论文标题

智能反射表面辅助多用户交流:容量区域和部署策略

Intelligent Reflecting Surface Aided Multi-User Communication: Capacity Region and Deployment Strategy

论文作者

Zhang, Shuowen, Zhang, Rui

论文摘要

智能反射表面(IRS)是一项新的有前途的技术,能够通过智能和被动信号反射重新配置无线传播通道。在本文中,我们调查了一个由$ M $ IRS元素辅助的两用户通信网络的容量区域,以增强用户AP频道,在此范围内,IRS会延迟可忽略的延迟,因此通过IRS遵循经典的离散存储通道模型,通过IRS遵循的用户AP通道。特别是,我们考虑了两种实用的IRS部署策略,这些策略导致用户与AP之间的不同有效渠道,即分布式部署,其中$ m $元素形成两个IRS,每个IRS在一个用户附近部署,而在集中的部署中,所有$ m $元素都在所有$ m $ emement epap ap ap ap ap ap ap。首先,我们考虑上行链路多访问渠道(MAC),并在不同的多个访问方案下得出两种部署策略的容量/可实现率区域。结果表明,在可实现的用户率方面,集中式部署通常优于对称渠道设置下的分布式部署。接下来,我们通过利用著名的上行链路 - 划线链接(或MAC-BC)双重性框架将结果扩展到下行链路广播频道(BC),并表明集中式的优于分布式部署的较高速率性能也可以。提出了验证我们的分析的数值结果,并揭示了无线网络中最佳IRS部署的新的和有用的见解。

Intelligent reflecting surface (IRS) is a new promising technology that is able to reconfigure the wireless propagation channel via smart and passive signal reflection. In this paper, we investigate the capacity region of a two-user communication network with one access point (AP) aided by $M$ IRS elements for enhancing the user-AP channels, where the IRS incurs negligible delay, thus the user-AP channels via the IRS follow the classic discrete memoryless channel model. In particular, we consider two practical IRS deployment strategies that lead to different effective channels between the users and AP, namely, the distributed deployment where the $M$ elements form two IRSs, each deployed in the vicinity of one user, versus the centralized deployment where all the $M$ elements are deployed in the vicinity of the AP. First, we consider the uplink multiple-access channel (MAC) and derive the capacity/achievable rate regions for both deployment strategies under different multiple access schemes. It is shown that the centralized deployment generally outperforms the distributed deployment under symmetric channel setups in terms of achievable user rates. Next, we extend the results to the downlink broadcast channel (BC) by leveraging the celebrated uplink-downlink (or MAC-BC) duality framework, and show that the superior rate performance of centralized over distributed deployment also holds. Numerical results are presented that validate our analysis, and reveal new and useful insights for optimal IRS deployment in wireless networks.

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