A method for throughput optimization of a cell-free radio network

Abstract

The application discloses a throughput optimization method of a cell-free 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 performs channel estimation after receiving an uplink pilot signal, and calculates an estimation and an estimation error of a direct link channel, and an estimation and an estimation error of a backscatter channel, a central controller takes maximizing a backscatter communication throughput of the cell-free radio network as an objective function, calculates beamforming settings of the access point and the backscatter device, time length allocation strategies of each stage, and reflection coefficient settings of the backscatter device, and the cell-free radio network operates according to the calculation result. The mixed CSR-PSR settings combine the advantages of the CSR settings which are beneficial to main communication and the PSR settings which are beneficial to backscatter communication, from the perspective of time length allocation, the durations of the CSR stage and the PSR stage are optimized, and the total backscatter network throughput is maximized.

Description

Technical Field

[0001] This application belongs to the field of cellless co-occurring radio network technology, and particularly relates to a throughput optimization method for cellless co-occurring radio networks. Background Technology

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

[0003] To address the challenges posed by scarce spectrum resources, symbiotic radio networks (SRNs) leverage the symbiotic relationship between primary and backscatter communication to improve spectrum efficiency. In an SRN, primary users (PUs) are authorized to access 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 common 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 radio frequency signal of primary communication to transmit backscattered data, and the primary communication system benefits from the additional multipath gain derived from the backscattered signal. In a PSR setup, the primary communication system treats the backscattered signal as interference.

[0004] To address 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 CFNs, access points are randomly distributed within a given area, connected to a central processing unit (CPU) via fronthaul links, and employ beamforming to optimize the complex weight vector of the antenna array to improve 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 hybrid CSR-PSR setups, employing only a single CSR or PSR setup, resulting in CF-SRNs focusing solely on primary or backscatter communication. Summary of the Invention

[0006] To overcome the shortcomings of existing technologies, this application provides a throughput optimization method for cellless co-occurring radio networks, applicable to scenarios where the symbol period of backscatter communication can be dynamically adjusted. It jointly optimizes the beamforming settings of access points and backscatter devices, the duration allocation strategy for each stage, and the reflection coefficient settings of backscatter devices to maximize the total throughput of backscatter communication.

[0007] To achieve the above objectives, the technical solution of this application is as follows:

[0008] A throughput optimization method for a cell-free co-occurring radio network, wherein each time slot of the cell-free co-occurring radio network includes a CSR phase, a PSR phase, and an AC phase, and the throughput optimization method for the cell-free co-occurring radio network includes:

[0009] The access point sends a channel estimation control signal to the receiver, and after receiving the control signal, the receiver simultaneously sends an uplink pilot signal to all access points.

[0010] After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimate and estimation error of the direct-link channel.

[0011] The access point sends a channel estimation control signal to the backscattering device and the receiver, and the receiver sends an uplink pilot signal to all access points simultaneously through the backscattering device.

[0012] After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimation of the backscatter channel and the estimation error.

[0013] All access points upload the estimation and estimation error of the direct link channel and the estimation and estimation error of the backscatter channel to the central controller. The central controller uses the maximization of the backscatter communication throughput of the cellless co-occurrence radio network as the objective function to calculate the beamforming settings of the access points and backscatter devices, the duration allocation strategy of each stage, and the reflection coefficient settings of the backscatter devices.

[0014] The non-cell coexisting radio network operates based on the calculation results.

[0015] Furthermore, the objective function is as follows:

[0016] ;

[0017] ;

[0018] in, Indicates the throughput of backscatter communication; Indicating the CSR stage Beamforming vectors for each access point Indicates the first Beamforming of each access point during the CSR phase; Indicates the PSR stage Beamforming vectors for each access point Indicates the first Beamforming of each access point during the PSR phase; Indicates the AC phase Beamforming vector of a backscattering device Indicates the first Beamforming of a backscattering device in the AC phase; This indicates the time allocation strategy for the CSR, PSR, and AC phases. ; express The reflection coefficient settings for each backscattering device Indicates the first The reflection coefficient of a backscattering device; Indicates bandwidth. express and The multiple relationship between them Indicates the symbol period of the main communication. The symbol period represents the period of backscatter communication; : indicates from the first The access point passes through the first Estimation of the backscatter link channel from the backscattering device to the receiver; Indicates from the first A backscattering device to the receiver channel; Indicates from the first The covariance matrix of the channel estimation error from each access point to the receiver; Indicates from the first The access point passes through the first The covariance matrix of the channel estimation error from each backscattering device to the receiver; This represents the power spectral density of Gaussian white noise.

