重庆理工大学学报2024，Vol.38Issue(5)：300-307,8.DOI:10.3969/j.issn.1674-8425(z).2024.03.033
智能反射面辅助下行NOMA网络功率最小化研究
Power minimization design for IRS-Aided downlink NOMA networks
摘要
Abstract
Both intelligent reflecting surface ( IRS ) and non-orthogonal multiple access ( NOMA )have been viewed as the key techniques for future communication systems. Together, IRS and NOMA effectively improve coverage quality and energy efficiency for communication systems. This paper focuses on an IRS-assisted downlink multi-antenna NOMA system. The transmit power of the base station is minimized based on the users' decoding orders, the base station's beam-forming vector, and the IRS's phase-shift matrix. Firstly, the optimal decoding order is obtained by the strengths of all users' channels. Then, the optimal beam-forming vector and phase shift matrix are designed by invoking the alternative optimization method. Specifically, when optimizing beam-forming vector, the original problem is transformed into a second order cone programming ( SOCP ) . Additionally, a sequential phase-rotation method is proposed to design the optimal phase shift matrix. Our simulation results show on condition of satisfying users' service quality, our design significantly reduces the transmission power of the base station.关键词
智能反射面/非正交多址/发送功率/相位偏移/波束成形Key words
intelligent reflective surface/non-orthogonal multiple access/transmit power/phase shift/beam-forming分类
信息技术与安全科学引用本文复制引用
刘泽宇,王鸿..智能反射面辅助下行NOMA网络功率最小化研究[J].重庆理工大学学报,2024,38(5):300-307,8.基金项目
国家自然科学基金面上项目(62171237) （62171237）
