Pre-coding and public rate joint optimization method based on ABLO-OFDM and RSMA

Abstract

The invention discloses a pre-coding and public rate joint optimization method based on ABLO-OFDM and RSMA, which belongs to the technical field of k visible light communication, and comprises the following steps: obtaining a pre-constructed pre-coding matrix and user public rate allocation joint optimization problem; wherein the pre-constructed precoding matrix and user public rate allocation joint optimization problem is a non-convex problem; converting the non-convex problem into a convex problem; and performing iterative solution on the convex problem based on given convergence precision to obtain an optimal solution of the precoding matrix and the user public rate allocation, thereby realizing maximization of the minimum user total reachable rate and improving the user rate allocation fairness in the multi-user visible light communication system.

Description

Technical Field

[0001] This invention relates to the field of visible light communication technology, and in particular to a joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA. Background Technology

[0002] With the rapid growth of data traffic, traditional radio frequency communication systems face problems such as scarce spectrum resources and high energy consumption. Visible light communication (VLC), as an emerging wireless communication method, has advantages such as abundant spectrum, energy saving, and resistance to electromagnetic interference, and is gradually becoming an important supplementary technology for high-speed indoor wireless communication. In multi-user visible light communication systems, how to maximize the minimum total reachable rate for users while satisfying non-negative signal constraints and average optical power limitations, so as to improve the fairness of user rate allocation, is an important research direction.

[0003] In multi-user access strategies, Rate-Splitting Multiple Access (RSMA) has attracted widespread attention as a communication technology that combines interference management and user decoupling capabilities. RSMA divides each user's information into a common part and a private part, and combines linear precoding to achieve flexible interference coordination. It can dynamically allocate resources among different users, improve the minimum user rate, and is especially suitable for multi-user environments with uneven load or significant differences in channel conditions.

[0004] On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) has been widely adopted in visible light communication systems due to its robustness against multipath effects and high spectral efficiency. To address the non-negative signal characteristics required by visible light communication systems, various optical OFDM variants have been developed. Among them, Asymmetrically Biased Layered Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) achieves efficient transmission of non-negative signals by constructing a zero-mean multi-layer frequency domain structure and adding a periodic bias in the time domain. Compared to traditional structures such as ACO-OFDM, ABLO-OFDM can complete all layer processing with only one FFT / IFFT operation while maintaining spectral efficiency. It has advantages such as simple structure, low computational complexity, and low implementation overhead, making it particularly suitable for resource- and power-sensitive multi-user optical communication scenarios.

[0005] Considering average optical power constraints and channel interference, the key to maximizing the minimum total reachable rate for users in a multi-user visible light communication system lies in how to collaboratively design the precoding matrix and user rate allocation strategy. Summary of the Invention

[0006] The purpose of this invention is to provide a joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA. This method achieves non-negative optical signal transmission by introducing hierarchical optical orthogonal frequency division multiplexing (ABLO-OFDM) with adaptive bias in a multi-user visible light communication system. By introducing rate segmentation multiple access (RSMA), which divides each user's information into a common and a private part, and combining this with linear precoding to achieve flexible interference coordination, resources can be dynamically allocated among different users, improving the minimum user rate. Within the ABLO-OFDM framework, an optimization problem is constructed and solved between the precoding matrix and the user common rate, thereby maximizing the minimum total achievable rate for users and improving the fairness of user rate allocation in multi-user visible light communication systems. This invention is achieved through the following technical solutions.

[0007] This invention provides a joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA, comprising the following:

[0008] Obtain a pre-constructed precoding matrix and a joint optimization problem for user common rate allocation; wherein the pre-constructed precoding matrix and the joint optimization problem for user common rate allocation are non-convex problems;

[0009] Transform the non-convex problem into a convex problem;

[0010] Based on the given convergence accuracy, the convex problem is solved iteratively to obtain the optimal solution for the precoding matrix and the allocation of the user common rate, thereby maximizing the minimum total reachable rate for users.

