Intelligent Reflecting Surface-Assisted and Artificial Noise Enhancement-Based Beamforming Method in Covert High-Speed Rail Communications
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摘要:
针对高铁无线通信系统中信息传输普遍存在有效吞吐量低和隐蔽程度受限的问题，以隐蔽需求、最大人工噪声（AN）发射功率和IRS相移的单位模为约束条件，构建以最大化高铁无线通信系统有效吞吐量为目标函数的优化问题，并设计一种基于智能反射面（IRS）辅助及AN增强的高铁无线隐蔽通信波束赋形方法；采用交替优化策略，把优化变量耦合问题拆分为3个子问题，分别为基站波束赋形、IRS相移优化以及AN发射功率优化；在分式规划中，借助二次变换方法将隐蔽需求约束映射在复圆流形上，利用共轭梯度算法（CG）对IRS相移进行优化，并使用Dinkelbach算法对AN发射功率设计并交替迭代优化. 仿真结果表明，该算法的计算复杂度较低，在高速移动环境下，系统有效吞吐量提高了27.31%，隐蔽传输性能得以提升，这对保障高铁无线通信系统安全信息传输具有重要的意义.
Abstract:To address the prevalent issues of low effective throughput and limited covertness in high-speed rail (HSR) wireless communication systems, an optimization problem was formulated to maximize the system’s effective throughput, subject to constraints on the covert requirement, transmit power of the maximum artificial noise (AN), and the unit modulus of the intelligent reflecting surface (IRS) phase shifts, and a beamforming method for covert HSR wireless communications based on IRS assistance and AN enhancement was designed. An alternating optimization strategy was adopted, decomposing the coupled optimization variables into three subproblems, including base station beamforming, IRS phase shift optimization, and AN transmit power optimization. The covert requirement constraint was mapped onto a complex circle manifold using the quadratic transform method from fractional programming. The conjugate gradient (CG) algorithm was employed to optimize the IRS phase shifts. The Dinkelbach algorithm was used to design the AN transmit power, and these steps were iterated alternately. Simulation results demonstrate that the proposed algorithm achieves a lower computational complexity. Under high-speed scenarios, it enhances the system’s effective throughput by 27.31% and improves the covert transmission performance, which is important for enhancing the security of information transmission in HSR wireless communication systems.
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图 1 IRS辅助的高铁隐蔽通信系统
Figure 1. IRS-assisted covert communication system for high-speed rail
图 4 MR端SINR与系统有效吞吐量随IRS反射单元数量的变化
Figure 4. Variation of SINR and effective system throughput at MR side with number of IRS reflection units
图 5 MR端SINR与系统有效吞吐量随IRS水平位置的变化
Figure 5. Variation of SINR and effective system throughput at MR side with IRS horizontal positions
图 6 MR端SINR与系统有效吞吐量随列车速度的变化
Figure 6. Variation of SINR and effective system throughput at MR side with train speed
图 7 MR端SINR与系统有效吞吐量随路径损耗因子的变化
Figure 7. Variation of SINR and effective system throughput at MR side with path loss factor
图 8 MR端SINR与系统有效吞吐量随AN最大发射功率的变化
Figure 8. Variation of SINR and effective system throughput at MR side with maximum transmit power of AN
图 9 多普勒频偏补偿误差对MR端SINR与系统有效吞吐量的影响
Figure 9. Effect of Doppler frequency offset compensation error on SINR and effective system throughput at MR side
表 1 算法运行时间比较
Table 1. Comparison of algorithm running time
s 算法 迭代次数 第 1 次 第 2 次 第 3 次 第 4 次 第 5 次 CG 9.3288 9.0754 8.9765 9.7164 8.8943 SDR 466.4370 453.7720 448.8260 485.8240 444.7110 
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表 2 仿真参数
Table 2. Simulation parameters
参数 数值 载波频率/GHz 5 系统带宽/MHz 100 噪声功率$ \sigma _{\text{w}}^2 $/dBm −110 AN 最大发射功率$P_{\mathrm{B}}^{{\mathrm{max}}}$/dBm 40 BS 天线数目NBS 4 BS到MR链路路径损耗因子 3.5 BS到IRS链路路径损耗因子 2.2 IRS到MR链路路径损耗因子 2.5 莱斯因子 10 时隙/ms 0.6
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