Resource allocation method and related equipment based on orthogonal time-frequency-space system

Abstract

The present application provides a resource allocation method and related equipment based on an orthogonal time-frequency-space system. Based on a communication network composed of multiple high-mobility users and base stations, a simplified NIMP algorithm is used to allocate resource grids to multiple high-mobility users for ideal pulse waveforms that meet dual-orthogonality conditions, and power allocation between different high-mobility users is achieved through the IA‑WF algorithm. For non-ideal pulse waveforms that do not meet dual-orthogonality conditions, the GSMA algorithm is used to allocate resource grids to multiple high-mobility users. Based on the allocated resource grids, power allocation between different high-mobility users is achieved through a genetic algorithm, and the throughput of the entire system under non-ideal pulse waveform conditions is maximized. Taking full account of the differences in channel conditions, the minimum unit of DD domain resources is allocated to each high-mobility user, and corresponding power allocation schemes are established for both ideal and non-ideal pulses, thereby improving system energy efficiency.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a resource allocation method based on an orthogonal time-frequency-space system and related equipment. Background Art

[0002] In high-mobility communication scenarios, wireless channels have fast time-varying characteristics and are doubly dispersed in nature, that is, multipath effects lead to time dispersion, and Doppler frequency shift leads to frequency dispersion. Traditional multi-carrier modulation technologies such as Orthogonal Frequency Division Multiplexing (OFDM) are mainly used to combat the multipath effects that cause inter-symbol interference (ISI), but cannot eliminate inter-carrier interference (ICI) caused by Doppler frequency shift. Orthogonal Time-Frequency Space Modulation (OTFS) is a new modulation technology suitable for doubly dispersed wireless channels, and can be achieved through pre-processing and post-processing in the OFDM system. At the same time, it converts fast time-varying channels into slowly varying channels in the delay-Doppler (DD) domain, which can simplify the design of receivers and detectors.

[0003] With the increase in the number of high-mobility users in wireless communication, the resource allocation method adopted in the related technology is generally to allocate resources between low-mobility users and fewer high-mobility users, without considering the power allocation among multiple high-mobility users. In addition, the related technology generally takes the window function under assumed ideal conditions as a prerequisite, and only considers the ideal condition of dual orthogonality of the transmitted pulse wave and the received pulse wave, and lacks a resource allocation method that combines the window function under ideal conditions and non-ideal conditions. Summary of the invention

[0004] In view of this, the purpose of the present application is to propose a resource allocation method based on an orthogonal time-frequency-space system and related equipment to solve the above problems.

[0005] Based on the above purpose, the first aspect of the present application provides a resource allocation method based on an orthogonal time-frequency-space system, comprising:

[0006] Performing a sparse inverse fast Fourier transform on the transmit signal converted into the DD domain to convert the transmit signal into the TF domain;

[0007] In response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain satisfy a biorthogonal condition, after the transmission signal is converted to the time domain and a cyclic prefix CP is added, a first channel model is established;

[0008] Based on the first channel model, allocating the resource grid to the plurality of the high mobility users by a simplified centralized matching NIMP algorithm;

[0009] In response to determining that the resource grid is allocated, allocating power to the plurality of high-mobility users by using an iterative IA-WF algorithm based on a water filling algorithm;

[0010] In response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain do not satisfy the biorthogonality condition, after the transmission signal is converted to the time domain and the cyclic prefix CP is added, a second channel model is established;

[0011] Based on the second channel model, allocating the resource grid to the plurality of the high mobility users by using a deferred acceptance matching GSMA algorithm;

[0012] In response to determining that the resource grid is completely allocated, power is allocated to the plurality of high-mobility users by using a genetic algorithm.

[0013] A second aspect of the present application provides a resource allocation device for an orthogonal time-frequency-space system, comprising:

[0014] A signal conversion module is configured to: perform a sparse inverse fast Fourier transform on the transmission signal converted to the DD domain to convert the transmission signal to the TF domain;

[0015] The model building module is configured to: in response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain meet the biorthogonal condition, after the transmission signal is converted into the time domain and a cyclic prefix CP is added, establish a first channel model;

[0016] A grid allocation module is configured to: allocate the resource grid to the plurality of the high-mobility users through a simplified centralized matching NIMP algorithm based on the first channel model;

[0017] A power allocation module is configured to: in response to determining that the resource grid is allocated, allocate power to the plurality of high-mobility users by using an iterative IA-WF algorithm based on a water injection algorithm;

[0018] The model building module is further configured to: in response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain do not satisfy the biorthogonal condition, establish a second channel model after the transmission signal is converted to the time domain and the cyclic prefix CP is added;

[0019] The grid allocation module is further configured to: allocate the resource grid to the plurality of the high mobility users through a deferred acceptance matching GSMA algorithm based on the second channel model;

[0020] The power allocation module is further configured to: in response to determining that the resource grid allocation is complete, allocate power to the plurality of high-mobility users by using a genetic algorithm.