[0011] In practical applications, existing radio frequency communication systems face problems such as limited spectrum resources and high energy consumption. This invention selects a visible light communication system, which offers advantages such as abundant spectrum and energy efficiency, for user message transmission. However, in multi-user visible light systems, it is necessary to maximize the minimum total reachable rate for each user while satisfying non-negative signal constraints, in order to improve the fairness of user rate allocation. Therefore, this invention introduces Rate Division Multiple Access (RSMA) and Layered Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) with adaptive bias at the transmitter end of the multi-user visible light system. RSMA can divide each user's information into a common part and a private part, and combined with linear precoding, achieves flexible interference coordination, dynamically allocating resources among different users and improving the minimum user rate. Layered Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) with adaptive bias achieves efficient transmission of non-negative signals by constructing a zero-mean multi-layer frequency domain structure and adding a periodic bias in the time domain.

[0012] Optionally, the joint optimization problem of the preconstructed precoding matrix and the user common rate allocation is:

[0013] ;

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] ;

[0019] ;

[0020] ;

[0021] ;

[0022] In the formula, The user serial number, with a value range of 1- , Total number of users For user collection, ; It is an index symbol used for summation; The total number of subcarriers for asymmetric bias stacked orthogonal frequency division multiplexing (ABLO-OFDM) is... For subcarrier layers, and These are the on-state current and the maximum permissible AC current, respectively. For the first transmitter The photocurrent of each LED; Only related to the number of subcarrier layers The relevant bias factors, It is the inverse cumulative distribution function of the standard normal distribution. It is a constant;

[0023] For the precoding matrix, For each user The merged public information stream precoding vector, For the first Precoded vectors of a user's private information stream For the first transmitter The pre-encoded vector of each LED, Indicates the first Precoded vectors of a user's private information stream The LED serial number to be emitted, with a value ranging from 1 to... , The total number of LEDs emitted; It is the line-of-sight (LOS) channel matrix for optical links, where For the first Channel vectors for each user;

[0024] For the first Private reachability rate for each user For the first Public reachability for each user For the first Public rate allocated to each user, For the first Total reachability for each user;

[0025] The number of effective subcarriers, Let V be the variance of the additive white Gaussian noise in the channel.

[0026] Optionally, transforming the non-convex problem into a convex problem includes introducing slack variables.

[0027] Optionally, the slack variable expression is as follows:

[0028] ;

[0029] ;

[0030] In the formula, Indicates the first Private reachability rate for each user Slack variables, Indicates the first Public reachability for individual users Slack variables, Indicates the first The ratio of signal to interference plus noise in a user's private stream is a slack variable. Indicates the first The ratio of signal to interference plus noise in a user's public stream is a slack variable.

[0031] Optionally, the expression for the convex problem is as follows:

[0032] ;

[0033] ;

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] ;

[0039] ;

[0040] ;

[0041] In the formula, To extract the real part of the complex number within the parentheses, Represents the achievement of the minimum number of th... Total reachability for individual users The objective function value is optimized.

[0042] Optionally, the iterative solution of the convex problem based on a given convergence accuracy includes the following steps:

[0043] Step 1, Set the convergence accuracy Initialize the iteration count i and the objective function value. And initialize the iteration point to obtain the initial iteration point;

[0044] Step 2: Solve the convex problem using the initial iteration point to obtain the optimized solution of the convex problem after iteration;

[0045] Step 3: Update the iteration count, objective function value, and iteration point;

[0046] Step 4: When the absolute value of the difference between the objective function values ​​of two adjacent iterations is less than the set convergence precision, the minimum value of the first iteration is achieved. Total reachability for individual users The iteration ends when the maximum value is reached.

[0047] Optionally, in step 1, the iteration points include i is the iteration number, which ranges from 0 to m, and m is the total number of iterations;

[0048] The initialization iteration number i and the objective function value This includes: initial iteration count Initialize the target function value ;

[0049] The initial iteration point is obtained by initializing the iteration point, which includes initializing the iteration point. = ;

[0050] The initial iteration point is .

