基于差分的超密集异构网络用户关联问题匹配算法

Chunxia Su, Fang Ye, Shanya Cong, Yuan Tian
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引用次数: 0

摘要

为了满足物联网用户日益增长的高数据传输速率需求,超密集异构网络(HetNet)以其在增强小区覆盖和提高系统吞吐量方面的优异性能被引入。然而,超密集网络的复杂结构使得用户关联成为一个关键问题。因此,本文主要研究超密集网络中的用户关联问题,以实现系统吞吐量的最大化。然后提出了一种基于差异的匹配算法,该算法在多个物联网用户使用相同的低功耗点(LPPs)竞争访问机会时,考虑当前请求与下一个请求之间可实现的速率差异。仿真结果表明,与四种比较算法相比,该算法既能获得最高的系统总吞吐量,又能获得最佳的公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Difference Based Matching Algorithm for User Association Problem in Ultra-Dense Heterogeneous Networks
To meet the ever-increasing requirements of high data transmission rates by Internet of Things (IoT) users, ultradense heterogeneous network (HetNet) is introduced for its excellent performance in enhancing cell coverage and improving system throughput. However, the sophisticated structure in ultradense HetNet makes user association become a crucial problem. Thus, this paper focuses on the user association problem in ultradense HetNet, aiming at maximizing system throughput. Then a difference based matching algorithm is proposed, in which the achievable rate difference between the current request and the next request is taken into account when multiple IoT users compete for the access opportunity with the same low power points (LPPs). Simulation results show that the proposed algorithm can achieve both the highest system sum-throughput and the best fairness compared with the four comparison algorithms.
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