[0021] The third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the present application is implemented.

[0022] The fourth aspect of the present application provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the method provided by the first aspect of the present application.

[0023] From the above, it can be seen that the resource allocation method and related equipment based on the orthogonal time-frequency-space system provided by the present application are based on a communication network composed of multiple high-mobility users and base stations, which increases the number of high-mobility users in communication and has stronger versatility. First, the transmission signal at the base station end is converted to the DD domain with a slowly changing channel, and the transmission signal is converted to the TF domain after sparse inverse fast Fourier transform; in the TF domain, for the ideal pulse waveform that meets the dual orthogonal condition, the simplified NIMP algorithm is used to allocate resource grids to multiple high-mobility users, and based on the allocated resource grids, the iterative IA-WF algorithm of the water injection algorithm is used to achieve power allocation between different high-mobility users, and the throughput of the entire system under the ideal pulse waveform condition is maximized. For non-ideal pulse waveforms that do not meet the dual orthogonal condition, the GSMA algorithm is used to allocate resource grids to multiple high-mobility users, and based on the allocated resource grids, the power allocation between different high-mobility users is achieved through the genetic algorithm, and the throughput of the entire system under the non-ideal pulse waveform condition is maximized. Taking full account of differences in channel conditions, the smallest unit of DD domain resources is allocated to each high-mobility user, and corresponding power allocation schemes are established for both ideal and non-ideal pulses, thereby improving system energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic diagram of an OTFS system according to an embodiment of the present application;

[0026] Figure 2 This is a flow chart of a resource allocation method based on an orthogonal time-frequency-space system according to an embodiment of the present application;

[0027] Figure 3 This is a schematic diagram of a downlink OTFS-NOMA resource allocation scenario in an embodiment of the present application;

[0028] Figure 4 A power allocation flow chart under the ideal waveform condition of integer Doppler shift according to an embodiment of the present application;

[0029] Figure 5 A flowchart of resource grid allocation under the ideal waveform condition of integer Doppler shift in an embodiment of the present application;

[0030] Figure 6 A flowchart of resource grid allocation under non-ideal waveform conditions of fractional Doppler shift in an embodiment of the present application;

[0031] Figure 7 NIMPMA (simplified NIMP) algorithm flow chart of the embodiment of the present application;

[0032] Figure 8 This is a flow chart of the IA-WF algorithm of an embodiment of the present application;

[0033] Fig. 9 A power allocation flow chart under non-ideal waveform conditions of fractional Doppler shift according to an embodiment of the present application;

[0034] Fig.10 GSMA algorithm flow chart of the embodiment of the present application;

[0035] Fig.11 This is a simulation comparison diagram of the convergence process of the matching algorithm of the embodiment of the present application;

[0036] Fig.12 A rate comparison diagram of the system of three power allocation schemes under different total powers in an embodiment of the present application;

[0037] Fig.13 This is a convergence comparison diagram of three matching algorithms under the rectangular window function condition of an embodiment of the present application;

[0038] Fig.14 This is a comparison diagram of the sum rate of three power allocation algorithms under different total powers in an embodiment of the present application;

[0039] Fig.15 This is a structural diagram of a resource allocation device based on an orthogonal time-frequency-space system according to an embodiment of the present application;

[0040] Fig.16 A structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0042] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0043] In some related technologies, NOMA is applied to the NOMA scenario of a highly mobile OTFS user and multiple low-mobility OFDM users. Multiple users share the same communication resources, which improves spectrum utilization. The signal-to-interference-noise ratio and interruption probability formulas are derived, and power allocation is performed in the OTFS-NOMA system consisting of two highly mobile users. However, the number of highly mobile users in this related technology is small, and it is impossible to solve the clustering and power allocation problems in multi-user scenarios.

[0044] In some related technologies, a power allocation method based on the OTFS-NOMA system is also disclosed. This method considers a NOMA system consisting of a high-mobility user and two multi-mobility users. The power of the three is allocated on the condition that the minimum rate of the low-mobility user is greater than the rate of the high-mobility user. The superimposed signal is demodulated step by step using the serial interference cancellation SIC (Successive Interference Cancellation) method at the receiving end. The application embodiment considers a communication network consisting of multiple high-mobility users, and allocates power with the system and rate as the maximization goal, thereby improving the system energy efficiency.