[0051] Optionally, in step 2, the initial iteration point is used to solve the convex problem to obtain an optimized solution to the convex problem after iteration, including:

[0052] Using the initial iteration point Solve the convex problem to obtain the th iteration. Optimization solution for the shared rate allocated to each user New objective function value , No. The pre-encoded vector of each LED , No. The optimal solution generated after iteration using user-private rate slack variables. , No. The optimal solution generated after iteration from the slack variables of the shared rate of each user , No. The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's private data stream. and the The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's public data stream. .

[0053] Optionally, in step 3, the number of update iterations and the optimized solution obtained after iterating over the convex problem include:

[0054] make ,renew , , , ;

[0055] in, This indicates that another iteration will be performed after this iteration, using the optimized solution from the previous iteration as the input for the next iteration. Specifically, this means using the new objective function value generated after the iteration. Assign to , Assign to , Assign to , Assign to .

[0056] Optionally, in step 4, the step of obtaining the maximum minimum user rate and ending the iteration when the absolute value of the difference between the objective functions of two adjacent iterations is less than the set convergence accuracy includes:

[0057] when The iteration ends;

[0058] Among them, the algorithm based on continuous convex approximation iteratively... times, when and The difference is less than the set precision. Then the first The next iteration is based on the previous one. The optimal solution is obtained in -1 iterations. and the The optimal solution for the shared rate allocated to each user ;

[0059] The optimal solution is obtained through iterative optimization. Find the optimal precoding matrix Thus, based on the optimal precoding matrix Calculate the first number using the following formula. Private reachability rate for each user ,

[0060] ,

[0061] According to the first The optimal solution for the shared rate allocated to each user Calculate the first number using the following formula. Total reachability for individual users to achieve ,

[0062] .

[0063] Beneficial effects (1) By solving the joint optimization problem of the constructed precoding matrix and the user common rate allocation, the present invention can obtain the optimal precoding matrix and user common rate. Based on the optimal solution of the precoding matrix and user common rate, the minimum total reachable rate of users can be maximized, thereby solving the problem of uneven rate allocation among multiple users in the prior art.

[0064] (2) This invention introduces Rate Division Multiple Access (RSMA) and Hierarchical Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) with adaptive bias into a selected multi-user visible light communication system and combines the two. Under the premise of satisfying signal nonnegativity and optical power constraints, it effectively coordinates the resource allocation of common rates among users and designs precoding that takes into account channel environment and user differences. Thus, it maximizes the minimum total reachable rate for users and improves the fairness of user rate allocation in multi-user visible light communication systems.

[0065] (3) Compared with traditional OFDM modulation methods based on optical fiber communication systems, the layered optical orthogonal frequency division multiplexing (ABLO-OFDM) structure with adaptive bias adopted in this invention does not require multiple FFT / IFFT calculations, which greatly simplifies hardware complexity and reduces implementation costs. It is particularly suitable for visible light communication systems with limited LED resources or high real-time requirements. Rate Division Multiple Access (RSMA) can divide the information of each user into a common part and a private part, and combined with linear precoding, it can achieve flexible interference coordination, dynamically allocate resources among different users, and improve the minimum user rate. Attached Figure Description

[0066] Figure 1 The diagram shown is a schematic flowchart of the precoding matrix and user common rate joint optimization method of the present invention.

[0067] Figure 2 The diagram shown is a schematic diagram of the transmitter principle of a multi-user visible light communication system according to an embodiment of the present invention.

[0068] Figure 3 The diagram shown is a schematic diagram of the receiver principle of a multi-user visible light communication system according to an embodiment of the present invention.

[0069] Figure 4 The diagram shows the relationship between the minimum total reachability rate of users and the number of iterations in the simulation experiment of this invention. Detailed Implementation

[0070] The following description, in conjunction with the accompanying drawings and specific embodiments, provides further details. In this description, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature.

[0071] Example 1 This invention provides a joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA, comprising the following:

[0072] Obtain a pre-constructed precoding matrix and a joint optimization problem for user common rate allocation; wherein the pre-constructed precoding matrix and the joint optimization problem for user common rate allocation are non-convex problems;

[0073] Transform the non-convex problem into a convex problem;

[0074] Based on the given convergence accuracy, the convex problem is solved iteratively to obtain the optimal solution for the precoding matrix and the allocation of the user common rate, thereby maximizing the minimum total reachable rate for users.

