A Decentralized Framework for Dynamic Downlink Base Station Cooperation

Sheng Zhou, Jie Gong, Z. Niu, Yunjian Jia, Peng Yang
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引用次数: 40

Abstract

Multiple Base Station (Multi-BS) cooperation has been considered as a promising mechanism to suppress co-channel interference and boost the capacity for cellular networks. However, the large feedback and signaling overhead hinder it from practice. Therefore, limited cooperation among BSs is recognized as a good tradeoff between the performance gain and the relevant cost. In this paper, the whole network is divided into small disjointing BS cooperation groups, namely, clusters. A decentralized framework is proposed to facilitate the BS cluster formation on the downlink, in order to maximize the sum-rate of the scheduled mobile stations (MSs) under the cluster size constraint. Moreover, an efficient BS negotiation algorithm is designed for cluster formation, of which the feedback overhead per MS is irrelevant to the network size, and the number of iteration rounds scales very slowly with the network size. Simulations show that our strategy leads to significant sum-rate gain over static clustering and performs almost the same as the centralized greedy approach. With its low signaling overhead and complexity, the proposed framework is well suited for implementation in large-scale cellular networks.
一种分散的动态下行基站合作框架
多基站(Multi-BS)合作被认为是抑制同信道干扰和提高蜂窝网络容量的一种很有前途的机制。然而,大量的反馈和信号开销阻碍了它的实践。因此,BSs之间的有限合作被认为是性能增益和相关成本之间的良好权衡。本文将整个网络划分为相互脱节的小型BS合作组,即集群。为了在集群规模约束下最大化调度移动站(MSs)的总速率,提出了一种促进下行链路上BS集群形成的去中心化框架。设计了一种高效的聚类协商算法,该算法每MS的反馈开销与网络规模无关,迭代轮数随网络规模的增长缓慢。仿真表明,我们的策略比静态聚类具有显著的和速率增益,并且性能与集中式贪婪方法几乎相同。该框架具有较低的信号开销和复杂性,适合在大规模蜂窝网络中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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