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Traffic-Aware Multiple Association in Ultradense Networks: A State-Based Potential Game
IEEE Systems Journal ( IF 4.4 ) Pub Date : 2020-05-13 , DOI: 10.1109/jsyst.2020.2984512
Xinwei Wang , Liying Li , Jiandong Li , Chungang Yang , Lingxia Wang , Dusit Niyato

In the fifth-generation (5G) mobile communication system, base stations become denser, and user equipment becomes more powerful. Multiple-association technique promises diversity gains for 5G. However, existing multiple-association schemes are centralized, which have high signal overhead and depend on the reference signal receiving power, and cannot adapt to the fluctuating traffic of users. Therefore, it calls for a new distributed multiple-association scheme. We model the multiple-association problem as a state-based potential game (SPG). With the aid of SPG, the association policy that we designed could drive the ultradense networks to evolve toward the global optimization in the flow level performance. Finally, the performance of our proposed traffic-aware multiple association (TAMA) algorithm is investigated through a practical and discrete simulation method.

中文翻译:

超密集网络中的流量感知多重关联:基于状态的潜在博弈

在第五代(5G)移动通信系统中,基站变得更密集,并且用户设备变得更强大。多重关联技术有望为5G带来多样性。然而,现有的多关联方案是集中式的,其具有较高的信号开销并且依赖于参考信号的接收功率,并且不能适应用户的波动的业务。因此,它要求一种新的分布式多重关联方案。我们将多重关联问题建模为基于状态的潜在博弈(SPG)。借助SPG,我们设计的关联策略可以驱动超密集网络向流量级别性能的全局优化方向发展。最后,
更新日期:2020-05-13
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