Throughput optimization method for cell-free symbiotic radio network

Abstract

The invention discloses a throughput optimization method of a cell-free symbiotic radio network, each time slot comprises a CSR stage, a PSR stage and an AC stage, an access point sends a channel estimation control signal and carries out channel estimation after receiving an uplink pilot signal, and the access point carries out channel estimation after receiving the uplink pilot signal. The central controller uses maximization of backscatter communication throughput of the cell-free symbiotic radio network as a target function, and the maximum backscatter communication throughput of the cell-free symbiotic radio network is calculated to obtain estimation errors of a straight-chain channel and estimation errors of a backscatter channel; and calculating beam forming setting of the access point and the backscattering equipment, a time length distribution strategy of each stage and reflection coefficient setting of the backscattering equipment, and operating the cell-free symbiotic radio network according to a calculation result. According to the hybrid CSR-PSR setting, the advantages that CSR setting is beneficial to main communication and PSR setting is beneficial to backscatter communication are combined, and the total throughput of the backscatter network is maximized by optimizing the duration of the CSR stage and the PSR stage from the perspective of time length distribution.

Description

Technical Field

[0001] The present application belongs to the technical field of non-cell symbiotic radio networks, and in particular to a throughput optimization method for non-cell symbiotic radio networks. Background Art

[0002] The emergence of ultra-high-definition video and telemedicine applications has placed high demands on network data rates. 6G networks utilize a dense base station deployment architecture to achieve ultra-high data rates. However, this dense deployment of base stations has led to a scarcity of spectrum resources.

[0003] To address the challenges of scarce spectrum resources, symbiotic radio networks (SRNs) leverage the symbiotic relationship between primary and backscatter communications to improve spectrum efficiency. In an SRN, primary users (PUs) are granted access to the spectrum for primary communication and share the spectrum with backscatter devices (BDs) for backscatter communication. In an SRN, if the symbol period of backscatter communication is longer than that of primary communication, it is called a commensal symbiotic radio (CSR) setup; if the symbol period of backscatter communication is equal to that of primary communication, it is called a parasitic symbiotic radio (PSR) setup. In a CSR setup, backscatter communication utilizes the primary communication's RF signal to transmit backscattered data. The primary communication system views the backscatter signal as additional multipath gain and benefits from it. In a PSR setup, the primary communication system views the backscatter signal as interference.

[0004] To meet the challenge of ultra-high data rates, cell-free networks (CFNs) eliminate the concept of cell boundaries, enabling access points (APs) to cooperate in serving users, thereby enhancing spatial diversity and improving communication rates. In a CFN, APs are randomly distributed within a given area and connected to a central processing unit (CPU) via fronthaul links. Beamforming is used to optimize the complex weight vectors of the antenna array to increase communication rates.

[0005] To address the challenges of achieving ultra-high data rates in 6G networks, cell-free-symbiotic radio networks (CF-SRNs) are an effective solution. Existing CF-SRNs do not consider the advantages of a hybrid CSR-PSR setup and only use a single CSR or PSR setup, resulting in CF-SRNs focusing only on primary communication or backscatter communication. Summary of the Invention

[0006] In order to overcome the shortcomings of the existing technology, the present application provides a throughput optimization method for a cell-free symbiotic radio network, which is suitable for scenarios where the backscatter communication symbol period can be dynamically adjusted. It jointly optimizes the beamforming settings of the access point and the backscatter device, the duration allocation strategy of each stage, and the reflection coefficient setting of the backscatter device to maximize the total throughput of the backscatter communication.

