Research On Energy Efficiency Optimization In Large-scale MIMO Systems

Along with the rapid development of science and technology,wireless business is showing a flourishing and rapid development trend,and the pursuit of multimedia network gradually diversifies.High speed data transmission brings better and better user experience,while on the other hand the attendant environmental pollution and energy consumption become more and more serious.In response to the call of the green communication,the wireless communication system design has been transformed from the simple pursuit of high spectral efficiency(SE)to the minimum energy loss based on the satisfaction of Qo S(quality of service).Compared with traditional MIMO,the large-scale MIMO system can improve the spectral efficiency by the high diversity gain generated by the large antenna array.However,the more antennas and RF chains bring the greater power consumption.The effect of the increasing antenna on the channel capacity is small after it reaches to a certain value,but will reduce the energy efficiency.Therefore,it is very promising to study the maximization of the energy efficiency by adjusting the transmit power and the number of antennas in large scale MIMO system.This paper mainly studies the optimization of energy efficiency in large-scale MIMO systems.The main contents are as follows:An optimization model is proposed to maximize the transmit power and the number of antennas in order to maximize the energy efficiency.Considering the formulation of EE,this fractional programming problem can be converted to a non-fractional optimization problem,and the Dinkelbach method is proposed to deal with this problem.And the Dinkelbach method is compared with the traditional sequential search algorithm(SSA)and binary search algorithm(BSA).To start with,the EE optimization problem,i.e.finding the optimal EE-based values of each parameter,when the other one is fixed,is investigated.Then the optimization problem jointly considering these two parameters to maximize EE is studied.Moreover,the EE optimization problem is extended to multi-user system.Simulation results show that the EE can be improved with the proposed Dinkelbach method,and it has a faster convergence speed than the BSA and SSA without any performance loss for both single-user system and multi-user system.High rate and large capacity communication technology has been the focus of wireless communication research.SE is a classical measure of communication system,that is to say,the design of the traditional system focuses on the promotion of spectral efficiency.Obviously,high rate data transmission and high frequency wireless access technology mean high energy consumption.With the green communications proposed recently,the improvement of the energy efficiency has become a major focus of attention.In order to better balance EE and SE in wireless systems,it is necessary to study the tradeoffs between these two indicators.Firstly,a closed-form approximation of the EE-SE tradeoff is derived in large scale MIMO system.Based on the approximate EE-SE tradeoff,the EE-maximum system parameters can be obtained in closed form with the help of Lambert function.In addition,the pareto set is introduced for joint optimization of EE and SE,and then a multi-objective optimization problem is proposed to solve the EE-SE trade-off problem.With the help of Cobb-Douglas production model in economics,a unified EE-SE trade-off metric is derived to convert the multi-objective optimization problem into a single-objective one.Furthermore,the transmit power and the number of antennas corresponding to EE,SE and the EE-SE tradeoff metric are optimized analyzed.