AI 中文总结
研究LC - RIS辅助系统安全通信中的温度感知优化问题，提出不依赖完整CSI的相移设计及低复杂度启发式方法，设计温度鲁棒算法，仿真表明该方法相比传统设计能提升保密率。
AI 中文摘要
虽然液晶（LC）技术有助于实现节能且可扩展的可重构智能表面（RIS），但其相移响应本质上依赖于温度。忽略这种热依赖性会导致性能下降，在安全无线系统中尤其有害，因为相移不准确可能导致意外的信息泄露。为应对这一挑战，我们研究了LC - RIS辅助系统中的安全通信并开发了温度自适应相移设计。毫米波频率下大量元件用于补偿高路径损耗，大规模部署LC - RIS会因信道状态信息（CSI）获取带来巨大开销挑战。为此提出不依赖完整CSI的相移设计，通过照亮空间区域而非单个目标位置增强对热致相移误差和定位不准确的鲁棒性。我们提出基于半定规划（SDP）的方法作为高性能基准以及低复杂度启发式方法。基于此可扩展框架进一步设计温度鲁棒算法，无需实时温度数据即可保持高安全性。大量仿真结果证实，与忽略温度影响的传统设计相比；我们的温度自适应和温度鲁棒方法产生了更高的保密率。
英文摘要
While LC technology facilitates the realization of energy-efficient and scalable RISs, their phase shift response is inherently temperature-dependent. Neglecting this thermal dependency can lead to performance degradation, which is particularly detrimental in secure wireless systems where phase-shift inaccuracies may result in unintended information leakage. To address this challenge, we investigate secure communication in LC-RIS-aided systems and develop a temperature-adaptive phase-shift design. Beyond thermal sensitivity, the massive number of elements at mmWave frequencies is required to compensate for high path loss. This large-scale deployment of LC-RISs can lead to significant overhead challenges due to the acquisition of CSI. To ensure practical feasibility, this work proposes a phase-shift design that does not rely on the full CSI; instead, it employs only the possible locations of legitimate users and potential eavesdroppers. By illuminating a spatial zone rather than a single target location, the proposed temperature-adaptive algorithm enhances robustness against both thermally induced phase errors and positioning inaccuracies. To solve the resulting optimization problem, we present an SDP-based approach to serve as a high-performance benchmark, as well as a low-complexity heuristic method. The latter demonstrates superior scalability as the number of RIS elements increases, which makes it highly effective for deploying extremely large surfaces in dynamic, real-time environments. Based on this scalable framework, we further design a temperature-robust algorithm that maintains high security without requiring real-time temperature data. Extensive simulation results confirm that our temperature-adaptive and temperature-robust approaches yield a superior secrecy rate compared to conventional designs that neglect temperature impacts.