[0007] In order to achieve the above objectives, the technical solutions of this application are as follows: A throughput optimization method for a cell-free symbiotic radio network, wherein each time slot of the cell-free symbiotic radio network includes a CSR phase, a PSR phase, and an AC phase, and the throughput optimization method for the cell-free symbiotic radio network comprises: The access point sends a channel estimation control signal to the receiver, and after receiving the control signal, the receiver sends an uplink pilot signal to all access points simultaneously; After receiving the uplink pilot signal, the access point performs channel estimation and calculates the direct link channel estimate and estimation error. The access point sends a channel estimation control signal to the backscatter device and the receiver, and the receiver sends an uplink pilot signal to all access points simultaneously through the backscatter device; After receiving the uplink pilot signal, the access point performs channel estimation and calculates the backscatter channel estimate and estimation error; All access points upload their direct link channel estimates and estimation errors, as well as backscatter channel estimates and estimation errors, to the central controller. The central controller uses maximizing the backscatter communication throughput of the cell-free coexistence radio network as its objective function. It then calculates the beamforming settings for the access points and backscatter devices, the duration allocation strategy for each phase, and the reflection coefficient settings for the backscatter devices. The cell-free coexistence radio network operates according to the calculation results.

[0008] Furthermore, the objective function is as follows: ; ; in, represents the backscatter communication throughput; Indicates that in the CSR stage The beamforming vectors of the access points, Indicates the Beamforming of each access point during the CSR phase; Indicates that it is in the PSR stage The beamforming vectors of the access points, Indicates the Beamforming of access points in the PSR phase; Indicates that in the AC stage The beamforming vectors of the backscatter devices, Indicates the Beamforming of a backscatter device in the AC phase; Indicates the duration allocation strategy for the CSR stage, PSR stage, and AC stage. ; express Reflection coefficient setting for each backscatter device, Indicates the The reflection coefficient of each backscatter device; Indicates bandwidth, express and The multiple relationship between represents the symbol period of the main communication, represents the symbol period of backscatter communication; :Indicates that from The access point passes through An estimate of the backscatter link channel from a backscatter device to a receiver; Indicates that from The channel from the backscatter device to the receiver; Indicates that from The covariance matrix of the channel estimation error from the access point to the receiver; Indicates that from The access point passes through The covariance matrix of the channel estimation error from the backscatter device to the receiver; represents the power spectral density of Gaussian white noise.

[0009] Furthermore, the objective function also includes a primary communication throughput constraint, that is, the primary network throughput is higher than the minimum requirement of the primary network throughput.

[0010] Furthermore, the objective function also includes access point power constraints, that is, the transmit power of each access point in the CSR phase or the PSR phase is lower than the maximum transmit power.

[0011] Furthermore, the objective function also includes a backscatter device energy constraint, that is, the energy consumed by the backscatter device in the AC phase does not exceed the total energy collected in the CSR phase and the PSR phase.

[0012] Furthermore, the objective function also includes a reflection coefficient constraint, and each reflection coefficient is greater than or equal to 0 and less than or equal to 1.

[0013] Furthermore, the objective function also includes a time slot length constraint, and the durations of the CSR phase, the PSR phase, and the AC phase are respectively greater than or equal to 0, and the sum is less than or equal to the time slot length.

[0014] Furthermore, the cell-free symbiotic radio network operates according to the calculation result, including: Allocate the running time of the CSR phase, PSR phase, and AC phase in a time slot according to the calculated duration allocation strategy for each phase; In the CSR phase, a mutualistic radio setting is used, where the period of the backscatter signal is greater than the period of the main signal. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. The backscatter device adjusts the impedance based on the reflection coefficient settings to achieve signal transmission and energy collection. In the PSR phase, a parasitic symbiotic radio setting is used, where the period of the backscattered signal is equal to the period of the main signal. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. The backscatter device adjusts the impedance based on the reflection coefficient settings to achieve signal transmission and energy collection. In the AC phase, the access point remains silent, and the backscatter device transmits data to the receiver in an active communication mode. The backscatter device adjusts the gain and phase offset of each antenna according to the calculated beamforming settings.

[0015] This application proposes a throughput optimization method for cell-free symbiotic radio networks. This method is based on the resource allocation problem of cell-free symbiotic radio networks in a hybrid CSR-PSR setting. Compared with traditional cell-free symbiotic radio network design and throughput maximization methods, it has the following advantages: (1) A hybrid CSR-PSR setting is designed in a cell-free coexistence radio network. The hybrid CSR-PSR setting combines the advantages of the CSR setting, which is beneficial for primary communication, and the PSR setting, which is beneficial for backscatter communication. From the perspective of time allocation, the trade-off between maximizing the total throughput of the backscatter network and improving the total throughput of the main network is achieved by optimizing the duration of the CSR phase and the PSR phase.

