CN113099461B - Symbiotic radio network design method based on non-orthogonal multiple access technology - Google Patents

Symbiotic radio network design method based on non-orthogonal multiple access technology Download PDF

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CN113099461B
CN113099461B CN202110355843.3A CN202110355843A CN113099461B CN 113099461 B CN113099461 B CN 113099461B CN 202110355843 A CN202110355843 A CN 202110355843A CN 113099461 B CN113099461 B CN 113099461B
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CN113099461A (en
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梁应敞
张荣海翔
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/345—Interference values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention belongs to the technical field of wireless communication, and particularly relates to a design method of a symbiotic radio network based on a non-orthogonal multiple access technology. Firstly, estimating the energy of all BD emission signals, and then carrying out cluster division on the BD by adopting a high-energy priority matching criterion; during data transmission, NOMA is adopted in the cluster, that is, all BD in the cluster can simultaneously transmit data in corresponding time slots, and TDMA is adopted among different clusters, that is, each time slot only allows one cluster to work; furthermore, an energy absorption method based on cluster mutual power supply is proposed, namely for the BD in other clusters, energy can be absorbed not only from the main signal transmitted by the base station but also from the signal reflected by the cluster currently transmitting. The invention has the advantages that the system performance is improved to a certain extent compared with the communication system performance adopting the traditional transmission protocol on the premise of ensuring low power consumption and high spectrum utilization rate.

Description

Symbiotic radio network design method based on non-orthogonal multiple access technology
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a design method of a Symbian Radio Network (SRN) based on non-orthogonal multiple access (NOMA) technology.
Background
In recent years, with the explosive growth of data in the information age, the Internet of Things (IoT) industry has been greatly developed, wherein the use of the Internet of Things on a large scale is becoming more and more frequent. In the large-scale internet of things, brand new and higher requirements are provided for precious resources such as energy, frequency spectrum and the like. However, the conventional wireless communication network generally has the problems of insufficient energy supply, low frequency spectrum utilization rate and the like, and the development step of the internet of things industry is slowed down to a certain extent, so that the development of the internet of things industry meets the unprecedented bottleneck. Therefore, technologies for introducing low power consumption and high spectrum utilization in the conventional wireless communication network are urgently needed, and the technologies can effectively alleviate the problems faced by the current internet of things industry. Among them, the ambient backscattering communication (AmBC) is a technology that has been developed rapidly in recent years, and has low power consumption and high spectrum utilization. In AmBC, a Backscatter Device (BD) can modulate its own information onto an existing ambient radio frequency signal and then reflect the modulated information to a receiver, which not only eliminates the need to configure a special radio frequency signal emission source for a communication system, but also eliminates the need to generate a radio frequency signal for the BD to transmit information, thereby reducing energy consumption. However, in the conventional AmBC, the signal strength of the environmental signal is much larger than that of the reflected signal, so that strong interference is brought to a receiver for demodulating the reflected signal, and the demodulation difficulty is increased. The emerging symbiotic radio technology (SR) provides a new idea for solving this problem. In SR, the primary communication process and the backscatter communication process are combined together, that is, the two communication processes share a primary receiver, and for the primary receiver, the primary signal and the reflected signal are demodulated by using serial interference cancellation technology, so that the strong interference caused by the environmental signal can be eliminated in the reflected signal demodulation process.
In addition, NOMA is also a technique to achieve high spectral utilization. Unlike Orthogonal Multiple Access (OMA), NOMA allows multiple devices to transmit on the same orthogonal resource block. Therefore, efficient combination of SR and NOMA provides the potential for a low-power, high-spectrum-utilization communication system of the internet of things.
Disclosure of Invention
Aiming at the problems of insufficient energy supply, low spectrum utilization rate and the like in the existing Internet of things, the SR technology and the NOMA technology are combined, a symbiotic radio communication network based on the non-orthogonal multiple access technology is designed, and the control of base station transmitting power (transmit power), BD energy reflection coefficients (power reflection coefficients) and transmission slot length (time slot duration) is considered, so that the performance of the whole system is optimized.
