5G小蜂窝网络中协同层干扰抑制的博弈论

Ducheng Wu, Qi-hui Wu, Yuhua Xu
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引用次数: 0

摘要

小蜂窝技术被视为无线数据服务和5G需求快速增长的最有前途的解决方案之一。然而,由于大多数SBSs的部署很少受到最终用户和服务提供商的干预,因此很难减轻共层干扰。研究自组织分布式共层干扰抑制和资源分配具有重要意义。博弈论是一种有效的分布式方法,可以在没有中央控制器的情况下处理分布式共层干扰缓解问题。本章将讨论博弈论和分布式学习解决方案在分布式共层干扰缓解中的应用。针对固定负载和动态负载的小蜂窝网络,分别提出和讨论了静态和动态共层干扰抑制的两种潜在博弈模型。此外,还提出了两种分布式学习算法,并对结果进行了讨论。最后,对今后的研究方向进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Game Theory for Co-Tiered Interference Mitigation in 5G Small-Cell Networks
Small-cell technologies are seen as one of the most promising solutions for the rapid growth of wireless data services and 5G requirements. However, because most SBSs are deployed with minimum intervention from the end users and the service providers, it is hard to mitigate co-tiered interference. It is significant to study the self-organized distributed co-tiered interference mitigation and resource allocation. Game theory is an effective distributed approach towards handling the distributed co-tiered interference mitigation problem without a central controller. This chapter is to address the application of game theory and distributed learning solutions for distributed co-tiered interference mitigation. Two potential game models for static and dynamic co-tiered interference mitigation are presented and discussed for small-cell networks with fixed loads and dynamic loads separately. In addition, two distributed learning algorithms are presented and results are discussed. Finally, some future research directions are given.
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