[0016] (2) Under the constraints of main communication throughput, access point power constraint, and backscattering device energy constraint, the beamforming settings of access points and backscattering devices, the time allocation strategy of each stage, and the reflection coefficient setting of backscattering devices are jointly optimized to maximize the total backscattering communication throughput of the cell-free symbiotic radio network. This is a multi-coupled high-dimensional variable non-convex problem, which effectively improves the total throughput of the backscattering network. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the throughput optimization method for a non-cell co-existence radio network of this application.

[0018] Figure 2 Schematic diagram of the radio network structure without cell coexistence.

[0019] Figure 3 This is the time slot structure diagram of this application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0021] One embodiment of the present application, such as Figure 1 As shown, a throughput optimization method for a non-cell symbiotic radio network is proposed. In this embodiment, each time slot of the non-cell symbiotic radio network includes a CSR phase, a PSR phase, and an AC phase. The throughput optimization method for the non-cell symbiotic radio network includes: Step S1: An access point sends a channel estimation control signal to a receiver. After receiving the control signal, the receiver sends an uplink pilot signal to all access points simultaneously.

[0022] The non-cell symbiotic radio network of this embodiment, such as Figure 2 As shown, it includes a central controller, access points, receivers, and backscatter devices. All access points are connected to a central controller, and each backscatter device is equipped with an energy harvester, an energy storage unit, a backscatter transmitter, and a microcontroller. Each time slot is designed to include a CSR phase (abbreviated as the symbiotic phase), a PSR phase (abbreviated as the parasitic phase), and an active communication (AC) phase. The entire cell-free symbiotic radio network consists of two parts: one is the primary network, which consists of access points and receivers, and the other is the secondary network or backscatter network, which consists of backscatter devices and receivers. The two networks exist in a symbiotic or parasitic form, which will not be described here.

[0023] First, the access point sends a first channel estimation control signal to the receiver. After receiving the control signal, the receiver sends an uplink pilot signal to all access points simultaneously.

[0024] Step S2: After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimation and estimation error of the direct link channel.

[0025] Linear Minimum Mean Square Error (LMMSE) is a signal processing technique primarily used to estimate the optimal linear estimate of a random vector. Its goal is to find a linear estimator that minimizes the mean square error (MSE) of the estimated error. In communication systems, the LMMSE algorithm is commonly used for channel estimation and equalization. For example, in wireless communications, signal transmission is affected by multipath and noise. The LMMSE algorithm effectively addresses these interferences and improves signal quality. In fiber-optic communication systems, the LMMSE algorithm helps equalizers better handle various interferences, ensuring accurate signal transmission. Furthermore, the LMMSE algorithm is widely used in digital signal processing for signal denoising and enhancement, improving signal processing accuracy.

[0026] This embodiment uses the linear minimum mean square error (LMMSE) channel estimation model to perform channel estimation and calculate the estimation and estimation error of the direct link channel. The direct link channel refers to the channel from an access point to the receiver, such as or .

[0027] Step S3: The access point sends a channel estimation control signal to the backscatter device and the receiver, and the receiver simultaneously sends an uplink pilot signal to all access points via the backscatter device.

[0028] The channel estimation phase of the cell-free coexistence radio network of the present application includes two phases. The first phase is described by steps 1-2. In the first phase, the backscatter device remains silent (which can be understood as shutting down) to avoid affecting the estimation of the direct link channel between the receiver and the access point. The second phase is described by steps 3-4. The second phase is used to obtain the estimation and estimation error of the backscatter channel. The backscatter channel refers to the channel from the access point to the receiver through the backscatter device, such as .

[0029] This step sends the channel estimation control signal again to estimate the backscatter channel and the estimation error in the second phase. The receiver sends an uplink pilot signal to all access points simultaneously, and the signal is reflected by the backscatter device one by one in sequence to all access points simultaneously.

[0030] Step S4: After receiving the uplink pilot signal, the access point performs channel estimation and calculates the backscatter channel estimate and the estimation error.

