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Efficient Low-Complexity Antenna Selection Algorithms in Multi-User Massive MIMO Systems With Matched Filter Precoding
IEEE Transactions on Vehicular Technology ( IF 6.1 ) Pub Date : 2020-01-14 , DOI: 10.1109/tvt.2020.2966565
Zaid Abdullah , Charalampos C. Tsimenidis , Gaojie Chen , Martin Johnston , Jonathon A. Chambers

In this work, two efficient low complexity Antenna Selection (AS) algorithms are proposed for downlink Multi-User (MU) Massive Multiple-Input Multiple-Output (M-MIMO) systems with Matched Filter (MF) precoding. Both algorithms avoid vector multiplications during the iterative selection procedure to reduce complexity. Considering a system with N antennas at the Base Station (BS) serving K single-antenna users in the same time-frequency resources, the first algorithm divides the available antennas into K groups, with the kth group containing the N/K antennas that have the maximum channel norms for the kth user. Therefore, the Signal-to-Interference plus Noise Ratio (SINR) for the kth user can be maximized by selecting a subset of the antennas from only the kth group, thereby resulting in a search space reduction by a factor of K. The second algorithm is a semiblind interference rejection method that relies only on the signs of the interference terms, and at each iteration the antenna that rejects the maximum number of interference terms will be selected. The performance of our proposed methods is evaluated under perfect and imperfect Channel State Information (CSI) and compared with other low complexity AS schemes in terms of the achievable sum rate as well as the energy efficiency. In particular, when the Signal-to-Noise Ratio (SNR) is 10 dB, and for a system with 20 MHz of bandwidth, the proposed methods outperform the case where all the antennas are employed by 108.8 and 49.2 Mbps for the first and second proposed algorithms, respectively, given that the BS has perfect CSI knowledge and is equipped with 256 antennas, out of which 64 are selected to serve 8 single-antenna users.

中文翻译:


具有匹配滤波器预编码的多用户大规模 MIMO 系统中高效、低复杂度的天线选择算法



在这项工作中,提出了两种有效的低复杂度天线选择(AS)算法,用于具有匹配滤波器(MF)预编码的下行链路多用户(MU)大规模多输入多输出(M-MIMO)系统。两种算法在迭代选择过程中都避免了向量乘法,以降低复杂性。考虑到基站(BS)具有 N 个天线的系统,在相同的时频资源中为 K 个单天线用户提供服务,第一个算法将可用天线分为 K 组,其中第 k 组包含具有以下功能的 N/K 个天线:第 k 个用户的最大信道规范。因此,可以通过仅从第 k 组中选择天线子集来最大化第 k 个用户的信号干扰加噪声比 (SINR),从而导致搜索空间减少 K 倍。第二种算法是一种半盲干扰抑制方法,仅依赖于干扰项的符号,并且在每次迭代时将选择抑制最大数量的干扰项的天线。我们提出的方法的性能在完美和不完美的信道状态信息(CSI)下进行评估,并在可实现的总速率以及能量效率方面与其他低复杂度AS方案进行比较。特别是,当信噪比 (SNR) 为 10 dB 且带宽为 20 MHz 的系统时,所提出的方法优于使用所有天线的情况,第一和第二个天线的速度为 108.8 和 49.2 Mbps考虑到BS具有完善的CSI知识并配备256个天线,其中选择64个天线来服务8个单天线用户,分别提出了算法。
更新日期:2020-01-14
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