基于HetNets用户关联优化的纳什议价方案

Dantong Liu, Yue Chen, K. K. Chai, Tiankui Zhang
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引用次数: 25

摘要

本文提出了一种异构网络(HetNets)的公平用户关联方案,其中用户关联优化被描述为纳什议价问题。优化目标是在用户最小速率约束下,考虑用户公平性和不同层单元间的负载均衡,使速率相关效用总和最大化。采用纳什议价方案和联盟方案求解该优化问题。首先,提出了一种针对两个基站进行用户关联议价的双机议价方案。然后利用匈牙利算法将该二人方案扩展为多人议价方案,该算法将BSs最优分组成对。仿真结果表明,该方案可以有效地将用户从宏单元中剥离出来,提高用户公平性,并且与不考虑用户公平性的最大化和率方案相比,可以获得相当的和率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nash bargaining solution based user association optimization in HetNets
In this paper, a fair user association scheme is proposed for heterogeneous networks (HetNets), where the user association optimization is formulated as a Nash bargaining problem. The optimization objective is to maximize the sum of rate related utility, under users' minimal rate constrains, while considering user fairness and load balance between cells in different tiers. Nash bargaining solution and coalition are adopted to solve this optimization problem. Firstly, a two-player bargaining scheme is developed for two base stations (BSs) to bargain user association. Then this two-player scheme is extended to a multi-player bargaining scheme with the aid of Hungarian algorithm that optimally groups BSs into pairs. Simulation results show that the proposed scheme can effectively offload users from macrocells, improve user fairness, and also achieve comparable sum rate to the scheme that maximizes the sum rate without considering user fairness.
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