[0031] In the second phase, the access point receives both the pilot signal directly transmitted by the transmitter and the pilot signal reflected by the backscatter device. These two signals are combined. Since the direct link channel estimate and estimation error have been obtained in the first phase, the LMMSE algorithm subtracts the pilot signal directly transmitted by the receiver from the combined received signal. The LMMSE algorithm then outputs the backscatter channel estimate and estimation error according to the LMMSE calculation rules.

[0032] Step S5: All access points upload the direct link channel estimate and estimation error, and the backscatter channel estimate and estimation error to the central controller. The central controller uses maximizing the backscatter communication throughput of the cell-free coexistence radio network as the objective function to calculate the beamforming settings of the access points and backscatter devices, the duration allocation strategy for each stage, and the reflection coefficient setting of the backscatter devices.

[0033] In this step, all access points upload global channel estimation information to the central controller CPU. The global channel estimation information includes the estimation and estimation error of the direct link channel and the estimation and estimation error of the backscatter channel.

[0034] The central controller then calculates the beamforming settings for the access points and backscatter devices, the duration allocation strategy for each phase, and the reflection coefficient settings for the backscatter devices based on the input global channel estimation information, the primary communication throughput constraint, the access point power constraint, and the backscatter device energy constraint to maximize the total backscatter communication throughput of the cell-free coexistence radio network.

[0035] The CPU performs calculations based on the semi-definite relaxation (SDR) of block coordinate descent (BCD) and the successive convex approximation (SCA) algorithm. The objective function for maximizing the total backscattered communication throughput of the non-cell coexistence radio network is expressed as: ; ; Variables to be optimized: : Indicates the CSR stage The beamforming vectors of the access points, ; : Indicates the PSR stage The beamforming vectors of the access points, ; : Indicates the AC phase The beamforming vectors of the backscatter devices, ; : Indicates the duration allocation strategy for the CSR stage, PSR stage, and AC stage. , Indicates the duration allocation strategy of the CSR stage, Indicates the duration allocation strategy of the PSR stage, Indicates the duration allocation strategy of the AC phase; :express Reflection coefficient setting for each backscatter device, .

[0036] in: : represents the total backscatter communication throughput; : indicates bandwidth; :express and The multiple relationship between ; : represents the symbol period of the main communication; : represents the symbol period of backscatter communication; :Indicates the The reflection coefficient of each backscatter device; :Indicates that from The access point passes through Estimation of the cascaded backscatter link channel from each backscatter device to the receiver; :Indicates that from The channel from the backscatter device to the receiver; :Indicates the Beamforming of each access point during the CSR phase; :Indicates the Beamforming of access points in the PSR phase; :Indicates the Beamforming of a backscatter device in the AC phase; :Indicates that from The covariance matrix of the channel estimation error from the access point to the receiver; :Indicates that from The access point passes through The covariance matrix of the channel estimation error from the backscatter device to the receiver; : Represents the power spectral density of Gaussian white noise.

[0037] The primary communication throughput constraint in this embodiment, that is, the primary network throughput is higher than the minimum requirement of the primary network throughput, is expressed as follows: , ; .

[0038] in: : represents the total throughput of the primary network; : Indicates the minimum requirement for the total throughput of the main network.

[0039] : Indicates the number of signal states possessed by a backscatter device using phase-shift keying modulation; :express The backscatter symbol vector of the backscatter devices, ; : represents the set of all backscattered symbol vectors; :Indicates that from An estimate of the direct link channel from the access point to the receiver; In this embodiment, the access point power constraint, that is, the transmit power of each access point in the CSR phase or the PSR phase is lower than the maximum transmit power, is expressed as follows: ; .

[0040] in: :Indicates the m Maximum transmit power of each access point; Indicates inclusion A collection of access points; represents the Euclidean norm.

[0041] In this embodiment, the backscatter device energy constraint is that the energy consumed by the backscatter device in the AC phase does not exceed the total energy collected in the CSR phase and the PSR phase. The reflection coefficient constraint is that each reflection coefficient is greater than or equal to 0 and less than or equal to 1. The time slot length constraint is that the duration of the CSR phase, PSR phase, and AC phase in the time slot is greater than or equal to 0, and the total is less than or equal to the time slot length. The formulas are: ; ; ; .

