Cell-free massive distributed antenna system (CF-MDAS) can further reduce the access distance between mobile stations (MSs) and remote access points (RAPs), which brings a lower propagation loss and higher multiplexing gain. However, the interference caused by the overlapping coverage areas of distributed RAPs will severely degrade the system performance in terms of the sum-rate. Since that clustering RAPs can mitigate the interference, in this paper, we investigate a novel clustering algorithm for a downlink CF-MDAS with the limited-capacity backhaul. To reduce the backhaul burden and mitigate interference effectively, a semidynamic bidirectional clustering algorithm based on the long-term channel state information (CSI) is proposed, which has a low computational complexity. Simulation results show that the proposed algorithm can efficiently achieve a higher sum-rate than that of the static clustering one, which is close to the curve obtained by dynamic clustering algorithm using the short-term CSI. Furthermore, the proposed algorithm always reveals a significant performance gain regardless of the size of the networks.

中文翻译：

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下行无小区大规模分布式天线系统的半动态双向聚类算法

无单元大规模分布式天线系统（CF-MDAS）可以进一步缩短移动台（MS）与远程接入点（RAP）之间的访问距离，从而带来更低的传播损耗和更高的复用增益。但是，由分布式RAP的覆盖区域重叠引起的干扰将严重影响系统的总和速率。由于该群集RAP可以减轻干扰，因此，本文针对具有有限容量回程的下行链路CF-MDAS研究了一种新颖的群集算法。为了减轻回程负担并有效减轻干扰，提出了一种基于长期信道状态信息（CSI）的半动态双向聚类算法，该算法计算复杂度较低。仿真结果表明，与静态聚类算法相比，该算法能有效地获得更高的求和率，与采用短期CSI的动态聚类算法获得的曲线接近。此外，无论网络的大小如何，所提出的算法始终可以显着提高性能。