Enhanced-rate Iterative Beamformers for Active IRS-assisted Wireless Communications
Yeqing Lin, Feng Shu, Rongen Dong, Riqing Chen, Siling Feng, Weiping, Shi, Jing Liu, Jiangzhou Wang

TL;DR
This paper introduces three novel iterative beamforming methods for active IRS-assisted wireless networks, significantly improving achievable rates over existing passive IRS and other beamforming techniques.
Contribution
It proposes three enhanced-rate iterative beamforming algorithms, including Max-SSNR-RR, GMRR, and Max-SNR-FP, for active IRS to boost wireless communication rates.
Findings
All three methods outperform passive IRS and existing beamforming techniques.
Max-SNR-FP achieves the highest rate among the proposed methods.
Simulation results confirm substantial rate enhancements with the new algorithms.
Abstract
Compared to passive intelligent reflecting surface (IRS), active IRS is viewed as a more efficient promising technique to combat the double-fading impact in IRS-aided wireless network. In this paper, in order to boost the achievable rate of user in such a wireless network, three enhanced-rate iterative beamforming methods are proposed by designing the amplifying factors and the corresponding phases at active IRS. The first method, maximizing the simplified signal-to-noise ratio (Max-SSNR) is designed by omitting the cross-term in the definition of rate. Using the Rayleigh-Ritz (RR) theorem, Max-SSNR-RR is proposed to iteratively optimize the norm of beamforming vector and its associated normalized vector. In addition, generalized maximum ratio reflection (GMRR) is presented with a closed-form expression, which is motivated by the maximum ratio combining. To further improve rate,…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced Antenna and Metasurface Technologies · Antenna Design and Analysis