[0042] in: : represents the backscatter device collection; : Indicates the duration of the time slot; :Indicates the The sum of the energy captured by the backscattering devices in the CSR and PSR phases, ; : represents the energy capture efficiency factor; From Access point to the channels for backscatter devices.

[0043] for , first use block coordinate descent to This is transformed into the following three sub-questions: Time allocation strategy optimization problem : The problem is to maximize the total backscatter communication throughput of the cell-free coexistence radio network by optimizing the duration allocation strategy of each phase given the beamforming settings of the access point and backscatter device and the reflection coefficient settings of the backscatter device. , is a linear programming problem, and the convex optimization toolbox is used to obtain the optimal solution.

[0044] Optimizing the beamforming settings for outbound access points and backscatter devices : The problem is to maximize the total backscatter communication throughput of the cell-free coexistence radio network by optimizing the beamforming settings of the access point and backscatter device given the time allocation strategy of each phase and the reflection coefficient setting of the backscatter device. , due to the non-convexity of the problem, it cannot be solved directly.

[0045] In order to solve , first introduce the following cascade vector: , , , .

[0046] Further, use the SDP method to convert ,make , , , . Introduce SDP variables, , When the introduced SDP variable satisfies the semi-positive definite property and has a rank of 1, Medium Optimization Equivalent to optimization , , .

[0047] Going one step further, The expression is non-convex, and the SDP method is used to deal with The terms that cause non-convexity in the expression of have the following equivalent transformation process: , , in, is a diagonal matrix, , , It means finding the trace of a matrix.

[0048] Similarly, use the SDP method to handle The terms that cause non-convexity in , have the following equivalent transformation process: , , in, , Extracts the diagonal elements of a matrix.

[0049] Further, use the SDP method to process The terms that cause non-convexity in , have the following equivalent transformation process: in, .

[0050] According to the above conversion process using the SDP method, is converted to , the formula is: ; ; ; ; ; ; ; ; in, was rewritten as , and Rewritten as C9, adding SDP constraints 、 、 、 . :Indicates that No. Rank Column to Rank A submatrix consisting of column elements.

[0051] Further, due to The objective function and Fractional structure and rank 1 constraint in and The non-convexity of It is a non-convex problem. To make it easier to handle, SCA is used to process the objective function and , and use the SDR method to relax and , the following processing procedures are involved: ; ; in, express In the The local solution of the iteration. Using SCA, according to the The local solution of the iteration is found The local solution of the iteration is obtained when the difference between the objective function of the previous and next two iterations is less than the preset accuracy, and the SCA iteration converges. Specifically, according to the processed objective function and ,question Transformed into a convex problem , using the convex optimization toolbox to obtain The optimal solution is considered to be No. The local solution of the iteration is obtained when the iteration converges. The approximate optimal solution for the beamforming settings of the access point and backscatter device is obtained. It is worth noting that is equivalently converted into ,therefore The approximate optimal solution is also The approximate optimal solution of .

[0052] c. Backscatter device reflection coefficient setting optimization problem P4: The problem is to maximize the total backscatter communication throughput of the cell-free coexistence radio network by optimizing the reflection coefficient setting of the backscatter device given the beamforming settings of the access point and backscatter device and the time allocation strategy of each phase. Due to the non-convexity of the problem, it cannot be solved directly.

[0053] similar In order to solve the problem , using the SDP method to convert About dealing with non-convex constraints ,for The first term of the expression has the following equivalent transformation process: ; ; in, , , . is the introduced SDP variable, and When the SDP variable is introduced When the semi-positive definite property is satisfied and the rank is 1, Medium Optimization Equivalence and Optimization . , , .

[0054] for The second term of the expression has the following equivalent transformation process: ; ; in, , , .

[0055] Further, similar The objective function transformation process in is processed using the SDP method The objective function of the above transformation process Equivalently converted to , the formula is: ; : ; ; ; ; ; ; in, was rewritten as , was rewritten as , was rewritten as , add SDP constraints , , .

