当前位置: X-MOL 学术IEEE Trans. Commun. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Multi-User Small Base Station Association via Contextual Combinatorial Volatile Bandits
IEEE Transactions on Communications ( IF 8.3 ) Pub Date : 2021-03-09 , DOI: 10.1109/tcomm.2021.3064939
Muhammad Anjum Qureshi , Andi Nika , Cem Tekin

We propose an efficient mobility management solution to the problem of assigning small base stations (SBSs) to multiple mobile data users in a heterogeneous setting. We formalize the problem using a novel sequential decision-making model named contextual combinatorial volatile multi-armed bandits (MABs), in which each association is considered as an arm, volatility of an arm is imposed by the dynamic arrivals of the users, and context is the additional information linked with the user and the SBS such as user/SBS distance and the transmission frequency. As the next-generation communications are envisioned to take place over highly dynamic links such as the millimeter wave (mmWave) frequency band, we consider the association problem over an unknown channel distribution with a limited feedback in the form of acknowledgments and under the absence of channel state information (CSI). As the links are unknown and dynamically varying, the assignment problem cannot be solved offline. Thus, we propose an online algorithm which is able to solve the user-SBS association problem in a multi-user and time-varying environment, where the number of users dynamically varies over time. Our algorithm strikes the balance between exploration and exploitation and achieves sublinear in time regret with an optimal dependence on the problem structure and the dynamics of user arrivals and departures. In addition, we demonstrate via numerical experiments that our algorithm achieves significant performance gains compared to several benchmark algorithms.

中文翻译:

通过上下文组合易失性强盗的多用户小基站关联

我们针对在异构环境中将小型基站 (SBS) 分配给多个移动数据用户的问题提出了一种有效的移动性管理解决方案。我们使用一种名为上下文组合易失性多臂强盗 (MAB) 的新型顺序决策模型将问题形式化,其中每个关联被视为一个臂,臂的波动性由用户的动态到达强加,而上下文是与用户和SBS相关联的附加信息,例如用户/SBS距离和传输频率。由于下一代通信被设想在高度动态的链路上进行,例如毫米波 (mmWave) 频段,我们考虑了未知信道分布上的关联问题,并且在没有信道状态信息 (CSI) 的情况下,以确认的形式提供有限的反馈。由于链接未知且动态变化,分配问题无法离线解决。因此,我们提出了一种在线算法,该算法能够在多用户和时变环境中解决用户-SBS 关联问题,其中用户数量随时间动态变化。我们的算法在探索和开发之间取得了平衡,并通过对问题结构和用户到达和离开动态的最佳依赖实现了时间遗憾的次线性。此外,我们通过数值实验证明,与几种基准算法相比,我们的算法实现了显着的性能提升。
更新日期:2021-03-09
down
wechat
bug