Energy-Spectral Efficiency Tradeoff Scheme Based On Rate Splitting In Next Generation Mobile Communication System

With the rise of mobile terminals and various multimedia applications,academia and industry have opened up the research and exploration of next generation mobile communication systems,which need to meet the requirements of low energy consumption,high spectral efficiency,low latency and high traffic density.However,the tradeoff between energy efficiency and spectral efficiency is essential to meet the growing demand for data traffic and to improve the spectral utilization of the mobile Internet,which inevitably leads to a significant increase in energy consumption and decreases the energy efficiency of the system.Therefore,many new multiple access technologies have been proposed.Among them,rate splitting multiple access(RSMA),a new multiple access scheme based on multi-user rate splitting(RS)has attracted the attention of many researchers.Specifically,the transmitter splits the user information into common and private parts when sending the user messages,and then the receivers are able to decode user messages with a soft bridge between the two extremes of fully decoding the interference and treating the interference as noise.RSMA is able to improve the energy efficiency(EE)and spectral efficiency(SE)of the system with its rate splitting and flexible interference handling.Meanwhile,reconfigurable intelligent surface(RIS)is a device composed of multiple sub-wavelength reflective elements with reconfigurable electromagnetic characteristics,which can improve the spectral efficiency and energy efficiency of the system by controlling the phase and amplitude of each reflective unit.In order to optimize the energy and spectral efficiency of the system,this thesis first constructs a transmission system assisted by RIS based on rate splitting,and studies the energy efficiency maximization problem of the system under the estimated channel state information,and then studies the energy-spectral efficiency tradeoff optimization problem based on rate splitting under the perfect and imperfect channel state information.The specific work of this thesis are as follows.1.This thesis investigates the energy efficiency problem in RIS-assisted communication systems based on estimated channel state information.In this thesis,an RSMA-based RIS-assisted transmission system is designed under the condition of estimated channel state information.A problem of maximizing the energy efficiency under the power constraint and the modulus constraint of the smart reflecting surface cell is presented.To solve this problem,in this thesis,the single ratio form of the objective function is first decoupled using fractional programming.Then the optimal power allocation coefficients and the phase shift matrix of the RIS are obtained by an alternating optimization method.The numerical simulation results show that the energy efficiency performance of the RIS-assisted communication system can be significantly improved by optimizing the RIS deployment location and the number of reflective elements.2.The Energy Efficient-Spectral Efficient(EE-SE)tradeoff optimization problem based on the RSMA in multi-cell mobile communication networks is studied.In order to maximize both energy efficiency and spectral efficiency in multi-cell downlink using RSMA,this thesis first proposes a joint optimization problem based on power and common rate allocation.Then,a weight factor is used to transform it into a tradeoff problem which with multiple ratios.Since the objective function of the reformulated single-objective optimization problem is still non-convex,this thesis uses a fractional programming approach to decouple the multi-ratio optimization objectives.In order to further optimize the EE-SE tradeoff problem,this thesis adopts an alternating optimization approach,this thesis first fixing the power and rate of the common message to solve the optimal private message power allocation scheme,using the Lagrangian method to find the optimal private power allocation coefficient.Then fixing the obtained private power to solve power allocation scheme of the common message,these two stages are iterated until the algorithm converges,so as to obtain the optimal multi-cell spectral efficiency and energy efficiency tradeoff.Finally,numerical simulations verify the effects of the number of users,transmission power of the base station,energy efficiency and spectral efficiency weighting factors on the optimization problem under perfect and imperfect channel state information,and prove the superiority of the proposed algorithm.