[0056] Furthermore, due to The objective function and The fraction structure in , and the rank 1 constraint The non-convexity of It is a non-convex problem. Similar to The processing method is to use SCA The objective function is approximately The linear objective function is Approximately linear constraints. It is a convex optimization problem. Using the convex optimization toolbox, we can get The optimal solution is considered to be No. The local solution of the iteration is obtained when the iteration converges. The approximate optimal solution of , that is, the approximate optimal solution of the reflection coefficient setting of the backscattering device is obtained. It is worth noting that is equivalently converted into ,therefore The approximate optimal solution is also The approximate optimal solution of .

[0057] After the central controller calculates the beamforming settings of the access point and backscatter device, the time allocation strategy for each stage, and the reflection coefficient of the backscatter device, the calculation results of the central controller are sent to all backscatter devices via the access point.

[0058] Step S6: The non-cell symbiotic radio network operates according to the calculation result.

[0059] In this embodiment, Figure 3 As shown in the figure, the cell-free symbiotic wireless network operates in three phases within a time slot: the CSR phase (symbiotic phase), the PSR phase (parasitic phase), and the AC phase (active communication phase). The operating time of each phase is determined by a time allocation strategy calculated by a central controller. During the CSR and PSR phases, the central controller calculates the access point's beamforming and the backscatter device's reflection coefficient settings. The access point performs active communication, while the backscatter device performs energy harvesting and backscatter communication. During the AC phase, the central controller calculates the backscatter device's beamforming settings, the access point remains silent, and the backscatter device performs active communication.

[0060] During the CSR phase, a cell-free symbiotic wireless network uses a mutually beneficial symbiotic radio configuration, meaning the backscatter signal period is greater than the main signal period. During this phase, the access point transmits the main signal to the receiver, and the backscatter device reflects the RF signal from the access point back to the receiver, superimposing the backscattered signals. The backscatter device simultaneously reflects the signal and collects energy through energy splitting. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. Similarly, the backscatter device adjusts its impedance based on the reflection coefficient settings to achieve signal transmission and energy collection.

[0061] The cell-free symbiotic wireless network then adopts a parasitic symbiotic radio configuration during the PSR phase, where the backscatter signal period is equal to the primary signal period. The CSR configuration favors primary signal transmission, while the PSR phase favors reverse signal transmission. By adjusting the duration of the two configurations within a time slot, a hybrid CSR-PSR configuration can be designed. This balances the trade-off between maximizing the total backscatter network throughput and improving the total primary network throughput from a time allocation perspective by optimizing the durations of the CSR and PSR phases. Furthermore, the CSR and PSR phases differ only in the secondary signal period; the communication modes and configurations of each device are similar. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. Similarly, the backscatter device adjusts its impedance based on the reflection coefficient settings to achieve signal transmission and energy harvesting.

[0062] During the AC phase, the primary network's throughput meets the predetermined threshold, and the access point remains silent, no longer transmitting the primary signal. The backscatter device consumes the energy harvested during the CSR and PSR phases to actively transmit data to the receiver. Based on the calculated beamforming settings, the backscatter device adjusts the gain and phase offset of each antenna.

[0063] During the CSR and PSR phases, all access points use beamforming and transmit RF signals to the receiver via direct link and backscatter channels. Backscatter devices use beamforming and reflection coefficients to reflect RF signals from the access points toward the receiver while capturing energy. During the AC phase, backscatter devices use beamforming and consume the energy captured during the CSR and PSR phases to actively transmit RF signals to the receiver.