The present invention mainly focuses on SR-based internet of things networks, and designs a symbiotic radio communication network as shown in fig. 1. in the model under consideration, a communication system structure comprises a base station, a plurality of BDs and a main receiver, wherein the plurality of BDs are further divided into different clusters (clusters). Because the cluster division is involved, the invention designs a cluster division model based on energy group (power group). Specifically, in the training phase, the base station first transmits a signal, the BD modulates the signal after receiving the signal and reflects the modulated signal to the main receiver, and then the main receiver estimates the energy of the received signal. Since there are a plurality of BDs in the system, the above process is repeated by using Time Division Multiple Access (TDMA), i.e. the training phase is divided into a plurality of time slots, each time slot only allows one BD to operate, and different BDs complete the above process in their respective allocated time slots. After estimating the energy from all the BD reflected signals, the main receiver sequentially arranges in descending order (descending order) according to the estimated energy, divides the BD reflected signals into different energy subgroups according to the actual system specific parameters, and then selects corresponding BDs from the different energy subgroups to form clusters by adopting a high-energy priority matching criterion (head-to-head pairing scheme).
The technical scheme of the invention is as follows:
a design method of a symbiotic radio network based on a non-orthogonal multiple access technology comprises a base station, a plurality of backscattering devices and a main receiver, wherein the backscattering devices are in a full-duplex working mode; the design method is characterized by comprising the following steps:
the base station sends signals, the backscattering equipment modulates information of the backscattering equipment to the incident signals after receiving the signals and reflects the information to the main receiver, the main receiver estimates and measures energy of the reflected signals, after the estimation and measurement of the energy of the signals reflected by all the backscattering equipment are finished, the main receiver arranges the energy in a descending order according to energy intensity, the backscattering equipment is divided into a plurality of energy subgroups according to the ordering, and each energy subgroup comprises a plurality of backscattering equipment; and then selecting corresponding BD from different energy subgroups to form a cluster by adopting a high-energy priority matching criterion.
During data transmission, each transmission time slot only allows one cluster to communicate, all the backscatter devices in the same cluster simultaneously transmit data in the corresponding time slot, and the primary receiver receives and demodulates the received signal.
In the invention, based on the designed symbiotic radio communication system model, and considering the characteristics of different equipment access modes, namely that NOMA can improve the spectrum utilization rate but bring more interference, while OMA can reduce the mutual interference among signals but is not beneficial to the utilization of spectrum resources, a NOMA-plus-TDMA transmission protocol is designed. In particular, NOMA is used within a cluster, i.e. all BDs within the cluster can transmit data simultaneously in corresponding time slots, while TDMA is used between different clusters, i.e. only one cluster is allowed to operate per time slot.
In the present invention, a full-duplex BD, that is, a BD that can perform energy absorption using the remaining part of the incident signal while reflecting a part of the incident signal according to the energy reflection coefficient, is considered. Based on the energy absorption method, an energy absorption mode of mutual energy supply among clusters is designed, and a more practical energy causal constraint is designed. The energy absorption method for mutual energy supply among clusters means that, for BDs in other clusters, energy can be absorbed not only from the main signal transmitted by the base station but also from the signal reflected by the cluster currently transmitting. This energy absorption is designed for two reasons: in practice, the BDs exist in a dense mixture, and the transmission loss between the devices is relatively low; secondly, although the energy absorbed from the reflected signal is small, considering that the BD is a low power consumption energy-saving device, only a small amount of energy is needed to operate, and therefore, the absorbed energy also has a certain value. The energy causal constraint is that the energy absorbed by the BD after transmission cannot be used in the current transmission time slot, i.e. the BD can only absorb energy before and during transmission and achieve the corresponding energy absorption requirement.
The invention aims to improve the minimum throughput in a symbiotic radio communication network, and achieves the aim of improving the minimum throughput of a system by distributing the sending power of a base station, the BD energy reflection coefficient and the length of a transmission time slot, thereby further ensuring the fairness of communication among the BD and improving the communication performance of the whole system. Based on the optimization purpose, the invention designs an iterative optimization algorithm based on fast coordinated reduction (BCD) and Sequential Convex Approximation (SCA) technologies.
