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Dynamic Clustering and User Association in Wireless Small Cell Networks with Social Considerations

机译:无线小蜂窝网络中的动态聚类和用户关联   与社会考虑

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摘要

In this paper, a novel social network-aware user association in wirelesssmall cell networks with underlaid device-to-device (D2D) communication isinvestigated. The proposed approach exploits social strategic relationshipsbetween user equipments (UEs) and their physical proximity to optimize theoverall network performance. This problem is formulated as a matching gamebetween UEs and their serving nodes (SNs) in which, an SN can be a small cellbase station (SCBS) or an important UE with D2D capabilities. The problem iscast as a many-to-one matching game in which UEs and SNs rank one another usingpreference relations that capture both the wireless aspects (i.e., receivedsignal strength, traffic load, etc.) and users' social ties (e.g., UE proximityand social distance). Due to the combinatorial nature of the network-wide UE-SNmatching, the problem is decomposed into a dynamic clustering problem in whichSCBSs are grouped into disjoint clusters based on mutual interference.Subsequently, an UE-SN matching game is carried out per cluster. The game underconsideration is shown to belong to a class of matching games withexternalities arising from interference and peer effects due to users socialdistance, enabling UEs and SNs to interact with one another until reaching astable matching. Simulation results show that the proposed social-aware userassociation approach yields significant performance gains, reaching up to 26%,24%, and 31% for 5-th, 50-th and 95-th percentiles for UE throughputs,respectively, as compared to the classical social-unaware baseline.
机译:在本文中,研究了具有底层设备到设备(D2D)通信的无线小型蜂窝网络中一种新型的社交网络感知用户关联。所提出的方法利用用户设备(UE)与其物理接近度之间的社会战略关系来优化整体网络性能。此问题被表述为UE与它们的服务节点(SN)之间的匹配游戏,其中SN可以是小型蜂窝基站(SCBS)或具有D2D功能的重要UE。该问题被广播为多对一匹配游戏,在该游戏中,UE和SN使用偏好关系相互排名,该偏好关系既捕获了无线方面(即,接收信号强度,流量负载等)又捕获了用户的社会纽带(例如,UE接近度和社会距离)。由于网络范围内UE-SN匹配的组合性质,该问题被分解为动态聚类问题,在该问题中,SCBS基于相互干扰被分为不相交的群集。欠考虑的游戏显示为属于一类匹配游戏,其外部性是由于用户社交距离引起的干扰和对等效应而引起的,从而使UE和SN可以相互交互直到达到稳定的匹配。仿真结果表明,所提出的具有社交意识的用户关联方法可显着提高性能,与之相比,UE吞吐量的第5,第50和第95个百分位数分别达到26%,24%和31%经典的社会意识基线。

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