[0045] In some related technologies, a multi-user multiplexing method for allocating DD domain resources to multiple users in the downlink is disclosed. In this method, the DD domain resources are divided into multiple segments, one or more resources in the multiple segments are allocated to each user, and the signal sending and receiving process including equalization is designed. In order to increase spectrum utilization and improve system energy efficiency, it is necessary to consider resource allocation in multiple high-speed mobile user scenarios. Different from the time-frequency domain TF (Time-Frequency) resource allocation method in the OFDM system, due to the signal transmission characteristics of the DD domain in the OTFS system, under the ideal pulse condition represented by the ideal window function, the DD domain signal does not have the strict orthogonal characteristics of the TF domain signal, and most of the research focuses on assuming the ideal window function condition, only considering the dual orthogonal conditions of the transmitted pulse and the received pulse, and most of the research only considers the integer part of the Doppler, and the fractional Doppler is ignored.

[0046] The embodiment of the present application fully considers the differences in channel conditions, allocates the smallest unit of DD domain resources to each high-mobility user, and establishes corresponding power allocation schemes for ideal and non-ideal pulses. The algorithm has a smaller granularity and a more precise allocation, which can achieve higher systems and rates while taking into account actual conditions, thereby improving system energy efficiency.

[0047] In some embodiments, Figure 1 As shown, in the downlink of the orthogonal time-frequency-space system, a transmission signal is generated at the base station end, and the transmission signal is converted into a reception signal received by the receiving end via the delay-Doppler DD domain. The receiving end includes multiple high-mobility users, and the DD domain is a resource grid of NM dimensions; then the resource allocation method based on the orthogonal time-frequency-space system is as follows: Figure 2 As shown, including:

[0048] Step 100: Perform sparse inverse fast Fourier transform on the transmission signal converted into the DD domain to convert the transmission signal into the TF domain.

[0049] Step 200 includes:

[0050] Step 211: In response to determining that the transmitted waveform and the received waveform of the pulse wave in the TF domain satisfy the biorthogonal condition, after the transmitted signal is converted to the time domain and a cyclic prefix CP is added, a first channel model is established.

[0051] Step 212: Based on the first channel model, resource grids are allocated to multiple high-mobility users by using a simplified centralized matching NIMP algorithm.

[0052] Step 213: In response to determining that the resource grid allocation is complete, power is allocated to multiple high-mobility users by using an iterative IA-WF algorithm based on a water filling algorithm.

[0053] Step 221: In response to determining that the transmitted waveform and the received waveform of the pulse wave in the TF domain do not satisfy the biorthogonal condition, after the transmitted signal is converted to the time domain and a cyclic prefix CP is added, a second channel model is established.

[0054] Step 222: Based on the second channel model, resource grids are allocated to multiple high-mobility users through a deferred acceptance matching GSMA algorithm.

[0055] Step 223: In response to determining that the resource grid allocation is complete, power is allocated to multiple high-mobility users by using a genetic algorithm.

[0056] Among them, the physical layer signal transmission process of the orthogonal time-frequency-space OTFS modulation technology system is as follows: Figure 1 As shown. At the transmitting end, after the transmitted signal enters the Delay-Doppler DD (Delay-Doppler), the DD domain signal is transformed by ISFFT (Sparse Fast Fourier Transform) in turn, and converted to a time domain signal after sending a pulse. After adding a cyclic prefix CP (Cyclic Prefix), it passes through the channel, removes the CP, and receives the pulse before being transformed into a DD domain signal by SFFT (Sparse Fast Fourier Transform). After equalization and detection, the received signal is obtained.

[0057] It should be noted that if Figure 3 As shown, the embodiment of the present application uses multiple high-mobility users (such as drones) to form the downlink of the communication network, which increases the number of high-mobility users in communication and has stronger versatility. A base station is used to send communication signals to high-mobility users, where each drone has a different mobile configuration, and the base station can obtain perfect channel state information CSI (Channel Statement Information) of each drone. Figure 3In the downlink of the OTFS-NOMA system shown, resources are first allocated based on CSI information at the base station: drones are clustered, and users in the same cluster share the same DD domain resource grid, that is, users are matched with resource grids. Then, at the base station, considering the differences in channel conditions, power is allocated between resource grids and between drone users based on NOMA. Users with poor channels are allocated higher power. The minimum unit of DD domain resources is allocated to each high-mobility user, and corresponding power allocation schemes are established for ideal and non-ideal pulses, thereby improving the energy efficiency of the system. The ideal pulse is a TF domain pulse wave whose transmitting waveform and receiving waveform meet the dual orthogonal condition, and the non-ideal pulse is a TF domain pulse wave whose transmitting waveform and receiving waveform do not meet the dual orthogonal condition. Finally, at each receiving end, strong users with higher allocated power are demodulated first, and the demodulated information is broadcast to other users in the same cluster, thereby reducing co-channel interference. Assume that all users and base stations are equipped with a single antenna. There are U drone users in this downlink scenario, and the set Indicates that there are J between the base station and each user u The base station sends signals distributed in the NM-dimensional DD domain, using the set and Represents the index of the Doppler dimension and delay dimension in the NM-dimensional DD domain.

