论文标题
智能反射表面辅助MMWave MISO系统的稳健且安全的光束形成
Robust and Secure Beamforming for Intelligent Reflecting Surface Aided mmWave MISO Systems
论文作者
论文摘要
在这封信中，我们研究了智能反射表面（IRS）辅助毫米波（MMWave）多个输入单输出（MISO）系统的稳健和安全的光束形成（RSBF），其中多个单个天线窃听器（EVES）是任意分布在附近的合法接收机。考虑到在合法发射器上不完美地知道EVES通道的通道状态信息（CSI），因此在总传输功率和单位模块约束下，RSBF设计问题以最大化可实现的保密率（ASR）最大化。由于问题由于其非凸性和耦合变量而难以最佳解决，因此我们通过离散样品的加权组合替代窃听通道，并提出基于交替优化和半预菲斯松弛（SDR）技术的RSBF方案，以填充胶水和非胶水凝胶场景。仿真结果表明，所提出的RSBF方案可以有效地改善ASR，并优于其他基准方案。
In this letter, we investigate the robust and secure beamforming (RSBF) in an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multiple input single output (MISO) system, where multiple single antenna eavesdroppers (Eves) are arbitrarily distributed nearby the legitimate receiver. Considering the channel state information (CSI) of Eves' channels is imperfectly known at the legitimate transmitter, the RSBF design problems to maximize the worst case of achievable secrecy rate (ASR) are formulated under the total transmission power and unit-modulus constraints. Since the problems are difficult to solve optimally due to their nonconvexity and coupled variables, we substitute the wiretap channels by a weighted combination of discrete samples and propose a RSBF scheme based on alternating optimization and semidefinite relaxation (SDR) techniques, for both colluding and noncolluding eavesdropping scenarios. Simulation results show that the proposed RSBF scheme can effectively improve the ASR and also outperforms other benchmark schemes.
