可重构智能表面辅助的通信信号处理技术
Signal Processing Technologies for RIS-assisted Wireless Communications
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摘要: 可重构智能表面(Reconfigurable Intelligent Surface,RIS)通过在平面上集成大量低成本无源反射元件,实现对无线传输环境的智能配置,从而显著提高无线通信网络的性能。具体来讲,RIS上的不同反射元件可以通过控制振幅和/或相位来独立反射入射信号,从而协同实现三维波束赋形,实现信号的增强或减弱。与其他类似技术形成鲜明对比的是,RIS通过高度可控地智能信号反射主动修正无线传输信道,来增强期望信号功率,或减小信道干扰,为进一步提升无线通信网络的性能提供了全新优化自由度。此外,RIS重量轻、体积小,很容易在墙壁、天花板、建筑物表面等实现安装、移除,具有可重复利用性;RIS的硬件结构通常比小型有源基站和中继简单,因此易于进行低成本快速部署。最后,RIS是一种补充设备,将其部署在现有无线系统中不需要更改相应标准和硬件,仅需对通信协议进行必要修改。基于以上优势,RIS引起了广泛关注,工业界、学术界对其开展了大量研究工作,包括传输协议设计、系统容量分析、能量/频谱效率分析、物理层安全、调制/编码方案设计等。尽管优点众多,但实现RIS与现有无线通信系统的完美融合,依然面临诸多挑战。首先,在RIS辅助的无线通信系统中,基站和RIS的主被动联合优化波束赋形是保证系统性能的基础。RIS由于结构特殊,无法对入射信号进行处理,只能被动的反射入射信号,此外,RIS 反射元件数量巨大,导致发射机主动波束成形和RIS被动反射设计的联合优化非常复杂、耗时。因此,RIS辅助的无线通信系统设计面临两大亟需解决的关键问题:(1)如何设计低复杂度优化方法以实现基站和RIS主被动波束赋形的联合设计;(2)在RIS辅助的无线通信系统中,如何设计合理的协作传输方案,以实现系统性能的最优化。本文针对以上问题,着重探讨了RIS辅助的无线通信系统低复杂度信号处理技术,从单RIS辅助无线通信场景扩展到多RIS辅助协作通信场景,探讨适合大规模RIS 辅助系统的低复杂度设计方法,推动RIS 在实际场景中的部署应用。Abstract: Reconfigurable intelligent surface (RIS), as a revolutionary technology, can realize intelligent configuration of the wireless transmission environment by integrating numerous low-cost passive reflective elements on a flat surface, thus significantly improving the performance of wireless communication networks. Specifically, different reflection elements can independently reflect incident signals by controlling their amplitudes and/or phase shifts, thus cooperatively achieving three-dimensional passive beamforming for directional signal enhancement or weakening. In sharp contrast to existing technologies, RIS can provide a new degree of optimization to further improve the performance of wireless communication networks. Owing to its ability to actively change the wireless transmission channels through highly controllable intelligent signal reflections, RIS can enhance the desired signal power at the receiver or mitigate undesired signals such as channel interference. Moreover, owing to the specificity of their hardware structure, RISs are generally lightweight and small. Therefore, they can be easily installed and removed from surfaces such as walls, ceilings, buildings, and advertising panels, allowing their reuse. In addition, RISs are usually significantly cheaper than active small base stations and relays and, therefore, can be rapidly deployed at a low cost. RIS is a complementary device that can be deployed in existing wireless systems without changing the corresponding standards or hardware, as only necessary modifications to the communication protocols are required. Owing to these advantages, RISs have been extensively investigated in research areas such as transmission protocol designs, system capacity analysis, energy/spectral efficiency, physical layer security, and modulation/coding schemes. New challenges have also arisen in the design and implementation of RIS-aided wireless systems. According to existing studies, for RIS-assisted wireless communication systems, the joint active-passive beamforming of the base station and RIS is fundamental to ensuring system performance. However, because of their special structures, RISs cannot process incident signals but only passively reflect them. Moreover, because of the high number of RIS reflecting elements, the joint optimization of the active beamforming at the transmitter and the passive reflecting at the RIS can be highly complicated and time-consuming. Therefore, the design of RIS-assisted wireless communication systems should address the following issues: (1) how to design a low-complexity optimization method to achieve joint active and passive beamforming at the base station and RIS, and (2) how to design efficient collaborative transmission schemes in multi-RIS-assisted wireless communication systems to achieve optimal system performance. To address the aforementioned challenges, an in-depth study is conducted. Herein, we focus on the low-complexity signal processing techniques for RIS-assisted wireless communication systems, extend from single RIS-assisted wireless communication systems to multi-RIS-assisted collaborative communication systems, explore a series of advanced digital signal processing techniques, and design a low-complexity design methodology that is suitable for large-scale RIS-assisted communication systems to promote the deployment and application of RIS in practical applications.