Interference-Aware Clustering Algorithms in Multi-relay Cellular Networks

Hae Sol Lee, Il Kim, Dong In Kim, Seokki Kim, Kwangae Lim
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引用次数: 1

Abstract

We consider the downlink of a wireless cellular network which consists of one Macro Base Station (MBS), multiple relays and User Equipments (UEs). In this scenario, we propose relay clustering algorithms to address the problem of inter-cluster interference. In each cluster, we adopt a time-division relaying scheme to avoid intra-cluster interference, but the inter-cluster interference still remains. In interference-aware network, an optimal clustering algorithm requires an exhaustive search, which is infeasible. Hence, we propose a clustering algorithm which improves the system capacity by exploiting the inter-cluster information. But this algorithm is implemented in a centralized manner with high complexity that requires the calculation of inter-cluster information. To circumvent this, we propose a cluster-wise distributed algorithm with manageable complexity, which shows the performance within acceptable range from the optimal one, far better than simple and intuitive algorithms because of the effect of inter-cluster interference.
多中继蜂窝网络中干扰感知聚类算法
我们考虑一个由一个宏基站(MBS)、多个中继和用户设备(ue)组成的无线蜂窝网络的下行链路。在这种情况下,我们提出中继聚类算法来解决簇间干扰问题。在每个集群中,我们采用时分中继方案来避免集群内干扰,但集群间的干扰仍然存在。在干扰感知网络中,最优聚类算法需要穷举搜索,这是不可行的。因此,我们提出了一种利用集群间信息来提高系统容量的聚类算法。但该算法实现集中,复杂度高,需要计算集群间信息。为了解决这一问题,我们提出了一种可管理复杂度的集群分布式算法,由于集群间干扰的影响,该算法的性能在最优算法的可接受范围内,远远优于简单直观的算法。
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