[0075] In practical applications, existing radio frequency communication systems face problems such as limited spectrum resources and high energy consumption. This invention selects a visible light communication system, which offers advantages such as abundant spectrum and energy efficiency, for user message transmission. However, in multi-user visible light systems, it is necessary to maximize the minimum total reachable rate for each user while satisfying non-negative signal constraints, in order to improve the fairness of user rate allocation. Therefore, this invention introduces Rate Division Multiple Access (RSMA) and Layered Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) with adaptive bias at the transmitter end of the multi-user visible light system. RSMA can divide each user's information into a common part and a private part, and combined with linear precoding, achieves flexible interference coordination, dynamically allocating resources among different users and improving the minimum user rate. Layered Optical Orthogonal Frequency Division Multiplexing (ABLO-OFDM) with adaptive bias achieves efficient transmission of non-negative signals by constructing a zero-mean multi-layer frequency domain structure and adding a periodic bias in the time domain.

[0076] Example 2 Based on Example 1, this example introduces a specific implementation process of a joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA, such as... Figure 1 As shown, it specifically includes the following:

[0077] I. Optimization Problem Construction

[0078] In one specific embodiment of the present invention, the joint optimization problem of the preconstructed precoding matrix and the user common rate allocation is as follows:

[0079] ;

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] In the formula, The user serial number, with a value range of 1- , Total number of users For user collection, ; It is an index symbol used for summation; The total number of subcarriers for hierarchical optical orthogonal frequency division multiplexing (ABLO-OFDM) with adaptive bias. For subcarrier layers, and These are the on-state current and the maximum permissible AC current, respectively. For the first transmitter The photocurrent of each LED; Only related to the number of subcarrier layers The relevant bias factors, It is the inverse cumulative distribution function of the standard normal distribution. It is a constant;

[0089] For the precoding matrix, Each user For the precoding vector of the merged public information stream, For the first Precoded vectors of a user's private information stream For the first transmitter The pre-encoded vector of each LED, Indicates the first Precoded vectors of a user's private information stream The LED serial number to be emitted, with a value ranging from 1 to... , The total number of LEDs emitted; It is the line-of-sight (LOS) channel matrix for optical links, where For the first Channel vectors for each user;

[0090] For the first Private reachability rate for each user For the first Public reachability for each user For the first Public rate allocated to each user, For the first Total reachability for each user;

[0091] The number of effective subcarriers, Let V be the variance of the additive white Gaussian noise in the channel.

[0092] II. Solving the Optimization Problem

[0093] 2.1 Transforming a non-convex problem into a convex problem

[0094] In one specific embodiment of the present invention, transforming the non-convex problem into a convex problem includes introducing slack variables.

[0095] The expression for the slack variable is as follows:

[0096] ;

[0097] ;

[0098] In the formula, Indicates the first Private reachability rate for each user Slack variables, Indicates the first Public reachability for individual users Slack variables, Indicates the first The ratio of signal to interference plus noise in a user's private stream is a slack variable. Indicates the first The ratio of signal to interference plus noise in a user's public stream is a slack variable.

[0099] In one specific embodiment of the present invention, the expression for the convex problem is as follows:

[0100] ;

[0101] ;

[0102] ;

[0103] ;

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] In the formula, To extract the real part of the complex number within the parentheses, Represents the achievement of the minimum number of th... Total reachability for individual users The objective function value is optimized.

[0110] 2.2 Solving convex problems

[0111] In one specific embodiment of the present invention, the iterative solution of the convex problem based on a given convergence accuracy includes the following steps:

[0112] Step 1, Set the convergence accuracy Initialize the iteration count i and the objective function value. And initialize the iteration point to obtain the initial iteration point;

[0113] Step 2: Solve the convex problem using the initial iteration point to obtain the optimized solution of the convex problem after iteration;

[0114] Step 3: Update the iteration count, objective function value, and iteration point;

[0115] Step 4: When the absolute value of the difference between the objective function values ​​of two adjacent iterations is less than the set convergence precision, the minimum value of the first iteration is achieved. Total reachability for individual users The iteration ends when the maximum value is reached.

