Achieving accurate location-awareness in wireless networks requires integrated sensing and communication (ISAC), where optimization, signal processing, and data fusion are performed under a common framework. The efficiency of ISAC in complex wireless environments can be improved via the use of reconfigurable intelligent surfaces (RISs). This paper introduces the concept of continuous intelligent surface (CIS) and establishes the fundamental limits of RIS-aided ISAC systems, specifically, an RIS-aided localization and communication system. In particular, this paper considers two types of RISs, namely CISs and discrete intelligent surfaces (DISs). First, this paper proposes a general signal model for RIS-aided localization and communication valid for both near-field and far-field scenarios, and then theoretical limits on the localization and communication performance are derived. Based on the proposed model, Fisher information analyses of the localization performance in networks with RISs are performed. Numerical results show that RISs with optimized phase responses can improve the received signal-to-noise ratio (SNR) and spectral efficiency of communication, and the localization accuracy significantly.

中文翻译：

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通过可重新配置的智能表面实现超越 5G 网络的位置感知


在无线网络中实现准确的位置感知需要集成传感和通信（ISAC），其中优化、信号处理和数据融合在通用框架下执行。通过使用可重构智能表面 (RIS) 可以提高复杂无线环境中 ISAC 的效率。本文介绍了连续智能表面（CIS）的概念，并建立了 RIS 辅助 ISAC 系统的基本限制，特别是 RIS 辅助定位和通信系统。特别是，本文考虑了两种类型的 RIS，即 CIS 和离散智能表面（DIS）。首先，本文提出了一种适用于近场和远场场景的 RIS 辅助定位和通信的通用信号模型，然后推导了定位和通信性能的理论限制。基于所提出的模型，对具有 RIS 的网络中的定位性能进行了 Fisher 信息分析。数值结果表明，具有优化相位响应的RIS可以显着提高接收信噪比（SNR）和通信频谱效率以及定位精度。