[0058] In some embodiments, Figure 5 As shown, step 212 includes:

[0059] Step 2121: Based on the first channel model, determine the signal-to-noise ratio (SNR) of each high-mobility user in the DD domain after being equalized by the decision feedback equalizer (DFE);

[0060] Step 2122: Based on the SNR, determine a signal to interference plus noise ratio SINR based on a non-orthogonal multiple access NOMA condition;

[0061] Step 2123: constructing a user preference list of high mobility users and a grid preference list of DD domain resource grids respectively;

[0062] Step 2124: Based on the SINR, resource grids are allocated to multiple high-mobility users using a simplified NIMP algorithm.

[0063] In some embodiments, Figure 6 As shown, step 222 includes:

[0064] Step 2221: determining a signal input-output relationship and interference terms in the TF domain of the transmitted signal through the second channel model, and determining a signal input-output relationship and interference terms in the DD domain of the transmitted signal through the second channel model;

[0065] Step 2222: Simplify the DD domain channel matrix based on the second channel model;

[0066] Step 2223: Calculate SINR under NOMA conditions;

[0067] Step 2224: Based on SINR, resource grids are allocated to multiple high-mobility users using the GSMA algorithm.

[0068] Among them, Figure 4 As shown, the specific process of step 211 to step 213 under the ideal pulse waveform condition of integer Doppler shift is as follows:

[0069] 1. The channel form in the constructed first channel model is multipath channel, where h u,j represents the channel gain coefficient of user u in the jth path, τ u,j represents the delay of user u on the jth path, υ u,j represents the Doppler shift value of user u on the jth path, and τ u,j =(l u,j +l′ u,j ) / (MΔf),υ u,j =(k u,j +k′ u,j ) / (NT), l u,j With k u,j is a non-negative integer, l′ u,j ,k′ u,j is the decimal part. Assuming that M and N are large enough, the decimal part of the numerator can be ignored. If the transmitted waveform and received waveform of the TF domain pulse wave are ideal waveforms and meet the biorthogonal condition, the signal input and output relationship of the TF domain is Y u [n,m]=H u [n,m]X[n,m], the DD domain signal transmission and reception relationship is Rewritten in vector form as y u =H u x+z u , where H u is a block circulant matrix, representing the DD domain channel of the link from the base station to the u-th user, and its specific structure is as follows:

[0070]

[0071] Among them B n For h u,j An M×M matrix determined by , k and l.

[0072] 2. By H uFrom the matrix characteristics, we can see that there is still inter-symbol interference in the OTFS system, so DFE equalization is used. The output after equalization is in, represents the signal after the decision at the u-th user, represents the feed-forward part of the equalizer, G u =L u -I NM Represents the feedback part of the equalizer, L u By H u The Cholesky decomposition of D u is a MN×MN diagonal matrix, which is substituted into the equalization output. Consider the perfect decision of the signal, that is, but The covariance matrix of the noise calculated according to the signal form is: Therefore, the signal-to-noise ratio (SNR) of user u at the [k, l] resource grid is expressed as

[0073] 3. From step 2, we can know that in the OMA (Orthgonal Multiple Access) system, the SNR of user u at the [k, l] resource grid is related to the power, DD domain channel gain and noise. If we consider the NOMA system, after clustering the users according to the DD domain channel gain and noise, we assume that the clustering result is represented by a binary variable, and use the binary variable δ kl,u represents whether the resource grid [k, l] is allocated to user u, and the binary variable κ kl,u,i Indicates whether user i causes interference to user u at the resource grid point [k, l]. Then the SINR (signal to interference plus noise ratio) of user u at [k, l] is Then the communication rate of user u at the [k, l] resource grid is R u,kl =log2(1+SINR u,kl ), then the sum rate of the whole system is

[0074] 4. Computational complexity analysis: NIMP is a stable matching algorithm for bilateral matching. Another common stable matching algorithm is the deferred acceptance algorithm GS (Gale-Shapley). In the GS matching process, each round of iteration obtains a temporary match, and the next iteration will continue to update the existing match. The complexity is O(UM 2 N 2), and the embodiment of the present application simplifies the NIMP matching algorithm to obtain the NIMPMA (NIMP Matching Algorithm) algorithm, in which the result of each round of matching will not change in subsequent iterations, and the complexity is O(U 2 MN), when M and N are large, the complexity simplification effect is more obvious. Therefore, the NIMPMA algorithm is more suitable for the scenario of multiple high-mobility users.

[0075] Among them, Figure 7 As shown, the specific steps of the NIMPMA algorithm are as follows:

[0076] 1. Users and grids sort each other to generate a user preference list for highly mobile users and a grid preference list for DD domain resource grids: define a resource grid set and user collections Then, construct the grid preference list PB = {P(B1), P(B2), L, P(B MN )} and user preference list PQ = {P(Q1), P(Q2), L, P(Q U )}, the higher the preference, the higher the position in the preference list, among which, Using the set M(Q u ) indicates that the u The matching resource grid.

