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Flexible Resource Allocation in 5G Ultra Dense Network with Self-backhaul

机译:灵活的资源分配在5G超密集网络中的自回式

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Self-backhaul is flexible and cost efficient for ultra dense network (UDN) since it provides backhaul using the same wireless technology as access link. Content prediction and caching can lower the load on backhaul and improve user experience. Therefore, an algorithm named tri-stage fairness (TSF) is proposed to solve the resource allocation problem in UDN with self-backhaul and caching, in which cells without direct network connection (rTP) access core network through donor TP (dTP). In TSF, rTP determines to transmit files cached in rTP (rTP files) or the files not cached in rTP (dTP files) according to delay and link capacity, and allocate access link resource using proportional fairness algorithm. dTP allocates backhaul resource among its users and rTPs with fairness considerations, and decides the time each rTP spends on backhaul link. Fairness, efficiency, overhead and complexity are jointly considered in TSF. To facilitate system level simulation, a traffic model considering the influence of caching is also introduced. Simulation results suggest flexible resource allocation between access and backhaul link yield substantial performance gain.
机译:自回程灵活且具有成本高的超密集网络(UDN),因为它提供了使用与访问链路相同的无线技术的回程。内容预测和缓存可以降低回程的负载并提高用户体验。因此,提出了一种名为三级公平性(TSF)的算法,以解决UDN的资源分配问题,具有自回程和高速缓存,其中通过捐赠TP(DTP)没有直接网络连接(RTP)访问核心网络的单元。在TSF中,RTP确定在RTP(RTP文件)中缓存的文件或在RTP(DTP文件)中未通过延迟和链路容量的文件,以及使用比例公平算法分配访问链接资源。 DTP在其用户和RTPS之间分配回程资源,具有公平考虑,并决定每个RTP在回程链路上花费的时间。在TSF中共同考虑公平,效率,开销和复杂性。为了便于系统级模拟,考虑到缓存的影响的交通模型也被引入。仿真结果表明,访问和回程链路之间的灵活资源分配产生了实质性的性能增益。

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