The invention has the advantages that SR and NOMA are combined, a symbiotic radio communication network based on the non-orthogonal multiple access technology is provided, and the system performance is improved to a certain extent compared with the performance of a communication system adopting a traditional transmission protocol on the premise of ensuring low power consumption and high spectrum utilization rate. The proposed optimization algorithm has the advantages of low complexity and high convergence speed.
Drawings
Figure 1 shows a symbiotic radio communication network system model and frame structure in the present invention;
FIG. 2 shows the flow of the optimization algorithm in the present invention;
FIG. 3 shows the optimization algorithm convergence behavior in the present invention;
FIG. 4 shows the performance of a system designed in the present invention and a comparison of the performance with a system using a conventional transport protocol;
fig. 5 shows the influence of the energy absorption mode based on cluster mutual-aid energy supply designed in the invention on the system performance.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
Fig. 1 shows a model of a co-existing radio communication system designed in the present invention, which includes a base station, a plurality of BDs, and a main receiver. The present invention considers BD to be in full duplex mode of operation, i.e. it can absorb energy from the rest of the incident signal while reflecting a portion of the incident signal. As can be seen from figure one, we further divide the BD into different clusters. Therefore, the invention provides a cluster division model based on an energy group, which is implemented specifically as follows: in the invention, supposing that MK BDs are arranged, in the training phase, a base station firstly sends signals, the BD modulates own information on the incident signals after receiving the signals and reflects the information to a main receiver, and the main receiver estimates and measures the energy of the reflected signals. Since there are multiple BDs, the above process will be performed in a TDMA transmission mode, i.e. each training time slot only allows one BD to operate with the same energy reflection coefficient. After estimating the measured energy of all BD reflected signals, the main receiver will be arranged in descending order according to the energy intensity and further divided into M energy subgroups, each containing K BDs. Based on the obtained energy subgroups, the invention selects corresponding BD from each energy subgroup to form a cluster by using a high-energy priority matching criterion. Thus, K clusters are available, each cluster containing M BDs.
In the present invention, all channels are block fading channels, and the block length is longer than the length of the system transmission frame structure, so it can be considered that the channel state information remains stable during the transmission. In the invention, all channels adopt Rayleigh fading channel model (Rayleigh fading channel model). As can be seen from the first figure, the invention uses hm,kDenotes the channel between the base station and the BD (m, k), where BD (m, k) denotes the m-th BD in the k-th cluster, denoted by fm.kTo representThe channel between the main receiver and the BD (m, k) is denoted by g.
According to a system model, the invention designs a mixed transmission protocol, namely NOMA-plus-TDMA transmission protocol based on a non-orthogonal multiple access technology. In particular, during the transmission phase, there are K transmission slots, each of which only allows one cluster to communicate, i.e. NOMA is used within a cluster, while TDMA is used between clusters. For example, in k time slot, the base station first sends a main signal, after receiving the main signal, the BD in the kth cluster modulates information to be transmitted to an incident signal, and then transmits the modulated signal to the main receiver, and in this process, the rest clusters are kept silent. Therefore, according to the above analysis, the frame structure of the present invention is shown in fig. one, and comprises two stages, i.e., a training stage and a transmission stage, wherein the training stage mainly performs channel estimation and cluster division, and the transmission stage communicates using the NOMA-plus-TDMA transmission protocol.