[0077] 2. Set the binary variable γ u and γ kl , where γ u Represents user Q u Whether the number of matched resource grids is full max , using γ kl Indicates whether the number of users that have been matched in the grid is full max , where γ u =0 indicates user Q u The number of matching resource grids is not full, γ kl = 0 means that the number of users matching the [k, l] resource grid is not full, γ kl =1, it means that the number of users matching the [k, l] resource grid is full. In order to ensure user fairness, based on the principle of fairness, the number of resource grids matched by each user is η u Should not be greater than the maximum number of grids η max , the number of matching users at each resource grid is η kl Should not be greater than the maximum number of users U max .

[0078] 3. When γ u = 0, such as Figure 7As shown, the following matching loop is performed:

[0079] 1) For each user Q u , select the first resource grid B from the user preference list kl .

[0080] 2) 1:1 matching step: When γ kl = 0, if in B kl Q u The first one is matched successfully, and the matching pair is updated to the set M(Q u ), update γ u With γ kl , otherwise, the matching goes to step 3).

[0081] 3) 2:1 matching step: For user Q u , filter the second resource grid from the user preference list, repeat step 2), if the match fails, go to step 4).

[0082] 4) k:1 matching step: for user Q u , select the kth resource grid B from the user preference list kl , repeat step 2), if the match fails, go to step 5).

[0083] 5) n:1 matching step: for user Q u , if the nth (n is user Q u Total number of resource grids in the preference list) resource grids B kl If step 2) is repeated and still fails, the matching of the user is terminated as unmatched.

[0084] 6) Update the preference list of users and resource grids, delete the resource grids ranked lower than k in the user preference list in step 4), and remove the resource grids that have entered the matching pair set M(Q) before step 5) u ) in the user deletion.

[0085] 7) If the system and rate no longer increase, end the algorithm, otherwise return to step 1)

[0086] When γ u =1 when the loop ends and the allocation of resource grid ends.

[0087] The power allocation process of the iterative IA-WF algorithm based on the water injection algorithm is as follows:

[0088] 1. First, perform power allocation between resource grids. Suppose the total power of all users at grid [k, l] is p kl The corresponding noise power and channel coefficient should be the sum of the proportions of the noise power and channel coefficient allocated to the user at the grid. Among them, ε (0≤ε≤1) is the channel gain attenuation factor. The larger the value, the smaller the channel gain proportion of users with better channel quality, which can ensure fairness. Then we need to solve The maximum value of .

[0089] 2. Use the water injection algorithm to perform Lagrangian derivation of the variables to obtain the optimal solution Then the water filling iterative algorithm for power allocation between resource grids is as follows: Figure 8 As shown, where β0=1 / λln 2.

[0090] 1) First set the initial value of the iteration:

[0091]

[0092] 2) Then according to the optimal solution p kl * , calculate the initial power allocated to each resource grid

[0093] 3) Determine the relationship between the initial power and the target value of each resource grid respectively: In the embodiment of the present application, the target value is set to zero. If the initial power value of a resource grid is less than zero, the resource grid is removed from the iterative process; if the initial power value of a resource grid is greater than or equal to zero, proceed to the next step.

[0094] 4) Determine whether the total power of the resource grid that has not been deleted has reached the maximum power P max , if the total power is less than the maximum power, update the water injection level, let And return to step 2); if the total power is greater than or equal to the maximum power, the algorithm iteration ends.

[0095] 3. Let U max =2, then two users are matched at the grid [k, l], namely user 1 and user 2. The two users need to use NOMA to share communication resources. SIC is used at the receiving end to eliminate interference. First, it is necessary to distinguish between strong and weak users, and then calculate SINR, so it is divided into two cases for allocation. Let the power allocation ratio coefficient between the two users at this grid be α kl , and p kl，1 =α kl p kl , p kl，2 =(1-α kl ) kl , we need to solve α for each case kl , the specific steps are as follows:

[0096] 1) If User 1 has a poor channel quality, so it is allocated more power and is a strong user with p kl，1 > kl，2 , then the SINR expression of user 1 at the grid [k, l] is The SNR expression of user 2 at the grid [k, l] is Then the achievable rates of the two users are About α kl Single increase, About α kl Single minus, the sum rate at this grid is R kl =R 1,kl +R 2,kl , about α kl Single reduction, since the user has a minimum rate constraint R at the grid u,min , so it is necessary to satisfy R 1,kl ≥R 1,min , then the power allocation ratio coefficient at the grid can be solved as

[0097] 2) If Similar to 1), there is p kl，1 <p kl，2 , by taking partial derivatives, we can know that R 1,kl About α kl Single increase, R 2,kl About α kl Single minus, and rate R kl It's about α kl A monotonically increasing function, considering the boundary value R 2,kl ≥R 2,min , the solution is

[0098] 4. Follow step 3 to solve the optimal proportional coefficient of power allocation at each grid.

