtain an optimal precoding matrix; After the common data of each group is precoded by using the precoding matrix, it is transmitted to the target antenna of the corresponding user via a time-varying channel in the form of a linear array.

2. The multiple-input multiple-output communication method based on orthogonal time-frequency modulation according to claim 1, characterized in that: After the step of precoding the common data of each group using the precoding matrix, the method further includes: Construct an optimal power allocation model; Based on the total network transmission rate and in combination with the constraint that the lower the channel strength, the greater the transmission power allocated to the user, the optimal power allocation model is solved to obtain the maximum transmission rate matching the corresponding user; After the common data of each group is precoded by using the precoding matrix, it is transmitted to the target antenna of the corresponding user in the form of a linear array through a time-varying channel at a maximum transmission rate matching the corresponding user.

3. The multiple-input multiple-output communication method based on orthogonal time-frequency modulation according to claim 1, characterized in that: The step of assigning similar users to the same group based on the spatial feature information includes: Preset number of groups; Randomly select a user from all users, assign the user to the first group, and use the user as the center of the first group to determine the current center user; S: Randomly select a target user from the remaining users, calculate the correlation between the channel of the target user and the channel of the current center user, until the correlation between the corresponding channels of all the remaining users and the channel of the current center user is determined, divide the target user with the smallest correlation into the next group as the center of the next group, and update the current center user; Repeat step S until the centers of all groups are determined and all center users are obtained; Based on the spatial feature information of the central user, construct an important feature base for each group, and based on the spatial feature information of the target user, construct a target feature base; The chord distance between the target feature base of any target user and each of the important feature bases is calculated, and the target user is divided into a group with the shortest chord distance until all the remaining users are grouped.

4. The multiple-input multiple-output communication method based on orthogonal time-frequency modulation according to claim 1, characterized in that: The step of using orthogonal time-frequency-space modulation technology and adopting the same radio frequency chain to process the common data to determine the equivalent channel of the system includes: converting the common data in the delay-Doppler domain into the frequency-time domain by discrete Fourier transform; Using Zach transform, the common data in the frequency-time domain is converted from the frequency domain to the time domain to obtain a time series signal; Superimpose the time series signals of all groups to obtain the requested data matrix; Based on the request data matrix, an equivalent channel of the system is determined.

5. The multiple-input multiple-output communication method based on orthogonal time-frequency modulation according to claim 4, characterized in that: After the step of superimposing the time series signals of all groups to obtain the requested data matrix, the method further includes: A cyclic prefix of a preset length is added to each element in the request data matrix, and the request data matrix is ​​updated, wherein the preset length is greater than the maximum delay of the system.

6. The multiple-input multiple-output communication method based on orthogonal time-frequency air modulation according to any one of claims 1 to 5, characterized in that: The step of designing the optimal precoding of each group according to the equivalent channel to obtain the optimal precoding matrix comprises: Acquire the signal strengths of other groups of signals received by the same group of users, and construct a channel representation based on statistical features for each group in combination with the equivalent channel, including a channel feature dimension and a background noise feature dimension; Based on the channel representation, obtaining an important feature set for each group; The intersection of the important feature basis matrix in the important feature set and the null space feature basis matrix is ​​calculated to determine the optimal precoding for each group.

7. A multiple-input multiple-output communication system based on orthogonal time-frequency modulation, characterized in that: include, A spatial feature module, used to obtain spatial feature information in the channel of each user when the user requests a data sequence from the base station; A grouping module, used for allocating similar users into the same group based on the spatial feature information; A data superposition module is used to perform an addition operation on the data sequences requested by users in the same group from the base station to obtain common data; A modulation module, used for using an orthogonal time-frequency-space modulation technique to process the common data using a same radio frequency chain to determine an equivalent channel of the system; An optimal precoding module, used to design an optimal precoding for each group according to the equivalent channel to obtain an optimal precoding matrix; The communication module is used to precode the common data of each group using the precoding matrix, and then transmit the precoding data to the target antenna of the corresponding user via a time-varying channel in a linear array form.

8. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 6 when being executed by a processor.

Images