[0116] In step 1, the iteration points include i is the iteration number, which ranges from 0 to n, and n is the total number of iterations;

[0117] The initialization iteration number i and the objective function value This includes: initial iteration count Initialize the target function value ;

[0118] The initial iteration point is obtained by initializing the iteration point, which includes initializing the iteration point. = ;

[0119] The initial iteration point is .

[0120] In step 2, the convex problem is solved using the initial iteration point to obtain the optimized solution of the convex problem after iteration, including:

[0121] Using the initial iteration point Solve the convex problem to obtain the th iteration. Optimization solution for the shared rate allocated to each user New objective function value , No. The pre-encoded vector of each LED , No. The optimal solution generated after iteration using user-private rate slack variables. , No. The optimal solution generated after iteration from the slack variables of the shared rate of each user , No. The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's private data stream. and the The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's public data stream. .

[0122] In step 3, the number of update iterations and the optimized solution obtained after iterating over the convex problem include:

[0123] make ,renew , , , ;

[0124] in, This indicates that another iteration will be performed after this iteration, using the optimized solution from the previous iteration as the input for the next iteration. Specifically, this means using the new objective function value generated after the iteration. Assign to , Assign to , Assign to , Assign to .

[0125] In step 4, the step of obtaining the maximum minimum user rate and ending the iteration when the absolute value of the difference between two adjacent iterations of the objective function is less than the set convergence accuracy includes:

[0126] when The iteration ends;

[0127] Among them, the algorithm based on continuous convex approximation iteratively... times, when and The difference is less than the set precision. Then the first The next iteration is based on the previous one. The optimal solution is obtained in -1 iterations. and the The optimal solution for the shared rate allocated to each user ;

[0128] The optimal solution is obtained through iterative optimization. Find the optimal precoding matrix Thus, based on the optimal precoding matrix Calculate the first number using the following formula. Private reachability rate for each user ,

[0129] ,

[0130] According to the first The optimal solution for the shared rate allocated to each user Calculate the first number using the following formula. Total reachability for individual users to achieve ,

[0131] .

[0132] III. Transmitter Principle

[0133] In one specific embodiment of the present invention, such as Figure 2 The diagram shown is a schematic diagram of the transmitter principle of a multi-user visible light communication system.

[0134] Step 3.1, assuming the message to be sent is... The information of each user is Based on the principle of Rate Division Multiple Access (RSMA), the information of each user is... Divided into and ,in For its public portion, For its private portion, merge all users' data. for , This represents the total public information after merging the public information of all users.

[0135] Step 3.2, assuming the total number of subcarriers in the hierarchical optical orthogonal frequency division multiplexing (ABLO-OFDM) with adaptive bias is... The number of subcarrier layers is , will user messages After the bitstream is framed, grouped, and converted from serial to parallel, the bits of each frame are assigned to the index . The former Subcarriers, The symbol matrix is ​​obtained by using normalized coding modulation. , , The vector represents the total common information in this frame of Orthogonal Frequency Division Multiplexing (OFDM) symbols, after normalization coding and modulation, allocated to the first element. Symbols on a striped subcarrier, Vector representation of users in this frame of Orthogonal Frequency Division Multiplexing (OFDM) symbols The private information is allocated in the front after normalized coding and modulation. Symbols on a striped subcarrier.

[0136] Step 3.3, assuming the total number of LEDs at the transmitter of the multi-user visible light system is... The visible light communication channel is a flat optical link line-of-sight (LOS) channel. The channel matrix is ​​obtained according to the optical link line-of-sight (LOS) channel calculation formula. , ,in For the first The channel vector of each user; and then the channel matrix. Singular value decomposition is performed to obtain the precoding matrix. , ,in For public information stream precoding vectors, For the first Precoded vectors of a user's private information stream For the first of the transmitting end The pre-encoded vector of each LED, ; For the symbol matrix obtained in step 3.2 Precoding is performed to obtain the frequency domain signal matrix. , Then, after constructing according to the Hermitian symmetry rule... The symbols on each subcarrier are used to obtain the complete frequency domain signal matrix. , .