[0019] Furthermore, the objective function also includes a main communication throughput constraint, namely, a minimum requirement that the main network throughput is higher than the main network throughput.

[0020] Furthermore, the objective function also includes access point power constraints, namely, the transmit power of each access point during the CSR or PSR phase is lower than the maximum transmit power.

[0021] Furthermore, the objective function also includes an energy constraint on the backscattering device, namely, the energy consumed by the backscattering device in the AC phase does not exceed the total energy collected in the CSR and PSR phases.

[0022] Furthermore, the objective function also includes reflection coefficient constraints, where each reflection coefficient is greater than or equal to 0 and less than or equal to 1.

[0023] Furthermore, the objective function also includes a time slot length constraint, where the durations of the CSR phase, PSR phase, and AC phase are each greater than or equal to 0, and their sum is less than or equal to the time slot duration.

[0024] Furthermore, the cell-free coexistence radio network operates based on the calculation results, including:

[0025] Based on the calculated duration allocation strategy for each stage, allocate the running time of the CSR stage, PSR stage, and AC stage in a time slot;

[0026] In the CSR phase, a reciprocal radio setup is adopted, where the period of the backscattered signal is longer than the period of the main signal; the access point is set up with calculated beamforming, and the gain and phase offset of each antenna are adjusted; the backscattering device is set up with the reflection coefficient, and the impedance is adjusted to achieve signal transmission and energy harvesting.

[0027] In the PSR phase, a parasitic radio setup is used, where the period of the backscattered signal is equal to the period of the main signal; the access point is set up according to the calculated beamforming setup, adjusting the gain and phase shift of each antenna; the backscattering device is set up according to the reflection coefficient, adjusting the impedance to achieve signal transmission and energy harvesting.

[0028] During the AC phase, the access point remains silent, and the backscatter device transmits data to the receiver via active communication. The backscatter device adjusts the gain and phase shift of each antenna based on the calculated beamforming settings.

[0029] This application proposes a throughput optimization method for cell-free co-occurring radio networks. Based on the resource allocation problem of cell-free co-occurring radio networks with a hybrid CSR-PSR configuration, this method has the following advantages compared to traditional cell-free co-occurring radio network design and throughput maximization methods:

[0030] (1) A hybrid CSR-PSR setting was designed in a cellless co-occurrence radio network. The hybrid CSR-PSR setting combines the advantages of CSR setting for main communication and PSR setting for backscatter communication. From the perspective of time allocation, by optimizing the duration of CSR phase and PSR phase, the balance between maximizing the total throughput of backscatter network and improving the total throughput of main network is achieved.

[0031] (2) Under the constraints of main communication throughput, access point power, and backscattering device energy, the joint optimization of beamforming settings of access point and backscattering device, duration allocation strategy of each stage, and reflection coefficient settings of backscattering device to maximize the total backscattering communication throughput of cellless co-occurring radio network is a multi-coupled high-dimensional variable non-convex problem, which effectively improves the total throughput of backscattering network. Attached Figure Description

[0032] Figure 1 This is a flowchart of the throughput optimization method for cell-free coexisting radio networks in this application.

[0033] Figure 2 This is a schematic diagram of a cellless coexisting radio network structure.

[0034] Figure 3 This is a time slot structure diagram for this application. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0036] One embodiment of this application, such as Figure 1 As shown, a throughput optimization method for cell-free co-occurring radio networks is proposed. In this embodiment, each time slot of the cell-free co-occurring radio network includes a CSR phase, a PSR phase, and an AC phase. The throughput optimization method for the cell-free co-occurring radio network includes:

[0037] Step S1: The access point sends a channel estimation control signal to the receiver. After receiving the control signal, the receiver simultaneously sends an uplink pilot signal to all access points.