[0099] 5. Power allocation among multiple high-mobility users based on all optimal proportional coefficients.

[0100] In some embodiments, Fig. 9 As shown, the specific process of step 221 to step 223 under the non-ideal pulse waveform condition of fractional Doppler shift is as follows, wherein a rectangular pulse corresponding to a rectangular window function is taken as an example for explanation:

[0101] 1. Assume that the duration of the cyclic prefix CP is equal to the maximum channel delay, that is, After adding CP, the time domain transmitted signal is in the interval [-τ max ,NT) is expressed as The value is zero at other times.

[0102] 2. The signal input and output relationship and interference term of the entire system in the TF domain are shown as follows:

[0103]

[0104]

[0105] For a rectangular pulse, When |τ|<τ max ,|υ|<υ max is non-zero if and only if n′=n and n′=n-1, because the transmitted waveform g rx (t) and the received waveform is a pulse waveform with a duration of T, and τ max =T, then the input-output relationship of the TF domain becomes The second term from left to right in the formula refers to the signal X with different frequencies m′ in the same n time slot. v [n,m′] for signal X v The third term refers to the signal X at the previous time slot n-1. v [n-1,m′] for the current signal X v Therefore, the second term is ICI and the third term is ISI.

[0106] 3. Derivation of the DD domain receiving signal to obtain the input and output relationship of the DD domain system where h u (τ,υ) is the circular convolution of the channel response and the SFFT transform of the rectangular window function in the TF domain ∫∫h u (τ′,υ′)w(υ-υ′,τ-τ′)e -j2πυ′τ′ dτ′dυ′, where After the SFFT transformation of ICI and ISI in the TF domain in step 2, it can be seen that only if the condition is met and When , the ICI interference term is non-zero, and in other cases, ICI interference does not exist. and When , the value of the ISI interference signal is non-zero, and in other cases, ISI does not exist.

[0107] 4. Considering the additive white Gaussian noise AWGN, the DD domain signal is: The channel gain can be further simplified as where a u,j [k′,l′] is:

[0108]

[0109] 5. If we use matrix A u,j ∈￡ MN×MN To represent the gain coefficient of the channel matrix, the element in the (kM+l+1)th row and (k′M+l′+1)th column is a u,j [k′,l′]. Then use the matrix H u ∈￡ MN×MN represents the total channel matrix, where the element in the (kM+l+1)th row and (k′M+l′+1)th column is h u [k′,l′]. After the base station and the uth user pass through the jth path channel, the relationship between these two matrices can be written as Then the vector form of the received signal is y u =H u x+w u .

[0110] 6. Therefore, the received signal of the OMA system can be written as Consider U max For a NOMA system consisting of users, the expression of the received signal is The SINR of the u-th user at the grid [k, l] is Then the sum rate of the system is

[0111] 7. Due to the large number of interference items, it is impossible to obtain the user and grid preference sequences that are independent of each other. Therefore, an approximate preference sequence is initialized for the user, and the GSMA (GS Matching Algorithm) based on the GS algorithm is used for matching. The system and rate are calculated once for each matching to ensure that the system and rate are maximized. Then the genetic algorithm is used to design the power allocation method.

[0112] Among them, the GSMA method process is as follows Fig.10 As shown, the binary variable γ u Indicates whether the number of resource grids that the user has matched is full max .

[0113] 1) Initialize the user preference list:

[0114]

[0115] 2) Using the set AP(B kl ) indicates application resource grid B kl All users of kl ) represents the users that the resource grid has received, and M(Q u ) indicates temporary connection with user Q u The matching resource grid.

[0116] 3) Judge γ u Is it zero? If not, whether the entry and rate increase; if it is zero, user Q u Apply for the first resource grid from the step user preference list, and set Q u Add to AP(B kl ), where the construction of the preference list is the same as that in the NIMPMA algorithm and will not be repeated here.

[0117] 4) Determine AP(B kl ) and AC(B kl ) reaches the maximum number of users U max , if AP(B kl )+AC(B kl )≤U max , AP(B kl ) is added to AC(B kl );If AP(B kl )+AC(B kl )>U max , in AP(B kl )∪AC(B kl ), according to B kl Select the first U in the grid preference list. max Users, updated to AC(B kl ) and the user's corresponding matching pair set M(Q u ), the rejected user is removed from his M(Q u ) Delete B kl .

[0118] 5) Update γ u .

[0119] 6) Delete P(Q u )

[0120] 7) Determine P(Q u ) is empty, if P(Q u ) is empty, end user Q u If it is not empty, go to the next step.

[0121] 8) Determine whether the sum rate increases. If the sum rate continues to increase, return to step 3); if the sum rate no longer increases, the matching ends.

