Research On PAPR Reduction Algorithms Of Massive MIMO-OFDM System Based On ADMM

Since the massive multiple-input multiple-output(MIMO)-orthogonal frequency division multiplexing(OFDM)technology has higher communication rate,higher Frequency utilization,higher energy efficiency and higher reliability,it has become one of the key technologies in the next generation of communication systems.However,due to the use of OFDM technology,high peak-to-average power ratio(PAPR)occurs in massive MIMOOFDM system,which will affect the system's performance and greatly increase the hardware cost.Therefore,how to reduce the PAPR of massive MIMO-OFDM system has become one of the urgent problems in wireless communications to be solved.Therefore,we propose two methods to reduce PAPR in massive MIMO-OFDM systems.These two methods not only have low computational complexity,but also have better performance than the existing methods in PAPR reduction,bit error rate and out-of-band radiation suppression.Moreover we have proved their convergence performance.The main content and innovation of this thesis are as follows:1.This thesis introduces the causes of PAPR problem and the existing PAPR reduction methods in OFDM systems and massive MIMO-OFDM systems,and expounds the advantages and disadvantages of these methods.In addition,the system model of massive MIMO-OFDM is given,and the workflow of the whole system is introduced.Furthermore,we introduce the alternating direction multiplier method(ADMM),which is used to solve the optimization model.2.A PAPR reduction algorithm based on ADMM(ADMM-Based)with low complexity is proposed.We formulate a non-convex optimization model,which is based on minimizing data carrier distortion such that the constraints are placed on PAPR and the power of the free carriers.We exploit the ADMM technique to obtain the model's approximate optimal solution efficiently.It can be shown that the proposed ADMM-Based has low computational complexity.Moreover,as an optimization method,we can prove that when the algorithm is convergent,the optimized solution of the algorithm is some Karush-Kuhn-Tucker(KKT)point of the considered model.Furthermore,the simulation results show that the optimized signal obtained by ADMM-Based method has a small and constant PAPR value,and the method can achieve almost ideal bit error rate performance and can well inhibit out-of-band radiation.3.Based on the ADMM-Based algorithm,a relaxed PAPR reduction algorithm is proposed(ADMM-Relax).By introducing two auxiliary variables,we establish a relaxation optimization model and solve it by ADMM method.Due to the introduction of auxiliary variables,we can prove that the algorithm is convergent and can converge to the KKT point of the relaxation model.In addition,it can approach arbitrarily close to some KKT point of the original model if proper parameters are chosen.Moreover,the computational complexity of ADMM-Relax is the same as that of the ADMM-Based method.Furthermore,simulation results show that the optimized signal of ADMM-Relax also has a small and constant PAPR value.In addition,the bit error rate performance and out-of-band radiation performance of this method are better than the existing methods.