[0038] The cell-free coexisting radio network of this embodiment, such as Figure 2As shown, the system includes a central controller, access points, receivers, and backscattering devices. All access points are connected to a single central controller, and each backscattering device is equipped with an energy harvester, an energy storage unit, a backscattering transmitter, and a microcontroller. Each time slot is designed to include a CSR phase (also known as the symbiotic phase), a PSR phase (also known as the parasitic phase), and an active communication (AC) phase. The entire cell-free symbiotic radio network comprises two parts: a primary network consisting of access points and receivers, and a secondary network, or backscattering network, consisting of backscattering devices and receivers. These two networks exist in a symbiotic or parasitic manner, which will not be elaborated further here.

[0039] First, the access point sends a first channel estimation control signal to the receiver. After receiving the control signal, the receiver simultaneously sends an uplink pilot signal to all access points.

[0040] Step S2: After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimation of the direct-link channel and the estimation error.

[0041] Linear Minimum Mean Square Error (LMMSE) is a signal processing technique primarily used to estimate the optimal linear value of a random vector. Its goal is to find a linear estimator that minimizes the mean square error (MSE) of the estimation. In communication systems, the LMMSE algorithm is commonly used for channel estimation and equalization. For example, in wireless communication, signal transmission is affected by multipath effects and noise; the LMMSE algorithm can effectively address these interferences and improve 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 the accuracy of signal processing.

[0042] This embodiment utilizes the Linear Least Mean Square Error (LMMSE) channel estimation model for channel estimation, calculating the estimate and estimation error of the direct-link channel. A direct-link channel refers to the channel from an access point to the receiver, such as... or .

[0043] Step S3: The access point sends a channel estimation control signal to the backscattering device and the receiver. The receiver sends an uplink pilot signal to all access points simultaneously through the backscattering device.

[0044] The channel estimation stage of the cell-free coexisting radio network in this application comprises two stages. The first stage, described in steps 1-2, involves the backscattering device remaining silent (essentially powered off) to avoid affecting the estimation of the receiver-access point direct link channel. The second stage, described in steps 3-4, is used to obtain the estimation of the backscattered channel and its estimation error. The backscattered channel refers to the channel from the access point through the backscattering device to the receiver, such as... .

[0045] This step involves retransmitting the channel estimation control signal to estimate the backscatter channel and its estimation error in the second stage. The receiver simultaneously transmits an uplink pilot signal to all access points, which is then reflected sequentially by the backscattering device to all access points simultaneously.

[0046] Step S4: After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimation of the backscatter channel and the estimation error.

[0047] In the second phase, the access point directly receives the pilot signal transmitted by the transmitter and also receives the pilot signal reflected by the backscattering device. These two signals are combined and received. Since the direct-link channel estimate and estimation error have already been obtained in the first phase, the LMMSE can be calculated by subtracting the directly received pilot signal from the receiver from the combined received signal. Subsequently, according to the LMMSE calculation rules, the backscattering channel estimate and estimation error are output.

[0048] Step S5: All access points upload the estimation and estimation error of the direct link channel and the estimation and estimation error of the backscatter channel to the central controller. The central controller uses the maximization of the backscatter communication throughput of the cell-free co-occurrence 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 settings of the backscatter devices.

[0049] In this step, all access points upload global channel estimation information to the central controller CPU. This 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.

[0050] Then, based on the input global channel estimation information, main communication throughput constraints, access point power constraints, and backscatter device energy constraints, the central controller calculates the beamforming settings of the access point and backscatter device, the duration allocation strategy for each stage, and the reflection coefficient settings of the backscatter device to maximize the total backscatter communication throughput of the cellless co-occurring radio network.

