Heng Chang;Xueyu Kang;Hongjiang Lei;Theodoros A. Tsiftsis;Gaofeng Pan;Hongwu Liu
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For the sub-problem of optimizing the common rate allocation, a closed-form expression is derived for the optimal common rate allocation. For the multiple-ratio fractional programming sub-problems of optimizing the transmit beamforming and reflection/refraction beamforming, Lagrangian dual formulation and quadratic transformation are utilized to reconstruct the objective function in the form difference of convex functions. Then, a penalized successive convex approximation is utilized to tackle the rank-one constrained beamforming optimization. Simulation results clarify the effectiveness of the proposed AO algorithm to achieve the maximum covert communication rate. 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引用次数: 0
摘要
本文部署了一个同时发射和反射的可重构智能表面(STAR-RIS),以帮助多输入单输出(MISO)速率分割多路存取(RSMA)系统中的隐蔽通信。为了最大限度地提高隐蔽通信速率(由隐蔽用户的共享共用速率和专用速率决定),需要对发射波束成形、反射/折射波束成形和共用速率分配进行联合优化。通过将原始隐蔽通信速率最大化问题解耦为三个子问题,设计了一种交替优化(AO)算法,以获得优化解,从而实现最大隐蔽通信速率。对于优化公共速率分配的子问题,得出了最优公共速率分配的闭式表达式。对于优化发射波束成形和反射/折射波束成形的多比率分式编程子问题,利用拉格朗日对偶公式和二次变换将目标函数重构为凸函数差分形式。然后,利用受惩罚的连续凸近似来解决秩一约束波束成形优化问题。仿真结果证明了所提出的 AO 算法在实现最大隐蔽通信速率方面的有效性。与缺少共同速率分配的基准方案相比,仿真结果验证了 STAR-RIS 辅助 MISO-RSMA 方案有效地提高了隐蔽通信速率。
STAR-RIS-Aided Covert Communications in MISO-RSMA Systems
In this paper, a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is deployed to aid covert communications in a multiple-input single-output (MISO) rate-splitting multiple access (RSMA) system. To maximize the covert communication rate, which is characterized by the shared common rate and private rate of the covert user, the transmit beamforming, reflection/refraction beamforming, and common rate allocation need to be jointly optimized. By decoupling the original covert communication rate maximization problem into three sub-problems, an alternating optimization (AO) algorithm is designed to obtain the optimized solution to achieve the maximum covert communication rate. For the sub-problem of optimizing the common rate allocation, a closed-form expression is derived for the optimal common rate allocation. For the multiple-ratio fractional programming sub-problems of optimizing the transmit beamforming and reflection/refraction beamforming, Lagrangian dual formulation and quadratic transformation are utilized to reconstruct the objective function in the form difference of convex functions. Then, a penalized successive convex approximation is utilized to tackle the rank-one constrained beamforming optimization. Simulation results clarify the effectiveness of the proposed AO algorithm to achieve the maximum covert communication rate. Compared to the benchmark scheme in which the common rate allocation is missing, it is verified by simulation results that the STAR-RIS-aided MISO-RSMA scheme effectively increases the covert communication rate.