[0137] Step 3.4, for the complete frequency domain signal matrix Each row (each LED link) is processed by Inverse Fast Fourier Transform (IFFT) to obtain a signal matrix in the time domain that satisfies the real number property. , .in, For the first Time-domain signals on an LED link.

[0138] Step 3.5, for the corresponding time-domain signal on each LED link The following relationships are used to determine the values ​​on each LED link. Full A periodic adaptive bias signal: The matrix of the total adaptive bias signal on the LED link is obtained. .

[0139] Step 3.6: Superimpose the total adaptive bias signal on the LED link from step 3.5. This yields a real signal matrix that satisfies nonnegativity. , Then, after digital-to-analog conversion, the photodiode converts the signal into an optical signal for transmission.

[0140] IV. Receiver Principle

[0141] In one specific embodiment of the present invention, such as Figure 3 The diagram shown is a schematic diagram of the receiver principle of a multi-user visible light communication system.

[0142] For the receiving end user The receiving end first uses common message equalization technology to obtain the total common flow vector. Decoding it yields the total public message. Then, after splitting, the public information for each user is obtained. Next, continuous interference cancellation and private message equalization techniques are applied to the remaining private information streams to obtain the private information stream for each user. Then decode to get each user Private information Finally, and Merge, and obtain users Information .

[0143] According to step 3.5, in ABLO-OFDM, half of the subcarriers are used to satisfy Hermitian symmetry, and some of the other half are used to handle noise in the adaptive bias signal. Therefore, the effective number of subcarriers can be deduced as follows: As shown in step 3.3, this invention considers a flat LOS channel. Based on the rate formula of multi-carrier rate segmented multiple access (RSMA) and the properties of ABLO-OFDM described above, the following rate formula can be obtained:

[0144] ,

[0145] ,

[0146] In the formula, User Private reachability rate, It is the first The public reachable rate for each user; assuming the first... The shared rate allocated to each user is Then the first Total reachability for individual users .

[0147] V. Simulation Experiment

[0148] In one specific embodiment of the present invention, such as Figure 4 The diagram shown illustrates the relationship between the minimum total reachability rate for users and the number of iterations in the simulation experiment of this invention.

[0149] Figure 4 In the middle, after 24 iterations, the minimum total reachable rate for users was determined. The minimum total reachable rate for users was achieved by increasing the speed from 0.1806 bit / symbol to 1.55 bit / symbol. Maximize.

[0150] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A joint optimization method for precoding and common rate based on ABLO-OFDM and RSMA, characterized in that, include: Obtain a pre-constructed precoding matrix and a joint optimization problem for user common rate allocation; wherein the pre-constructed precoding matrix and the joint optimization problem for user common rate allocation are non-convex problems; Transform the non-convex problem into a convex problem; Based on the given convergence accuracy, the convex problem is solved iteratively to obtain the optimal solution for the precoding matrix and the allocation of the user common rate, thereby maximizing the minimum total reachable rate for users.

2. The precoding and common rate joint optimization method according to claim 1, characterized in that, The joint optimization problem of the preconstructed precoding matrix and the allocation of the user common rate is as follows: ； ； ； ； ； ； ； ； ； In the formula, The user serial number, with a value range of 1- , Total number of users For user collection, ; It is an index symbol used for summation; The total number of subcarriers for asymmetric bias stacked orthogonal frequency division multiplexing (ABLO-OFDM) is... For subcarrier layers, and These are the on-state current and the maximum permissible AC current, respectively. For the first transmitter The photocurrent of each LED; Only related to the number of subcarrier layers The relevant bias factors, It is the inverse cumulative distribution function of the standard normal distribution. It is a constant; For the precoding matrix, For each user The merged public information stream precoding vector, For the first Precoded vectors of a user's private information stream For the first transmitter The pre-encoded vector of each LED, Indicates the first Precoded vectors of a user's private information stream The LED serial number to be emitted, with a value ranging from 1 to... , The total number of LEDs emitted; It is the line-of-sight (LOS) channel matrix for optical links, where For the first Channel vectors for each user; For the first Private reachability rate for each user For the first Public reachability for each user For the first Public rate allocated to each user, For the first Total reachability for each user; The number of effective subcarriers, Let V be the variance of the additive white Gaussian noise in the channel.

