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Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems

机译:基于交换波束的多用户大规模MIMO系统的低复杂度波束分配

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摘要

This paper addresses the beam allocation problem in a switched-beam based massive multiple-input-multiple-output (MIMO) system working at the millimeter wave (mmWave) frequency band, with the target of maximizing the sum data rate. This beam allocation problem can be formulated as a combinatorial optimization problem under two constraints that each user uses at most one beam for its data transmission and each beam serves at most one user. The brute-force search is a straightforward method to solve this optimization problem. However, for a massive MIMO system with a large number of beams N, the brute-force search results in intractable complexity O(NK), where K is the number of users. In this paper, in order to solve the beam allocation problem with affordable complexity, a suboptimal low-complexity beam allocation (LBA) algorithm is developed based on submodular optimization theory, which has been shown to be a powerful tool for solving combinatorial optimization problems. Simulation results show that our proposed LBA algorithm achieves nearly optimal sum data rate with complexity O(K logN). Furthermore, the average service ratio, i.e., the ratio of the number of users being served to the total number of users, is theoretically analyzed and derived as an explicit function of the ratio N=K.
机译:本文旨在解决在毫米波(mmWave)频段工作的基于开关光束的大规模多输入多输出(MIMO)系统中的波束分配问题,其目标是最大化总数据速率。可以在两个约束条件下将此波束分配问题公式化为组合优化问题,这两个约束条件是每个用户最多使用一个波束进行数据传输,每个波束最多为一个用户服务。蛮力搜索是解决此优化问题的直接方法。但是,对于具有大量波束N的大规模MIMO系统,强力搜索会导致难以解决的复杂度O(NK),其中K是用户数。为了解决复杂度适中的波束分配问题,基于亚模优化理论开发了次优低复杂度波束分配算法,该算法已被证明是解决组合优化问题的有力工具。仿真结果表明,本文提出的LBA算法在复杂度为O(K logN)的情况下达到了接近最优的总数据速率。此外,理论上分析平均服务比率,即,服务的用户数目与用户总数的比率,并将其作为比率N = K的明确函数。

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