High-performance Power Allocation Strategies for Active IRS-aided Wireless Network

被引:0
|
作者
Zhao, Yifan [1 ]
Wang, Xuehui [1 ]
Wang, Yan [1 ]
Wang, Xianpeng [1 ]
Chen, Zhilin [1 ]
Shu, Feng [1 ]
Pan, Cunhua [2 ]
Wang, Jiangzhou [3 ]
机构
[1] Hainan Univ, Informat & Commun Engn, Haikou, Hainan, Peoples R China
[2] Southeast Univ, Natl Mobile Commun Sch Engn, Nanjing, Peoples R China
[3] Univ Kent, Sch Engn, Canterbury, Kent, England
基金
中国国家自然科学基金;
关键词
Active intelligent reflecting surface; power allocation; gradient ascent; equal-spacing-multiple-point-initialization; closed-form; rate performance; ENERGY EFFICIENCY;
D O I
10.1109/CCAI61966.2024.10603091
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Due to its intrinsic ability to combat the double-fading effect, the active intelligent reflective surface (IRS) be-comes popular. The main feature of active IRS must be supplied by power, and the problem of how to allocate the total power between base station (BS) and IRS to fully explore the rate gain achieved by power allocation (PA) to remove the rate gap between existing PA strategies and optimal exhaustive search (ES) arises naturally. First, the signal-to-noise ratio (SNR) expression is derived to be a function of PA factor beta is an element of[0,1]. Then, to improve the rate performance of the conventional gradient ascent (GA), an equal-spacing-multiple-point-initialization GA (ESMPI-GA) method is proposed. Due to its slow linear convergence from iterative GA, the proposed ESMPI-GA is high-complexity. Eventually, to reduce this high complexity, a low-complexity closed-form PA method with third-order Taylor expansion (TTE) centered at point beta(0) = 0.5 is proposed. Simulation results show that the proposed ESMPI-GA and TTE obviously outperform existing methods like equal PA.
引用
收藏
页码:388 / 393
页数:6
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