[0122] Complete the allocation of resource grid.

[0123] Finally, the power is allocated to multiple highly mobile users through genetic algorithm.

[0124] In some embodiments, Fig.11 This is a simulation comparison of the NIMPMA algorithm, the GS algorithm, and the optimal matching algorithm KM (Kuhn-Munkras) for bipartite graphs. Fig.12 It is a simulation comparison between the power allocation algorithm based on IA-WF and the fixed power allocation algorithm FPA (Fixed Power Allocation) and the fractional power allocation algorithm FTPA (Fractional Transmit Power Allocation). Fig.13 The simulation comparison of GSNA algorithm, NIMP algorithm and KM algorithm is shown in Figure 2. The comparison shows that under the premise of the same total power, NIMPMA has a faster convergence speed and lower complexity, IA-WF algorithm can achieve a higher sum rate, GAMA and genetic algorithm also achieve a higher system sum rate than other algorithms, and achieve a better allocation effect. Among them, the total power refers to the sum of the power that the base station can allocate to all high-mobility users. Optionally, as Fig.14 As shown, the power allocation process can adopt a power allocation GAPA algorithm based on a genetic algorithm to obtain a higher total user rate.

[0125] In summary, the embodiment of the present application is based on a communication network composed of multiple high-mobility users and base stations. In the TF domain, for an ideal pulse waveform that meets the dual-orthogonal condition, the NIMP algorithm is used to allocate resource grids to multiple high-mobility users. Based on the allocated resource grids, the iterative IA-WF algorithm of the water injection algorithm is used to achieve power allocation between different high-mobility users, and the throughput of the entire system under the ideal pulse waveform condition is maximized. For non-ideal pulse waveforms that do not meet the dual-orthogonal condition, the GSMA algorithm is used to allocate resource grids to multiple high-mobility users. Based on the allocated resource grids, the power allocation between different high-mobility users is achieved through a genetic algorithm, and the throughput of the entire system under the non-ideal pulse waveform condition is maximized. Taking full account of the differences in channel conditions, the minimum unit of DD domain resources is allocated to each high-mobility user, and corresponding power allocation schemes are established for both ideal and non-ideal pulses, thereby improving system energy efficiency.

[0126] Compared with the related art, the method of the embodiment of the present application first considers more practical rectangular window and fractional Doppler, and has more practical application value.

[0127] The method of the embodiment of the present application is universally applicable to a communication network composed of multiple high-mobility users with different channel configurations, and has a wider range of applications.

[0128] The method of the embodiment of the present application considers stable and low-complexity matching and low-complexity power allocation. The method of the embodiment of the present application is more suitable for implementation in actual products.

[0129] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0130] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0131] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a resource allocation device for an orthogonal time-frequency-space system.

[0132] refer to Fig.15 , a resource allocation device based on an orthogonal time-frequency-space system, comprising:

[0133] The signal conversion module 10 is configured to: perform a sparse inverse fast Fourier transform on the transmission signal converted to the DD domain to transform the transmission signal to the TF domain;

[0134] The model building module 20 is configured to: in response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain meet the biorthogonal condition, establish a first channel model after the transmission signal is converted to the time domain and a cyclic prefix CP is added;

[0135] In response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain do not satisfy the biorthogonality condition, after the transmission signal is converted into the time domain and a cyclic prefix CP is added, a second channel model is established;

[0136] The grid allocation module 30 is configured to: allocate resource grids to multiple high-mobility users through a centralized matching NIMP algorithm based on the first channel model;

[0137] Based on the second channel model, resource grids are allocated to multiple high-mobility users through the deferred acceptance matching GSMA algorithm;

[0138] The power allocation module 40 is configured to: in response to determining that the resource grid allocation is completed, allocate power to multiple high-mobility users through an iterative IA-WF algorithm based on a water injection algorithm;

[0139] In response to determining that the resource grid allocation is complete, power is allocated to a plurality of high-mobility users through a genetic algorithm.

[0140] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0141] The device of the above embodiment is used to implement the corresponding resource allocation method based on the orthogonal time-frequency-space system in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0142] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the resource allocation method based on the orthogonal time-frequency-space system described in any of the above embodiments is implemented.

[0143] Fig.16 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0144] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0145] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0146] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0147] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0148] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0149] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0150] The electronic device of the above embodiment is used to implement the corresponding resource allocation method based on orthogonal time-frequency-space system in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0151] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the resource allocation method based on the orthogonal time-frequency-space system as described in any of the above embodiments.