[0051] The CPU performs computations based on semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms using block coordinate descent (BCD). The objective function for maximizing the total backscatter communication throughput of the cell-free co-occurring radio network is expressed as:

[0052] ;

[0053] ;

[0054] Variables to be optimized:

[0055] : Indicates the CSR stage Beamforming vectors for each access point ;

[0056] : Indicates the PSR stage Beamforming vectors for each access point ;

[0057] : Indicates the AC phase Beamforming vector of a backscattering device ;

[0058] : Indicates the time allocation strategy for the CSR, PSR, and AC phases. , This indicates the time allocation strategy for the CSR phase. This indicates the time allocation strategy for the PSR phase. This indicates the time allocation strategy for the AC phase;

[0059] :express The reflection coefficient settings for each backscattering device .

[0060] in:

[0061] : Represents the total throughput of backscatter communication;

[0062] : Indicates bandwidth;

[0063] :express and The multiple relationship between them, that is ;

[0064] : Indicates the symbol period of the main communication;

[0065] : Indicates the symbol period of backscatter communication;

[0066] : indicates the first The reflection coefficient of a backscattering device;

[0067] : indicates from the first The access point passes through the first Estimation of the cascaded backscatter link channel from one backscattering device to the receiver;

[0068] : indicates from the first A backscattering device to the receiver channel;

[0069] : indicates the first Beamforming of each access point during the CSR phase;

[0070] : indicates the first Beamforming of each access point during the PSR phase;

[0071] : indicates the first Beamforming of a backscattering device in the AC phase;

[0072] : indicates from the first The covariance matrix of the channel estimation error from each access point to the receiver;

[0073] : indicates from the first The access point passes through the first The covariance matrix of the channel estimation error from each backscattering device to the receiver;

[0074] : Represents the power spectral density of Gaussian white noise.

[0075] In this embodiment, the main communication throughput constraint, i.e., the minimum requirement that the main network throughput must be higher than the main network throughput, is expressed by the formula:

[0076] ,

[0077] ;

[0078] .

[0079] in:

[0080] : Represents the total throughput of the main network;

[0081] : Indicates the minimum requirement for the total throughput of the main network.

[0082] : Indicates the number of signal states possessed by a backscattering device employing phase shift keying modulation;

[0083] :express The backscattering symbol vector of a backscattering device ;

[0084] : Represents the set of all backscattered symbol vectors;

[0085] : indicates from the first Estimation of the direct link channel from each access point to the receiver;

[0086] In this embodiment, the access point power constraint means that the transmit power of each access point during the CSR or PSR phase is lower than the maximum transmit power, as expressed by the formula:

[0087] ;

[0088] .

[0089] in:

[0090] : indicates the first m Maximum transmit power of each access point;

[0091] Indicates inclusion A set of access points;

[0092] This represents the Euclidean norm.

[0093] In this embodiment, the backscattering device is constrained in the following ways: energy consumption during the AC phase does not exceed the total energy collected during the CSR and PSR phases; reflection coefficient is constrained, meaning each reflection coefficient is greater than or equal to 0 and less than or equal to 1; and time slot length is constrained, meaning the durations of the CSR, PSR, and AC phases within a time slot are each greater than or equal to 0, and their sum is less than or equal to the time slot duration. The formulas are as follows:

[0094] ;

[0095] ;

[0096] ;

[0097] .

[0098] in:

[0099] : Represents a set of backscattering devices;

[0100] : Indicates the duration of a time slot;

[0101] : indicates the first The total energy captured by each backscattering device in the CSR and PSR phases ;

[0102] : Indicates the energy capture efficiency factor;

[0103] From the The access point to the first Channels of a backscattering device.

[0104] for First, the block coordinate descent method is used to... This can be broken down into the following three sub-problems:

[0105] Time allocation strategy optimization problem :

[0106]

[0107] This problem addresses the question of maximizing the total backscatter communication throughput of a cell-free co-occurrence radio network by optimizing the timing allocation strategy at each stage, given the beamforming settings of the access point and backscattering device, and the reflection coefficient settings of the backscattering device. This is a linear programming problem, and the optimal solution can be obtained using the convex optimization toolbox.

[0108] Optimization of beamforming settings for output access points and backscatter devices :

[0109]

[0110] This problem addresses how to maximize the total backscatter communication throughput of a cell-free co-occurrence radio network by optimizing the beamforming settings of the access point and backscatter devices, given the duration allocation strategy for each stage and the reflection coefficient settings of the backscatter devices. Due to the non-convex nature of the problem, it cannot be solved directly.

