多用户MIMO系统中的一种低复杂度用户选择算法

联合块对角化和几何均值分解(BD-GMD)是一种用于下行多用户多输入多输出(MU-MIMO)系统的预编码方案。在信噪比(SNR)较高的情况下,此方案在信道吞吐量和误符号率(SER)两方面都是渐进最优的。但是,在BD-GMD方案中,发射和接收天线的数量限制了能同时通信的用户数。在一个拥有大量用户的下行MU-MIMO系统中,为了使得系统总的吞吐量最大,基站必须从大量的用户中选出一个用户子集,同时对他们进行服务。采用穷尽搜索算法能得到最优的用户子集,但这种方法所需要的计算量太大。因此,提出了一种次最优但是计算复杂度较低的用户选择算法,用于采用BD-GMD方案的下行MU-MIMO系统。此算法具有随用户数变化的线性复杂度,另外,仿真结果显示,其总的吞吐量大致能达到采用穷尽搜索算法所获得的系统总吞吐量的95%。

Low complexity user selection algorithms for multi-user MIMO systems

The combined Block Diagonalization and Geometric Mean Decomposition(BD-GMD) is a precoding scheme that is asymptotically optimal for(moderately) high Signal-to-Noise Ratio(SNR) in terms of both channel throughput and the Symbol Error Rate(SER) performance in downlink Multi-User Multiple-Input-Multiple-Output(MU-MIMO) systems.The number of simultaneously supportable users 1with BD-GMD is limited by the number of transmitting and receiving antennas.In a downlink MU-MIMO system with a large number of users,the basestation may select a subset of users to serve in order to maximize the total throughput.The brute-force search for the optimal user set,however,is computationally prohibitive.We propose a low complexity suboptimal user selection algorithm for downlink MU-MIMO systems with BD-GMD.We show that the proposed algorithm has linear complexity in the number of users and achieves around 95% of the total throughput of the complete search method in simulations.