[0152] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0153] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the resource allocation method based on the orthogonal time-frequency-space system as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0154] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0155] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0156] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0157] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A resource allocation method based on an orthogonal time-frequency-space system, characterized in that: In the downlink of the orthogonal time-frequency-space system, a transmission signal sent by a base station end is converted into a reception signal received by a receiving end through a delay Doppler DD domain, the receiving end includes a plurality of high-mobility users, the DD domain includes N×M resource grids, and the method includes: Performing a sparse inverse fast Fourier transform on the transmit signal converted into the DD domain to convert the transmit signal into the TF domain; In response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain satisfy a biorthogonal condition, after the transmission signal is converted to the time domain and a cyclic prefix CP is added, a first channel model is established; Based on the first channel model, allocating the resource grid to the plurality of the high mobility users by a simplified centralized matching NIMP algorithm; In response to determining that the resource grid is allocated, allocating power to the plurality of high-mobility users by using an iterative IA-WF algorithm based on a water filling algorithm; In response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain do not satisfy the biorthogonality condition, after the transmission signal is converted to the time domain and the cyclic prefix CP is added, a second channel model is established; Based on the second channel model, allocating the resource grid to the plurality of the high mobility users by using a deferred acceptance matching GSMA algorithm; In response to determining that the resource grid is completely allocated, power is allocated to the plurality of high-mobility users by using a genetic algorithm.

2. The method according to claim 1, characterized in that Before performing a sparse inverse fast Fourier transform on the transmit signal converted to the DD domain to convert the transmit signal to the TF domain, the method further includes: Based on the channel state information CSI, the plurality of highly mobile users are clustered, and all the highly mobile users in the same cluster share one resource grid, wherein each cluster includes one or two highly mobile users.

3. The method according to claim 2, characterized in that Based on the fairness principle among the high-mobility users, the number of the resource grids allocated to each cluster is less than or equal to a preset maximum number of grids.

4. The method according to claim 3, characterized in that Based on the fairness principle, the number of the high-mobility users matched to each resource grid is less than or equal to a preset maximum number of users.

5. The method according to claim 2, characterized in that: Also includes: In response to determining that the power allocation is complete, demodulating the strong user to obtain demodulation information, wherein the high-mobility user allocated with higher power in the same cluster is the strong user; The demodulated information is broadcast within the cluster.

6. The method according to claim 1, characterized in that Based on the first channel model, allocating the resource grid to the plurality of high-mobility users by using a simplified centralized matching NIMP algorithm specifically includes: Based on the first channel model, determining a signal-to-noise ratio SNR of each of the high-mobility users in the DD domain after being equalized by a decision feedback equalizer DFE; Based on the SNR, determining a signal to interference plus noise ratio SINR based on a non-orthogonal multiple access NOMA condition; respectively constructing a user preference list of the highly mobile user and a grid preference list of the DD domain resource grid; Based on the SINR, the resource grid is allocated to a plurality of the high mobility users by using the simplified NIMP algorithm.

7. The method according to claim 1, characterized in that Based on the second channel model, allocating the resource grid to the plurality of high mobility users by using a deferred acceptance matching GSMA algorithm specifically includes: Determining a signal input-output relationship and interference terms of the TF domain of the transmitted signal through the second channel model, and determining a signal input-output relationship and interference terms of the DD domain of the transmitted signal through the second channel model; Based on the second channel model, simplifying the DD domain channel matrix; Calculate SINR under NOMA conditions; Based on the SINR, the resource grid is allocated to the plurality of the high mobility users through the GSMA algorithm.

8. A resource allocation device for an orthogonal time-frequency-space system, characterized in that: In a downlink of the orthogonal time-frequency-space system, a transmission signal sent by a base station end is converted into a reception signal received by a receiving end through a delay-Doppler (DD) domain, the receiving end includes a plurality of highly mobile users, and the DD domain includes N×M resource grids; The resource allocation device of the orthogonal time-frequency-space system comprises: A signal conversion module is configured to: perform a sparse inverse fast Fourier transform on the transmission signal converted to the DD domain to convert the transmission signal to the TF domain; The first model building module is configured to: in response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain meet the biorthogonal condition, establish a first channel model after the transmission signal is converted into the time domain and a cyclic prefix CP is added; A first grid allocation module is configured to: allocate the resource grid to the plurality of the high mobility users through a centralized matching NIMP algorithm based on the first channel model; A first power allocation module is configured to: in response to determining that the resource grid is allocated, allocate power to the plurality of high-mobility users by using an iterative IA-WF algorithm based on a water injection algorithm; The second model building module is configured to: in response to determining that the transmission waveform and the reception waveform of the pulse wave in the TF domain do not satisfy the biorthogonal condition, establish a second channel model after the transmission signal is converted to the time domain and the cyclic prefix CP is added; A second grid allocation module is configured to: allocate the resource grid to the plurality of the high mobility users through a deferred acceptance matching GSMA algorithm based on the second channel model; The second power allocation module is configured to: in response to determining that the resource grid is allocated, allocate power to the plurality of high-mobility users by using a genetic algorithm.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program. 10 . A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method according to claim 1 .

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