In the present invention, the transmission power of the base station at the k-th time slot is denoted as PkThe main signal transmitted in the nth attenuation block is sk(n) wherein sk(n) circularly symmetric complex Gaussian distribution (CSCG) obeying zero mean and unit variance. Thus, the received signal for BD (m, k) can be expressed as
Figure BDA0003003775670000041
Wherein z ism,k(n) denotes mean zero and variance σ2Complex gaussian noise. The invention records the energy reflection coefficient of BD (m, k) as alpham,k∈[0,1]I.e. representing alpha in the incident signalm,kIs partially reflected, and 1-alpham,kPart will be used for energy absorption. Therefore, the signal reflected by the BD (m, k) at the k-th time slot can be expressed as
Figure BDA0003003775670000051
Wherein c ism,k(n) represents information that the BD (m, k) itself needs to transmit, and follows CSCG distribution. The invention designs an energy absorption mode based on cluster mutual-aided energy supply, namely the BD in other clusters can not only obtain energy from a main signal from a base station, but also obtain energy from a signal reflected by a cluster which is currently transmitting. Therefore, based on this energy absorption manner and energy causal effect, the energy absorbed for BD (m, k) can be expressed as
Figure BDA0003003775670000052
The first part of energy comes from the cluster mutual aid, and the second part of energy and the third part of energy come from the main signal. τ denotes the transmission slot length, l(i,j),(m,k)Representing the channel between the BD [, ]m,kRepresenting the energy absorption probability. Therefore, the signal received by the primary receiver in the k-th time slot can be expressed as
Figure BDA0003003775670000053
Wherein wk(n) represents noise and the variance is σ2. Since the co-existing radio communication network is considered in the present invention, the primary receiver demodulates both the primary signal and the reflected signal. In the present invention, the main receiver utilizes the SIC technique for demodulation, and supposing that the SIC technique can be perfectly used, the demodulation sequence is to demodulate the main signal with stronger signal strength first, and then demodulate the reflected signals in sequence. Therefore, the throughput of the primary receiver and the throughput of the BD (m, k) in the k-th slot can be expressed as
Figure BDA0003003775670000054
Figure BDA0003003775670000055
The goal of the invention is to maximize the minimum throughput of the system, so the optimization problem can be expressed as
Figure BDA0003003775670000061
Where D represents the minimum throughput of the primary receiver and EminDenotes the lowest absorption energy, E, of the backscatter devicesumRepresenting the maximum transmission energy, P, of the base station during the whole operationpeakIndicating the maximum transmission power of the base station in each time slot. Fig. 2 shows the operation flow of the optimization algorithm designed in the present invention. The optimization algorithm designed by the invention is designed based on BCD and SCA technologies, firstly, because of more optimization variables, the BCD algorithm is used for dividing the optimization problem into a plurality of sub-problems to carry out iterative solution, and then the SCA technology is adopted for the sub-problems which cannot be directly solved according to the properties of the sub-problems. The specific analysis is as follows:
firstly, the transmission power P of a base station is given in the t-th iterationtAnd BD energy reflection coefficient αtThe following sub-problems can be obtained by optimally allocating the transmission time slot length:
Figure BDA0003003775670000062
the optimization problem is a typical linear programming problem and can be solved directly by using a convex optimization tool CVX. Again, given the length of the transmission slot τtAnd base station transmission power PtThe optimal distribution of the BD energy reflection coefficients can result in the following sub-problems:
Figure BDA0003003775670000071
in the optimization problem, the objective function is not a concave function when the energy reflection coefficient is optimally distributed, and the first constraint condition is not a convex constraint when the energy reflection coefficient is optimally distributed, so that the convex optimization tool cannot be directly used for solving the optimization problem. We therefore used SCA technology to transform the above problems. The basic idea of the SCA technique is to optimize the target lower bound during each iteration. The above optimization problem can therefore be approximated as the following:
Figure BDA0003003775670000072
wherein
Figure BDA0003003775670000073
And
Figure BDA0003003775670000074
are respectively represented as
Figure BDA0003003775670000075
Figure BDA0003003775670000076
The above approximation problem is a convex optimization problem that can be solved using the traditional convex optimization tool CVX. Finally, the length of the transmission slot τ is giventAnd BD energy reflection coefficient αtThe following sub-problems can be obtained by performing optimal allocation on the base station transmission power:
Figure BDA0003003775670000081
similarly, the sub-problem in (13) has respective limitations in optimizing the transmission power of the base station due to the objective function and the first constraint condition, and cannot be directly solved. In this regard, the SCA technique is still employed and the following approximation sub-problem can be obtained:
Figure BDA0003003775670000082
wherein
Figure BDA0003003775670000083
And
Figure BDA0003003775670000084
are respectively represented as
Figure BDA0003003775670000085
Figure BDA0003003775670000086
The above approximation problem is a convex optimization problem that can be solved using the traditional convex optimization tool CVX. Therefore, the optimization algorithm based on BCD and SCA technologies is designed, and the original problem is solved by respectively carrying out iteration solving on the three subproblems (8), (10) and (14), so that the invention target is realized. Fig. 2 shows the flow of the overall optimization algorithm.
