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arXiv 2406.09192eess.SP
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有源 IRS 辅助方向调制安全系统的联合功率分配与波束成形设计

Joint Power Allocation and Beamforming Design for Active IRS-Aided Directional Modulation Secure Systems

Yifan Zhao, Xiaoyu Wang, Kaibo Zhou, Xuehui Wang, Yan Wang, Wei Gao, Ruiqi Liu, Feng Shu

AI总结:

针对安全方向调制网络SR提升受限问题,提出有源IRS辅助网络,设计了LDT-CFFP方法及低复杂度的NSP-MRR-PA方法联合优化功率分配与波束成形,有效提升了系统安全速率。

摘要:

由于安全方向调制(DM)网络获得的安全速率(SR)性能提升有限,因此考虑采用有源智能反射面(IRS)辅助的 DM 网络以获得高 SR。为了解决 SR 最大化问题,提出了一种基于拉格朗日对偶变换和闭式分数规划算法(LDT-CFFP)的新方法,其中求得了基站(BS)波束成形向量和 IRS 反射系数矩阵的解。然而,LDT-CFFP 方法的计算复杂度较高。为了降低其复杂度,设计了一种分块 IRS 辅助的 DM 网络。为了满足网络性能要求,提出并在系统中采用了功率分配(PA)策略。具体而言,BS 和 IRS 之间的系统功率,以及来自 BS 的机密消息(CM)和人工噪声(AN)的传输功率,被分别进行分配。然后我们提出了零空间投影(NSP)方法、最大比反射(MRR)算法和 PA 策略(NSP-MRR-PA)来解决 SR 最大化问题。BS 波束成形向量和 IRS 反射系数矩阵的闭式解分别通过 NSP 和 MRR 算法获得。对于 PA 因子,我们利用穷举搜索(ES)算法、粒子群优化(PSO)和模拟退火(SA)算法来寻找解。从仿真结果验证,LDT-CFFP 方法比 NSP-MRR-PA 方法获得了更高的 SR 增益。对于 NSP-MRR-PA 方法,每个块中的 IRS 单元数量具有显著的 SR 性影响。此外,应用 PA 策略,即 ES、PSO、SA 方法优于其他具有固定 PA 因子的 PA 策略。

英文摘要:

Since the secrecy rate (SR) performance improvement obtained by secure directional modulation (DM) network is limited, an active intelligent reflective surface (IRS)-assisted DM network is considered to attain a high SR. To address the SR maximization problem, a novel method based on Lagrangian dual transform and closed-form fractional programming algorithm (LDT-CFFP) is proposed, where the solutions to base station (BS) beamforming vectors and IRS reflection coefficient matrix are achieved. However, the computational complexity of LDT-CFFP method is high . To reduce its complexity, a blocked IRS-assisted DM network is designed. To meet the requirements of the network performance, a power allocation (PA) strategy is proposed and adopted in the system. Specifically, the system power between BS and IRS, as well as the transmission power for confidential messages (CM) and artificial noise (AN) from the BS, are allocated separately. Then we put forward null-space projection (NSP) method, maximum-ratio-reflecting (MRR) algorithm and PA strategy (NSP-MRR-PA) to solve the SR maximization problem. The CF solutions to BS beamforming vectors and IRS reflection coefficient matrix are respectively attained via NSP and MRR algorithms. For the PA factors, we take advantage of exhaustive search (ES) algorithm, particle swarm optimization (PSO) and simulated annealing (SA) algorithm to search for the solutions. From simulation results, it is verified that the LDT-CFFP method derives a higher SR gain over NSP-MRR-PA method. For NSP-MRR-PA method, the number of IRS units in each block possesses a significant SR performance. In addition, the application PA strategies, namely ES, PSO, SA methods outperforms the other PA strategies with fixed PA factors.

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