Massive MIMO下行系统能效资源分配算法

摘要

In order to decrease the carbon emission and operator expenditure induced by energy consumption of wireless communication networks,this paper proposed an algorithm for energy-efficient resource allocation scheme in massive MIMO communication system.It provided a convex optimization issue with the objective of maximizing system energy efficiency lower bound under the minimum required data rate,maximum required power of each user and tolerable interference level constraint,meanwhile the BS used a maximum rate transmitting (MRT) precoding.First,it proposed an iterative algorithm derived from optimality condition for bandwidth assignment.Second,according to the properties of fractional programming,the resulting energy-efficient optimization in the fractional form was transformed into subtractive form.Convex optimization was exploited to obtain the numbers of antennas and optimal transmit power of each user which lead to maximum energy efficiency.Simulation results show that the proposed schemes not only have less iteration number but also have good perform for system energy efficiency and throughput,at the same time,the performance of spectral-efficiency of the proposed algorithm is very well and the complexity is significantly reduced.%针对无线通信网耗能造成二氧化碳排放量和运营成本日益增加的问题,提出了一种下行大规模天线系统能效最优的资源分配算法.算法在基站端采用最大比合并(M RT)预编码的情况下,考虑各用户最小数据速率、最大发射功率和可容忍的干扰水平约束条件下,以最大化系统能效下界为准则建立非凸优化模型.首先采用一种迭代算法确定每个用户的带宽分配;然后根据分数规划的性质,将能效优化问题的分数形式转换为减数形式,进而利用凸优化方法求解基站端最优的发射天线数和发射功率来获得最优能效.仿真结果表明,所提算法能以较小的迭代次数收敛到最大能效值,并且有较好的系统频谱效率性能,同时算法复杂度得到了显著降低.