Performance Optimization For Multi-user Simultaneous Wireless Information And Power Transfer Systems

With the development of the fifth generation mobile communication technology,the number of terminal devices and the scale of wireless communication systems continue to grow,and the demand for energy is increasing.However,the global energy shortage problem is becoming increasingly serious.How to reduce the energy consumption of communication system has become a key problem to be solved.Simultaneous Wireless Information and Power Transfer(SWIPT)integrates RF energy harvesting technology into the wireless communication systems,continuously provide energy to the energy limited devices to extend its battery life,and provide a new implementation solution for the realization of green communication.On the other hand,the specific performance requirements for the next generation wireless communication systems are: high data rate,low energy consumption,low latency and high connectivity and so on,and how to effectively improve the energy efficiency and spectral efficiency of the communication system become critical.Fortunately,researchers have proposed many effective solutions to the above challenges,such as non-orthogonal multiple access(NOMA),massive multiple input multiple output(MIMO)and millimeter Wave(mm Wave)communication technology.Hence,this thesis is dedicated to investigating the SWIPT system under the requirements of next generation wireless communication systems,combining with technologies such as NOMA,Massive MIMO and mm Wave,and optimizing the system resource allocation algorithm to improve the performance of the system.The main content and contributions are summarized as follows:(1)Optimize the resource allocation problem of the multi-user NOMA SWIPT system to maximize system security performance.Firstly,the multi-user NOMA SWIPT system based on multiple input single output(MISO)is constructed.To maximize the sum security rate(SSR)of the considered system,the resource allocation optimization problem is mathematically formulated with the constraints of the minimum data rate requirement of individual information user(IU)and the minimum harvest energy requirement of individual energy user(EU).The corresponding problem involves precoding and user power allocation,which is non-convex and difficult to solve directly.In order to tackle above problem,the precoding is optimized to maximize the channel gain of all IU based on the minimum harvest energy requirement of individual EU firstly,and then the original problem is simplified and transformed into a sequence of convex sub-problems which can be solved simultaneously.Hence,a closed-form solution of the optimal power allocation policy is derived based on the Karush-Kuhn-Tucker conditions.The simulation results verify the effectiveness of the proposed algorithm,and prove that the proposed resource allocation algorithm can improve system security.(2)Optimize the design algorithm of hybrid precoder and combiner in multi-user Massive MIMO SWIPT system to improve the spectrum efficiency.Firstly,the multi-user Massive MIMO SWIPT system based mm Wave communication is constructed,and the transceivers have adopted the hybrid analog/digital architecture to reduce the hardware complexity and energy consumption.To maximize the spectrum efficiency of the considered system,the problem of the design of analog precoder and combiner is mathematically formulated with the constraints of the total transmit power and the minimum harvest energy requirement of per energy user.Because of the constant-magnitude of analog precoding and the coupling of the hybrid precoding and combiners,we divide the joint optimization problem into the digital stage and analog stage and solve them sequentially.In particular,the greedy selection method based on the array response vectors is proposed in the analog stage.In the digital stage,we expand the objective function with first order Taylor expansion,and utilize an iterative algorithm to find the suboptimal digital precoder first,and then design the digital combiners based on Minimum Mean Square Error(MMSE)scheme.Finally,simulation results verify the effectiveness and robustness of the proposed algorithm.