3. The precoding and common rate joint optimization method according to claim 2, characterized in that, Transforming the non-convex problem into a convex problem includes introducing slack variables.

4. The precoding and common rate joint optimization method according to claim 3, characterized in that, The expression for the slack variable is as follows: ； ； In the formula, Indicates the first Private reachability rate for each user Slack variables, Indicates the first Public reachability for individual users Slack variables, Indicates the first The ratio of signal to interference plus noise in a user's private stream is a slack variable. Indicates the first The ratio of signal to interference plus noise in a user's public stream is a slack variable.

5. The precoding and common rate joint optimization method according to claim 4, characterized in that, The expression for the convex problem is as follows: ； ； ； ； ； ； ； ； ； In the formula, To extract the real part of the complex number within the parentheses, Represents the achievement of the minimum number of th... Total reachability for each user The objective function value is optimized.

6. The precoding and common rate joint optimization method according to claim 5, characterized in that, The iterative solution of the convex problem based on a given convergence accuracy includes the following steps: Set convergence precision Initialize the iteration count i and the objective function value. And initialize the iteration point to obtain the initial iteration point; The convex problem is solved using the initial iteration point to obtain the optimized solution of the convex problem after iteration; Update the number of iterations, the objective function value, and the iteration point; The minimum objective function value is achieved when the absolute value of the difference between two adjacent iterations is less than the set convergence precision. Total reachability for individual users The iteration ends when the maximum value is reached.

7. The precoding and common rate joint optimization method according to claim 6, characterized in that, The iteration points include i is the iteration number, which ranges from 0 to m, and m is the total number of iterations; The initialization iteration number i and the objective function value This includes: initial iteration count Initialize the target function value ; The initial iteration point is obtained by initializing the iteration point, which includes initializing the iteration point. = ; The initial iteration point is .

8. The precoding and common rate joint optimization method according to claim 7, characterized in that, Solving the convex problem using the initial iteration point yields an optimized solution after iteration, including: Using the initial iteration point Solve the convex problem to obtain the th iteration. Optimization solution for the shared rate allocated to each user New objective function value , No. The pre-encoded vector of each LED , No. The optimal solution generated after iteration using user-private rate slack variables. , No. The optimal solution generated after iteration from the slack variables of the shared rate of each user , No. The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's private data stream. and the The optimal solution after iteration of the signal-to-interference-plus-noise ratio slack variable of a user's public data stream. .

9. The precoding and common rate joint optimization method according to claim 8, characterized in that, The number of update iterations and the optimized solution obtained after iterating the convex problem include: make ,renew , , , ; in, This indicates that another iteration will be performed after this iteration, using the optimized solution from the previous iteration as the input for the next iteration. Specifically, this means using the new objective function value generated after the iteration. Assign to , Assign to , Assign to , Assign to .

10. The precoding and common rate joint optimization method according to claim 9, characterized in that, The step of terminating the iteration when the absolute value of the difference between the objective functions of two adjacent iterations is less than the set convergence precision, thereby maximizing the minimum user rate, includes: when The iteration ends; Among them, the algorithm based on continuous convex approximation iteratively... times, when and The difference is less than the set precision. Then the first The next iteration is based on the previous one. The optimal solution is obtained in -1 iterations. and the The optimal solution for the shared rate allocated to each user ; The optimal solution is obtained through iterative optimization. Find the optimal precoding matrix Thus, based on the optimal precoding matrix Find the first Private reachability rate for each user , According to the first The optimal solution for the shared rate allocated to each user Find the first Total reachability for each user to achieve .

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