Fig. 3 shows the convergence behavior of the optimization algorithm designed by the present invention. As can be seen from FIG. 3, the optimization algorithm designed by the invention reaches convergence after approximately 5 iterations, which shows that the optimization algorithm has high convergence speed and certain superiority and use value.
Fig. 4 shows the performance of a system designed by the present invention and the performance comparison with a system using a conventional transmission protocol. For comparison, the performance of two conventional transmission protocols, namely conventional NOMA and TDMA, is shown, wherein the conventional NOMA is that all BDs in the system transmit in the same time slot, and the TDMA is that the BDs in the system transmit in different time slots respectively. We can first find out from fig. 4 that the throughput in designing a system increases with the increase of the communication signal-to-noise ratio. Secondly, we can find that the fairness of communication of the BDs in the design system is guaranteed, that is, the throughput achieved by the BD with poor channel condition is almost the same as the throughput achieved by the BD with good channel condition. Furthermore, we can find that the total throughput of the system adopting the NOMA-plus-TDMA transmission protocol designed by the invention is improved to a certain extent compared with the total throughput of the system adopting the traditional NOMA and TDMA transmission protocols, wherein the reasons are as follows: compared with the traditional NOMA, the NOMA-plus-TDMA transmission protocol provided by the invention can reduce the interference when the main receiver demodulates signals to a certain extent; compared with the TDMA, the NOMA-plus-TDMA transmission protocol provided by the invention can increase the accessible time resource of each BD to a certain extent.
Fig. 5 shows the influence of the energy absorption mode based on cluster mutual-aid energy supply designed by the invention. As can be seen from fig. 5, the cluster mutual assist power supply can improve the system performance to some extent, mainly because the energy loss due to the channel condition can be alleviated to some extent for the BD with low power consumption by the cluster mutual assist power supply.

Claims (1)

1. A design method of a symbiotic radio network based on a non-orthogonal multiple access technology comprises a base station, a plurality of backscattering devices and a main receiver, wherein the backscattering devices are in a full-duplex working mode; the design method is characterized by comprising the following steps:
the base station sends signals, the backscatter devices modulate own information on incident signals after receiving the signals and reflect the signals to the main receiver, the main receiver estimates and measures the energy of the reflected signals, after the estimation and measurement of the energy of the signals reflected by all the backscatter devices are finished, the main receiver arranges the energy in a descending order according to the energy intensity, the backscatter devices are divided into a plurality of energy subgroups according to the ordering, and each energy subgroup comprises a plurality of backscatter devices; then selecting corresponding backscattering equipment from different energy groups to form a cluster based on a high-energy priority matching criterion;
during data transmission, each transmission time slot only allows one cluster to communicate, all backscattering equipment in the same cluster simultaneously transmits data in the corresponding time slot, and a main receiver receives and demodulates received signals;
specifically, the method comprises the following steps: supposing that MK backscattering devices are arranged and are divided into M clusters, each cluster comprises K backscattering devices, and the transmission power of a base station in the K time slot is PkThe main signal transmitted in the nth attenuation block is sk(n), then the signal received by the mth backscatter device of the kth cluster is:
Figure FDA0003501704450000011
wherein h ism,kIs the channel between the base station and the mth backscatter device of the kth cluster, zm,k(n) denotes mean zero and variance σ2Complex gaussian noise of (a);
let the energy reflection coefficient of the m-th backscatter device of the k-th cluster be denoted as αm,k∈[0,1]I.e. representing alpha in the incident signalm,kIs partially reflected, and 1-alpham,kPart of the signal will be used for energy absorption, so the signal reflected by the mth backscatter device of the kth cluster at the kth time slot is:
