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在多基站多用户MIMO系统中,最大化和速率(maximizing sum-rate,MSR)预编码是一种线性预编码,但是无闭式解.本文提出了一种交替迭代结构的准最大化和速率(Quasi-MSR)预编码方案来逼近MSR,将MSR的求解问题转化成最大化二次分式函数的乘积,并且设计了一种单接收天线用户环境下基于最大化和速率准则的低复杂度交替网格搜索功率分配(alternating grid search power allocation,AGSPA)方案.在此基础上,本文又提出了基于Quasi-MSR和低复杂度AGSPA的双层交替迭代结构(alternating iterative structure,AIS).仿真结果表明:考虑大尺度衰落和天线相关性时,AIS结构在和速率性能上明显优于4种典型的预编码算法(最大化信泄噪比、块对角化、最小均方误差与速率最大化).
In multi-base station multi-user MIMO systems, the maximizing sum-rate (MSR) precoding is a kind of linear precoding but without closed solutions.In this paper, we propose a quasi-maximization and rate- (Quasi-MSR) pre-coding scheme to approximate MSR, the problem of solving MSR is transformed into the product of maximizing quadratic fraction function, and a low complexity based on maximization and rate criterion is designed in the single receiving antenna user environment On the basis of this, an alternating iterative structure (AIS) based on Quasi-MSR and AGSPA with low complexity is proposed in this paper. The simulation is based on the alternating grid search power allocation (AGSPA) The results show that, considering the large-scale fading and the antenna correlation, the AIS structure is superior to the 4 typical precoding algorithms in terms of the rate performance (maximizing SNR, block diagonalization, minimum mean square error and maximum rate Change).