首页> 外文会议>IEEE International Conference on Communications >Decoupled Multiple Association in Full-Duplex Ultra-Dense Networks: An Evolutionary Game Approach
【24h】

Decoupled Multiple Association in Full-Duplex Ultra-Dense Networks: An Evolutionary Game Approach

机译:全双工超密集网络中的解耦多重关联:一种演化博弈方法

获取原文

摘要

User association is indispensable for the operation of wireless network and has critical impacts on system performance. For most existing work, user associations are typically coupled, which require a user equipment (UE) to associate with the same base station (BS) in uplink (UL) and downlink (DL). However, wireless networks are becoming heterogeneous and densifying, which generates intrinsic distinctions (transmission power, data traffic and backhaul capacity etc.) between UL and DL. Accordingly, coupled association may no longer be optimal. In this work, we explore decoupled user association in full-duplex ultra-dense networks (UDNs), which allows a UE to associate with different BSs in UL and DL respectively. Furthermore, to fully exploit the benefits of UDNs, multiple association, referring to associating a UE with multiple BSs, is jointly adopted in UL and DL. Considering the dynamic and complicated association process, an evolutionary game (EG) is formulated, where UEs are players, and their strategies are association selections in UL/DL. Particularly, evolutionary equilibrium is viewed as the stable solution to the formulated problem. Moreover, an EG-based algorithm with low complexity is proposed for decoupled multiple association. Numerical results validate the convergence of the proposed algorithm for strategy adoption. Besides, the impacts of information exchange delay and learning rate are investigated for providing a better association decision.
机译:用户关联对于无线网络的运行是必不可少的,并且对系统性能具有至关重要的影响。对于大多数现有工作,通常关联用户关联,这需要用户设备(UE)与上行链路(UL)和下行链路(DL)中的同一基站(BS)关联。然而,无线网络正变得异构和致密,这在UL和DL之间产生了固有的区别(传输功率,数据流量和回程容量等)。因此,耦合关联可能不再是最优的。在这项工作中,我们探索了全双工超密集网络(UDN)中的解耦用户关联,该关联使UE可以分别与UL和DL中的不同BS关联。此外,为了充分利用UDN的益处,在UL和DL中联合采用了多个关联,即将UE与多个BS关联。考虑到动态和复杂的关联过程,制定了一种进化游戏(EG),其中UE是玩家,其策略是UL / DL中的关联选择。特别地,进化均衡被视为解决所提出问题的稳定解决方案。此外,提出了一种基于EG的低复杂度算法,用于解耦的多重关联。数值结果验证了所提出算法在策略采用上的收敛性。此外,研究了信息交换延迟和学习率的影响,以提供更好的关联决策。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号