Research On Energy Efficiency Optimization Algorithms For Multi-user Massive MIMO System

Massive MIMO technology is the key technology of the future mobile communication system,and its energy efficiency becomes the hot research topic of green communication field.Aiming at the problems that the existing algorithms do not consider the effect of the other parameters in the massive MIMO system on energy efficiency,and only analyze the effect of the number of antennas on the energy efficiency,so two kinds of improved algorithms are proposed in this thesis.The specific contents are as follows:To solve the problem that the current algorithms only consider the effect of the number of the antennas at the base station on the energy efficiency,neglecting the other parameters in the massive MIMO system,an energy efficiency algorithm by jointly optimizing the number of antennas at base station and transmission power is proposed.The algorithm includes two steps.Firstly,according to the criterion of maximizing system energy efficiency,the objective function is established by jointly optimizing the number of antennas,antenna subset and transmission power in this thesis with utilizing the zero forcing precoding at the base station and using the new power consumption model.Secondly,to reduce the complexity of the combined optimization problem,a decomposition method is proposed to solve the objective function.At the beginning,the proposed antenna selection strategy is adopted to find the antenna subset,and then the problem is converted into a convex optimization problem,thus an adjusting strategy of transmission power is put forward to adjust the transmission power.Simulation results show that the proposed algorithm can improve the system energy efficiency effectively.Due to that the current energy efficiency algorithms are based on the small-scale fading channel model and do not consider the effect of the users on the energy efficiency,an energy efficiency algorithm is proposed in the thesis by jointly optimizing the number of antennas at base station and the number of users.The algorithm includes two steps.Firstly,the channel model including the large-scale and small-scale fading is established,and based the channel model,the closed-form expression is derived by using the maximum ration transmission precoding at the base station.And according to the characteristics of the expression,the objective function is established by jointly optimizing the number of antennas at base station,the subset of antennas,the number ofusers and the subset of users with satisfying the constraint condition.Secondly,a distribution optimization method is put forward to solve the combined optimization problem.The user selection strategy is proposed to get the the subset of the users,after that,the strategy is given to get the optimal number of antennas.The simulation results show that the proposed algorithm can effectively improve system energy efficiency and reduce the overhead of system.