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Multiuser MIMO User Selection Based on L (2)-Hausdorff Distance with Block Diagonalization

机译:基于L(2)-Hausdorff距离的对角化多用户MIMO用户选择

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摘要

Block diagonalization (BD) is an important precoding method for multiuser multiple-input and multiple-output (MU-MIMO) broadcast channel (BC) systems. When the number of users is large, user selection (scheduling) should be performed so as to make full use of BD precoding. In this paper, based on -Hausdorff distance, we propose two novel user selection algorithms, namely GUS- and US-, for MU-MIMO BC systems with BD precoding to maximize the throughput. Both of the proposed algorithms select users iteratively and perform power allocation using the waterfilling method. In GUS-, -Hausdorff distance is used as a crucial factor for the user selection criterion. In US-, besides the criterion in GUS-, a similarity criterion based on -hausdorff distance is employed to reduce the cardinality of the candidate user set effectively. The complexities of the proposed algorithms are analyzed and compared with those of typical existing algorithms. Simulations have been carried out to verify the performance of the proposed algorithms. Numerical results suggest that the proposed algorithms outperform most of their rivals in terms of complexity and show competitive performance in throughput.
机译:块对角化(BD)是用于多用户多输入多输出(MU-MIMO)广播信道(BC)系统的重要预编码方法。当用户数量很大时,应该执行用户选择(调度),以便充分利用BD预编码。本文基于-Hausdorff距离,针对带有BD预编码的MU-MIMO BC系统,提出了两种新颖的用户选择算法,即GUS-和US-,以最大化吞吐量。两种提出的算法都迭代选择用户并使用注水方法执行功率分配。在GUS-中,-Hausdorff距离用作用户选择标准的关键因素。在US-中,除GUS-中的准则外,还采用基于-hausdorff距离的相似性准则来有效降低候选用户集的基数。分析了所提出算法的复杂性,并将其与典型的现有算法进行了比较。已经进行了仿真以验证所提出算法的性能。数值结果表明,所提出的算法在复杂性方面优于大多数竞争对手,并且在吞吐量方面显示出竞争性能。

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