- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | LI Cuiran, SUN Shujing, ZHANG Zepeng, WANG Huiqin, XIE Jianli. Intelligent Reflecting Surface-Assisted and Artificial Noise Enhancement-Based Beamforming Method in Covert High-Speed Rail Communications[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240424
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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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