Research On Mutualistic Transmission Theory And Resource Allocation Method In Cognitive Backscatter Communications

With the extensive deployment of the fifth generation mobile communication networks,a large number of new services and applications such as augmented reality,Internet of Things,and Industrial Internet are developing rapidly,which makes the wireless data traffic and the number of mobile devices in exponential growth.This puts forward higher requirements for the spectrum efficiency and energy efficiency of mobile communications.Cognitive backscatter communication is an emerging technology that can effectively improve spectrum efficiency and reduce energy consumption.It is expected to meet the application requirements of huge traffic and massive connections in future mobile communication.Cognitive backscatter communication is composed of the primary system and the secondary system,in which the secondary system uses the radio frequency signal of the primary system to conduct the passive backscatter transmission,and thus the communication power consumption of the secondary system can be greatly reduced.Meanwhile,the introduction of the secondary system provides additional multipath components for the primary system,so that the performance of the primary system is expected to be improved.Such a transmission in which both primary and secondary systems can achieve benefits is called a mutualistic transmission.However,the setting of secondary transmission parameters can affect the relationship between the primary and secondary systems.Meanwhile,the backscatter link signal suffers from double fading and thus is weak,which limits the performance of the secondary system and the gain of the primary system.For the above two key problems,this dissertation is dedicated to the research on mutualistic transmission theory and resource allocation method in cognitive backscatter communications by exploring the mutualistic relationship between the primary and secondary systems and enhancing the strength of the backscatter link.This dissertation is mainly composed of four research contents,including(1)receiver design in cognitive backscatter communication;(2)mutualistic condition between the primary and secondary systems in cognitive backscatter communication;(3)The joint beamforming design of a reconfigurable intelligent surface(RIS)-based multi-input single-output(MISO)cognitive backscatter communication system;(4)The joint beamforming design of an RISbased multiple-input multiple-output(MIMO)cognitive backscatter communication system.The specific research works are summarized as follows:Firstly,the receiver design of the cognitive backscatter communication is studied.When the secondary system only knows its pilot information but not the pilot information of the primary system,the traditional method uses an incoherent detector to detect the secondary signal,which degrades the detection performance significantly due to the effect of the strong direct link interference.To improve the detection performance of the secondary system,a data-driven clustering receiver is investigated by using the machine learning method.Specifically,the secondary transmitter transmits two known labels before data transmission,while the secondary receiver first clusters the received signals,and then uses the two known labels to match the clustering categories with the data symbols to recover the symbols of the secondary system.By exploring the received signal constellation information,a modulation-constrained expectation-maximization clustering algorithm is proposed,based on which the clustering receiver is designed.Simulation results show that the designed clustering receiver can achieve comparable performance as the maximum-likelihood detector with the perfect channel state information.Secondly,the mutualistic condition between the primary and secondary systems in cognitive backscatter communication is studied.Since the setting of the secondary transmission parameters will affect the relationship between the primary and secondary systems,to achieve mutualistic transmission,this dissertation theoretically deduces the transmission condition through which the two systems can benefit each other.Specifically,this dissertation first analyzes the bit error rate performance of primary and secondary systems under the maximum-likelihood detection with the help of probability and statistics theory,from which this dissertation finds that the symbol period ratio between the primary and secondary systems is an important parameter.Then,the mathematical model of the mutualistic transmission is established,and the critical point that the secondary system can bring performance gain to the primary system is deduced.Finally,the expression of the mutualistic condition is obtained.The results show that when the signal-to-noise-ratio(SNR)of the direct link is high enough and the signal-period ratio of the primary and secondary systems is large enough,the equivalent average SNR of the primary system is equal to the sum of the average SNR of the direct link and the average SNR of the backscatter link.When the number of the receiver antennas is large enough,the mutualistic condition between primary and secondary systems is not related to the instantaneous channel response but determined by the average SNR of the direct link and the backscatter link.Further,this dissertation studies the joint beamforming design in the RIS-based MISO cognitive backscatter communication.RIS is an artificial metasurface containing a large number of reflective elements,which can effectively increase the strength of the receiver signal through passive beamforming.In this dissertation,RIS is introduced into a cognitive backscatter communication system to enhance the signal strength of the backscatter link while acting as a secondary transmitter to transmit messages.For the MISO case,two kinds of joint beamforming schemes are proposed to maximize the transmission rate of the secondary system subject to the primary transmission rate constraint.Specifically,both proposed schemes decompose the formulated problem into several subproblems.One scheme uses Lagrange dual algorithm to solve each subproblem.The other scheme uses low complexity heuristic algorithm to solve each subproblem.Then,the performance gain brought by RIS for the cognitive backscatter communication system is analyzed theoretically.Finally,the simulation results show that when RIS acts as the secondary transmitter,the signal strength of the backscatter link can be greatly enhanced,and the performance of the primary and secondary systems can be greatly improved.Finally,this dissertation studies the joint beamforming design in the RIS-based MIMO cognitive backscatter communication.Based on the previous research work,the MISO scenario is extended to the MIMO scenario to further improve the spectrum efficiency.Firstly,the achievable rates of both primary and secondary systems are derived,and the beamforming matrix of the primary and secondary systems is designed jointly to minimize the total transmit power of the primary system subject to performance constraints for both primary and secondary transmissions.Two joint beamforming design schemes are proposed in the RIS-based MIMO cognitive backscatter communication.One scheme is based on the alternating optimization algorithm,which decouples the original problem into a series of subproblems and then iteratively solves them by the matrix theory and convex theory.The other scheme is based low-complexity algorithm,which solves a backscatter link enhancement problem to design the reflecting coefficient matrix.Then,theoretical analysis is performed by using the random matrix theory to reveal the performance gain introduced by the secondary system.Finally,the simulation results show that the introduction of RIS can effectively balance the channel gains for the multiple spatial data streams and greatly reduce the transmit power of the primary system.