Figure FDA0003501704450000012
wherein c ism,k(n) represents the information which needs to be transmitted by the mth backscatter device of the kth cluster;
let the backscatter devices in the other clusters extract energy not only from the primary signal from the base station, but also from the reflected signal from the cluster currently being transmitted, so the energy absorbed by the mth backscatter device for the kth cluster is:
Figure FDA0003501704450000021
wherein eta ism,kRepresenting the probability of energy absorption,/(i,j),(m,k)Denotes the channel between the backscatter devices, τ denotes the transmission slot length;
the signal received by the primary receiver in the k time slot is:
Figure FDA0003501704450000022
wherein, wk(n) represents noise, fm,kRepresents the channel between the primary receiver and the mth backscatter device of the kth cluster, and g represents the channel between the base station and the primary receiver; after receiving the signal, the main receiver demodulates by using the SIC technology;
the optimization method of the base station sending power, the energy reflection coefficient of the backscattering equipment and the transmission time slot length comprises the following steps: aiming at maximizing the minimum throughput of the system, an optimization problem is established as follows:
Figure FDA0003501704450000023
Figure FDA0003501704450000024
Figure FDA0003501704450000025
Figure FDA0003501704450000026
Figure FDA0003501704450000027
Figure FDA0003501704450000028
Figure FDA0003501704450000029
wherein R iskFor the throughput of the primary receiver in the k-th slot:
Figure FDA00035017044500000210
wherein sigma2Represents the variance of the noise at the primary receiver, and Rm,kThroughput for the mth backscatter device of the kth cluster:
Figure FDA0003501704450000031
in addition, in the above optimization problem, the physical meaning of the remaining parameters is as follows: d represents the minimum throughput of the primary receiver, EminDenotes the lowest absorption energy, E, of the backscatter devicesumRepresenting the maximum transmission energy, P, of the base station during the whole operationpeakRepresenting the maximum transmission power of the base station in each time slot;
adopting a BCD algorithm to divide the optimization problem into a plurality of sub-problems for iterative solution, specifically:
1) given base station transmission power P at the t-th iterationtAnd the energy reflection coefficient alpha of the backscatter devicetAnd optimally allocating the length of the transmission time slot to obtain the following sub-problems:
Figure FDA0003501704450000032
Figure FDA0003501704450000033
Figure FDA0003501704450000034
Figure FDA0003501704450000035
Figure FDA0003501704450000036
solving through a convex optimization tool CVX to obtain an optimized transmission time slot length;
2) given transmission slot length tautAnd base station transmission power PtAnd optimally distributing the energy reflection coefficients of the backscattering equipment to obtain the following sub-problems:
Figure FDA0003501704450000037
Figure FDA0003501704450000038
Figure FDA0003501704450000039
Figure FDA00035017044500000310
the SCA technology is adopted to convert the problems into that:
Figure FDA0003501704450000041
Figure FDA0003501704450000042
Figure FDA0003501704450000043
Figure FDA0003501704450000044
wherein
Figure FDA0003501704450000045
And
Figure FDA0003501704450000046
respectively expressed as:
Figure FDA0003501704450000047
Figure FDA0003501704450000048
solving through a convex optimization tool CVX to obtain an optimized energy reflection coefficient of the backscattering equipment;
3) given transmission slot length tautAnd BD energy reflection coefficient αtAnd optimally distributing the base station transmitting power to obtain the following sub-problems:
Figure FDA0003501704450000049
Figure FDA00035017044500000410
Figure FDA00035017044500000411
Figure FDA00035017044500000412
Figure FDA00035017044500000413
the SCA technology is adopted to convert the problems into that:
Figure FDA0003501704450000051
Figure FDA0003501704450000052
Figure FDA0003501704450000053
Figure FDA0003501704450000054
Figure FDA0003501704450000055
wherein
Figure FDA0003501704450000056
And
Figure FDA0003501704450000057
respectively expressed as:
Figure FDA0003501704450000058
Figure FDA0003501704450000059
and solving by a convex optimization tool CVX to obtain the optimized base station transmitting power.
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