Good neighbor distributed beam scheduling in coexisting multi-RAT networks

A. M. Kuzminskiy, P. Xiao, R. Tafazolli
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引用次数: 3

Abstract

Spectrum sharing and employing highly directional antennas in the mm-wave bands are considered among the key enablers for 5G networks. Conventional interference avoidance techniques like listen-before-talk (LBT) may not be efficient for such coexisting networks. In this paper, we address a coexistence mechanism by means of distributed beam scheduling with minimum cooperation between spectrum sharing subsystems without any direct data exchange between them. We extend a “Good Neighbor” (GN) principle initially developed for decentralized spectrum allocation to the distributed beam scheduling problem. To do that, we introduce relative performance targets, develop a GN beam scheduling algorithm, and demonstrate its efficiency in terms of performance/complexity trade off compared to that of the conventional selfish (SLF) and recently proposed distributed learning scheduling (DLS) solutions by means of simulations in highly directional antenna mm-wave scenarios.
共存多rat网络中的好邻居分布式波束调度
频谱共享和在毫米波频段使用高定向天线被认为是5G网络的关键推动因素。传统的干扰避免技术,如先听后说(LBT)可能对这种共存的网络并不有效。本文提出了一种分布式波束调度的共存机制,使频谱共享子系统之间的协作最小化,而不需要直接的数据交换。我们将最初用于分散频谱分配的“好邻居”(GN)原则扩展到分布式波束调度问题。为了做到这一点,我们引入了相对的性能目标,开发了一种GN波束调度算法,并通过在高定向天线毫米波场景下的模拟,与传统的自私(SLF)和最近提出的分布式学习调度(DLS)解决方案相比,展示了其在性能/复杂性权衡方面的效率。
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