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ISSN 2095-9184 (print), ISSN 2095-9230 (online)

Interference coordination in full-duplex HetNet with large-scale antenna arrays

Abstract: Massive multiple-input multiple-output (MIMO), small cell, and full-duplex are promising techniques for future 5G communication systems, where interference has become the most challenging issue to be addressed. In this paper, we provide an interference coordination framework for a two-tier heterogeneous network (HetNet) that consists of a massive-MIMO enabled macro-cell base station (MBS) and a number of full-duplex small-cell base stations (SBSs). To suppress the interferences and maximize the throughput, the full-duplex mode of each SBS at the wireless backhaul link (i.e., in-band or out-of-band), which has a different impact on the interference pattern, should be carefully selected. To address this problem, we propose two centralized algorithms, a genetic algorithm (GEA) and a greedy algorithm (GRA). To sufficiently reduce the computational overhead of the MBS, a distributed graph coloring algorithm (DGCA) based on price is further proposed. Numerical results demonstrate that the proposed algorithms significantly improve the system throughput.

Key words: Massive MIMO, Full-duplex, Small cell, Wireless backhaul, Distributed algorithm

Chinese Summary  <445> 大规模天线阵列下全双工异构网络的干扰协调

概要:对于未来的第五代通信系统,干扰协调已经成为最具挑战性的问题,而大规模多输入多输出、小蜂窝和全双工技术均是在此背景下充满前景的技术。提出一个针对两层异构网络的干扰协调框架,该异构网络包含了一个装备大规模天线阵列的宏蜂窝基站和大量使用全双工技术的小蜂窝基站。因为带内全双工和带外全双工会产生不同的干扰模式,为了抑制干扰和最大化网络吞吐量,每个小蜂窝基站在无线回程链路的全双工模式都应慎重选择。为解决此模式选择问题,提出两种集中式算法,分别是遗传算法和贪心算法。此外,为了更充分降低宏蜂窝基站的计算开销,进一步提出一种基于代价的分布式图染色算法。仿真结果表明:提出的算法显著提高了系统吞吐量。

关键词组:大规模多输入多输出;全双工;小蜂窝;无线回程链路;分布式算法


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DOI:

10.1631/FITEE.1700047

CLC number:

TN929.5

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On-line Access:

2017-06-30

Received:

2017-01-15

Revision Accepted:

2017-04-06

Crosschecked:

2017-06-05

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