[0064] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A throughput optimization method for a non-cell symbiotic radio network, characterized in that: Each time slot of the non-cell symbiotic radio network includes a CSR phase, a PSR phase, and an AC phase. The throughput optimization method of the non-cell symbiotic radio network includes: The access point sends a channel estimation control signal to the receiver, and after receiving the control signal, the receiver sends an uplink pilot signal to all access points simultaneously; After receiving the uplink pilot signal, the access point performs channel estimation and calculates the direct link channel estimate and estimation error. The access point sends a channel estimation control signal to the backscatter device and the receiver, and the receiver sends an uplink pilot signal to all access points simultaneously through the backscatter device; After receiving the uplink pilot signal, the access point performs channel estimation and calculates the backscatter channel estimate and estimation error; All access points upload their direct link channel estimates and estimation errors, as well as backscatter channel estimates and estimation errors, to the central controller. The central controller uses maximizing the backscatter communication throughput of the cell-free coexistence radio network as its objective function. It then calculates the beamforming settings for the access points and backscatter devices, the duration allocation strategy for each phase, and the reflection coefficient settings for the backscatter devices. The cell-free coexistence radio network operates according to the calculation results.

2. The throughput optimization method for a non-cell symbiotic radio network according to claim 1, characterized in that: The objective function is as follows: ； ； in, represents the backscatter communication throughput; Indicates that in the CSR stage The beamforming vectors of the access points, Indicates the Beamforming of each access point in the CSR phase; Indicates that it is in the PSR stage The beamforming vectors of the access points, Indicates the Beamforming of access points in the PSR phase; Indicates that in the AC stage The beamforming vectors of the backscatter devices, Indicates the Beamforming of a backscatter device in the AC phase; Indicates the duration allocation strategy for the CSR stage, PSR stage, and AC stage. ; express Reflection coefficient setting for each backscatter device, Indicates the The reflection coefficient of each backscatter device; Indicates bandwidth, express and The multiple relationship between represents the symbol period of the main communication, represents the symbol period of backscatter communication; :Indicates that from The access point passes through An estimate of the backscatter link channel from a backscatter device to a receiver; Indicates that from The channel from the backscatter device to the receiver; Indicates that from The covariance matrix of the channel estimation error from the access point to the receiver; Indicates that from Access point through the The covariance matrix of the channel estimation error from the backscatter device to the receiver; represents the power spectral density of Gaussian white noise.

3. The throughput optimization method for a non-cell symbiotic radio network according to claim 2, characterized in that: The objective function also includes a primary communication throughput constraint, ie, the primary network throughput must be higher than a minimum requirement for the primary network throughput.

4. The throughput optimization method for a non-cell symbiotic radio network according to claim 2, characterized in that: The objective function also includes access point power constraints, that is, the transmit power of each access point in the CSR phase or the PSR phase is lower than the maximum transmit power.

5. The throughput optimization method for a non-cell symbiotic radio network according to claim 2, characterized in that: The objective function also includes a backscatter device energy constraint, ie, the energy consumed by the backscatter device in the AC phase does not exceed the total energy collected in the CSR phase and the PSR phase.

6. The throughput optimization method for a non-cell symbiotic radio network according to claim 2, characterized in that: The objective function also includes a reflection coefficient constraint, and each reflection coefficient is greater than or equal to 0 and less than or equal to 1.

7. The throughput optimization method for a non-cell symbiotic radio network according to claim 2, characterized in that: The objective function also includes a time slot length constraint, where the durations of the CSR phase, the PSR phase, and the AC phase are respectively greater than or equal to 0, and the sum thereof is less than or equal to the time slot length.

8. The throughput optimization method for a non-cell symbiotic radio network according to claim 1, characterized in that: The cell-free symbiotic radio network operates according to the calculation result, including: Allocate the running time of the CSR phase, PSR phase, and AC phase in a time slot according to the calculated duration allocation strategy for each phase; In the CSR phase, a mutualistic radio setting is used, where the period of the backscatter signal is greater than the period of the main signal. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. The backscatter device adjusts the impedance based on the reflection coefficient settings to achieve signal transmission and energy collection. In the PSR phase, a parasitic symbiotic radio setting is used, where the period of the backscattered signal is equal to the period of the main signal. The access point adjusts the gain and phase offset of each antenna based on the calculated beamforming settings. The backscatter device adjusts the impedance based on the reflection coefficient settings to achieve signal transmission and energy collection. In the AC phase, the access point remains silent, and the backscatter device transmits data to the receiver in an active communication mode. The backscatter device adjusts the gain and phase offset of each antenna according to the calculated beamforming settings.

Images