[0111] In order to solve First, we introduce the following concatenated vectors: , , , .

[0112] Furthermore, the SDP method is used for equivalent transformation. ,make , , , Introduce SDP variables. , When the introduced SDP variable satisfies the positive semidefinite property and has a rank of 1, in Medium optimization Equivalent to optimization , , .

[0113] Going a step further, The expression is non-convex, so the SDP method is used for processing. The following equivalent transformation process applies to the terms that cause non-convexity in the expression:

[0114]

[0115] ,

[0116] ,

[0117] in, It is a diagonal matrix. , , This indicates finding the trace of a matrix.

[0118] Similarly, the SDP method is used for processing. The following is an equivalent transformation process for terms that introduce non-convexity:

[0119] ,

[0120] ,

[0121] in, , This indicates that the diagonal elements of the matrix are extracted.

[0122] Furthermore, the SDP method is used for processing. The following is an equivalent transformation process for terms that introduce non-convexity:

[0123]

[0124] in, .

[0125] Based on the above conversion process using the SDP method, Converted to The formula is expressed as:

[0126] ;

[0127] ;

[0128] ;

[0129] ;

[0130] ;

[0131] ;

[0132] ;

[0133] ;

[0134] in, Rewritten as , and Rewritten as C9, with added SDP constraints. , , , . : indicates by The Line number Listed to number Line number A submatrix composed of column elements.

[0135] Furthermore, due to Objective function and Fractional structure and rank-1 constraint in and nonconvexity, This is a non-convex problem. For ease of handling, SCA is used to process the objective function and... And relax using the SDR method and The following processing steps are involved:

[0136] ;

[0137] ;

[0138] in, express In the Local solution of the nth iteration. Using SCA, according to the nth iteration. The local solution of the nth iteration is found. The local solution of the next iteration is obtained when the difference between the objective functions of the previous and subsequent iterations is less than the preset precision. The SCA iteration then converges. The approximate optimal solution. Specifically, based on the processed objective function and ,question Transformed into a convex problem Using the convex optimization toolbox, we can obtain the following results. The optimal solution, which is considered as The The local solution of the next iteration is obtained when the iteration converges. The approximate optimal solution is obtained, that is, the approximate optimal solution for the beamforming settings of the access point and the backscattering device. It is worth noting that... Equivalently transformed ,therefore The approximate optimal solution is also The approximate optimal solution.

[0139] c. Optimization of reflection coefficient settings for backscattering devices (P4):

[0140]

[0141] This problem addresses the challenge of maximizing the total backscatter communication throughput of a cell-free co-occurrence radio network by optimizing the reflection coefficient settings of the backscatter devices, given the beamforming configuration of the access point and backscatter equipment, and the duration allocation strategy for each stage. Due to the non-convex nature of the problem, it cannot be solved directly.

[0142] similar The solution process, in order to solve Equivalent transformation using SDP method Regarding the handling of non-convex constraints ,for The first term of the expression has the following equivalent transformation process:

[0143] ;

[0144] ;

[0145] in, , , . It is an introduced SDP variable, and When introducing SDP variables When the semi-positive definite property is satisfied and the rank is 1, in Optimization Equivalence and Optimization . , , .

[0146] for The second term of the expression has the following equivalent transformation process:

[0147] ;

[0148] ;

[0149] in, , , .

[0150] Furthermore, similar The objective function transformation process in the code is handled using the SDP method. The objective function. Based on the above transformation process. Equivalent conversion The formula is expressed as:

[0151] ;

[0152] :

[0153] ;

[0154] ;

[0155] ;

[0156] ;

[0157] ;

[0158] ;

[0159] in, Rewritten as , Rewritten as , Rewritten as Add SDP constraints , , .

[0160] Furthermore, due to Objective function and Fractional structures and rank-1 constraints in [the context of the text] nonconvexity, This is a non-convex problem. Similar to... The processing method uses SCA to make The objective function is approximated as The linear objective function makes Approximately Linear constraints. This is a convex optimization problem, which can be solved using the convex optimization toolbox. The optimal solution, which is considered as The The local solution of the next iteration is obtained when the iteration converges. The approximate optimal solution is obtained, that is, the approximate optimal solution for setting the reflection coefficient of the backscattering device. It is worth noting that... Equivalently transformed ,therefore The approximate optimal solution is also The approximate optimal solution.

[0161] After the central controller calculates the beamforming settings of the access point and backscattering device, the duration allocation strategy for each stage, and the reflection coefficient of the backscattering device, the calculation results of the central controller are sent to all backscattering devices via the access point.

[0162] Step S6: The cell-free coexisting radio network operates based on the calculation results.

[0163] In this embodiment, as Figure 3 As shown, the cell-free co-occurring wireless network operates in three phases within a time slot: the CSR (Co-occurrence) phase, the PSR (Parasite Relationship) phase, and the AC (Active Communication) phase. The operating time of each phase is determined by the time allocation strategy calculated by the central controller. During the CSR and PSR phases, the beamforming and reflection coefficient settings of the access point's backscattering devices are calculated by the central controller; the access point performs active communication, and the backscattering devices perform energy capture and backscattering communication. During the AC phase, the beamforming settings of the backscattering devices are calculated by the central controller; the access point remains silent, and the backscattering devices perform active communication.

[0164] Cellular-free coexisting wireless networks employ a reciprocal coexisting radio setup during the CSR phase, meaning the period of the backscattered signal is longer than the period of the main signal. In this phase, the access point sends the main signal to the receiver, and the backscattering device reflects the RF signal from the access point back to the receiver, superimposing the backscattered signal. The backscattering device simultaneously performs signal reflection and energy harvesting through energy splitting. The access point adjusts the gain and phase shift of each antenna based on calculated beamforming settings. Similarly, the backscattering device adjusts its impedance based on the reflection coefficient to achieve both signal transmission and energy harvesting.

[0165] Then, the cell-free co-occurring wireless network adopts a parasitic radio setting during the PSR phase, meaning the period of the backscattered signal equals the period of the main signal. The CSR setting favors the transmission of the main signal, while the PSR phase favors the transmission of the backscattered signal. Adjusting the duration of the two settings within a time slot allows for a hybrid CSR-PSR design. This balances the trade-off between maximizing the total backscattered network throughput and increasing the total main network throughput by optimizing the duration of the CSR and PSR phases from a time allocation perspective. 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 shift of each antenna based on the calculated beamforming settings. Similarly, the backscattering devices adjust their impedance based on the reflection coefficient settings to achieve signal transmission and energy harvesting.

[0166] During the AC phase, the throughput of the main network has met the predetermined value, and the access point remains silent, no longer sending main signals to the access point. The backscatter device consumes the energy collected during the CSR and PSR phases to transmit data to the receiver in an active communication manner. The backscatter device adjusts the gain and phase offset of each antenna according to the calculated beamforming settings.

[0167] During the CSR and PSR phases, all access points set up beamforming and transmit radio frequency (RF) signals to the receiver via a direct-link channel and a backscatter channel. The backscatter device sets up beamforming and reflection coefficients to reflect the RF signals from the access points to the receiver, while simultaneously performing energy capture. During the AC phase, the backscatter device sets up beamforming and consumes the energy captured in the CSR and PSR phases, actively transmitting RF signals to the receiver.

[0168] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A throughput optimization method for a cell-free coexisting radio network, characterized in that, Each time slot of the cell-free coexisting radio network includes a CSR phase, a PSR phase, and an AC phase. The throughput optimization method for the cell-free coexisting radio network includes: The access point sends a channel estimation control signal to the receiver, and after receiving the control signal, the receiver simultaneously sends an uplink pilot signal to all access points. After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimate and estimation error of the direct-link channel. The access point sends a channel estimation control signal to the backscattering device and the receiver, and the receiver sends an uplink pilot signal to all access points simultaneously through the backscattering device. After receiving the uplink pilot signal, the access point performs channel estimation and calculates the estimation of the backscatter channel and the estimation error. All access points upload the estimation and estimation error of the direct link channel and the estimation and estimation error of the backscatter channel to the central controller. The central controller uses the maximization of the backscatter communication throughput of the cellless co-occurrence radio network as the objective function to calculate the beamforming settings of the access points and backscatter devices, the duration allocation strategy of each stage, and the reflection coefficient settings of the backscatter devices. The non-cell coexisting radio network operates based on the calculation results.

2. The throughput optimization method for cell-free co-occurrence radio networks according to claim 1, characterized in that, The objective function is as follows: ； in, Indicates the throughput of backscatter communication; Indicating the CSR stage Beamforming vectors for each access point Indicates the first Beamforming of each access point during the CSR phase; Indicates the PSR stage Beamforming vectors for each access point Indicates the first Beamforming of each access point during the PSR phase; Indicates the AC phase Beamforming vector of a backscattering device Indicates the first Beamforming of a backscattering device in the AC phase; This indicates the time allocation strategy for the CSR, PSR, and AC phases. , This indicates the time allocation strategy for the CSR phase. This indicates the time allocation strategy for the PSR phase. This indicates the time allocation strategy for the AC phase; express The reflection coefficient settings for each backscattering device Indicates the first The reflection coefficient of a backscattering device; Indicates bandwidth. express and The multiple relationship between them , Indicates the symbol period of the main communication. The symbol period represents the period of backscatter communication; : indicates from the first The access point passes through the first Estimation of the backscatter link channel from the backscattering device to the receiver; Indicates from the first A backscattering device to the receiver channel; Indicates from the first The covariance matrix of the channel estimation error from each access point to the receiver; Indicates from the first The access point passes through the first The covariance matrix of the channel estimation error from each backscattering device to the receiver; This represents the power spectral density of Gaussian white noise.

3. The throughput optimization method for cell-free co-occurrence radio networks according to claim 2, characterized in that, The objective function also includes a main communication throughput constraint, which is a minimum requirement that the main network throughput is higher than the main network throughput.

4. The throughput optimization method for cell-free co-occurrence radio networks according to claim 2, characterized in that, The objective function also includes access point power constraints, namely, that the transmit power of each access point during the CSR or PSR phase is lower than the maximum transmit power.

5. The throughput optimization method for cell-free co-occurrence radio networks according to claim 2, characterized in that, The objective function also includes an energy constraint on the backscattering device, namely, the energy consumed by the backscattering device in the AC phase does not exceed the total energy collected in the CSR and PSR phases.

6. The throughput optimization method for cell-free co-occurrence radio networks according to claim 2, characterized in that, The objective function also includes reflection coefficient constraints, where each reflection coefficient is greater than or equal to 0 and less than or equal to 1.

7. The throughput optimization method for cell-free co-occurrence radio networks according to claim 2, characterized in that, The objective function also includes a time slot length constraint, where the durations of the CSR phase, PSR phase, and AC phase are all greater than 0, and their sum is less than or equal to the time slot duration.

8. The throughput optimization method for cell-free co-occurrence radio networks according to claim 1, characterized in that, The cell-free coexistence radio network operates based on calculation results, including: Based on the calculated duration allocation strategy for each stage, allocate the running time of the CSR stage, PSR stage, and AC stage in a time slot; In the CSR phase, a reciprocal radio setup is adopted, where the period of the backscattered signal is longer than the period of the main signal; the access point is set up with calculated beamforming, and the gain and phase offset of each antenna are adjusted; the backscattering device is set up with the reflection coefficient, and the impedance is adjusted to achieve signal transmission and energy harvesting. In the PSR phase, a parasitic radio setup is used, where the period of the backscattered signal is equal to the period of the main signal; the access point is set up according to the calculated beamforming setup, adjusting the gain and phase shift of each antenna; the backscattering device is set up according to the reflection coefficient, adjusting the impedance to achieve signal transmission and energy harvesting. During the AC phase, the access point remains silent, and the backscatter device transmits data to the receiver via active communication. The backscatter device adjusts the gain and phase shift of each antenna based on the calculated beamforming settings.

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