IRS-Enabled Spectrum Sharing: Interference Modeling, Channel Estimation and Robust Passive Beamforming

2022-03-16 Author:GUAN Xinrong, WU Qingqing Click:
IRS-Enabled Spectrum Sharing: Interference Modeling, Channel Estimation and Robust Passive Beamforming - ztecommunications
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IRS-Enabled Spectrum Sharing: Interference Modeling, Channel Estimation and Robust Passive Beamforming

Release Date:2022-03-16  Author:GUAN Xinrong, WU Qingqing  Click:

Coded Orthogonal Time Frequency Space Modulation

GUAN Xinrong1, WU Qingqing2
(1. College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China;
2. State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau 999078, China)

Abstract: Intelligent reflecting surface (IRS), with its unique capability of smartly reconfiguring wireless channels, provides a new solution to improving spectrum efficiency, reducing energy consumption and saving deployment/hardware cost for future wireless networks. In this paper, IRS-enabled spectrum sharing is investigated, from the perspectives of interference modeling, efficient channel estimation and robust passive beamforming design. Specifically, we first characterize the interference in a spectrum sharing system consisting of a single primary user (PU) pair and a single secondary user (SU) pair, and extend it to the large-scale network by leveraging the Poisson point process (PPP). Then, we propose an efficient channel estimation framework based on decoupling the cascaded IRS channels. Moreover, the tradeoff between spectrum efficiency and energy efficiency is derived from the view of channel estimation accuracy. Finally, we discuss the robust passive beamforming design in presence of imperfect channel estimation and nonideal/discrete phase shifts. It is hoped that this paper provides useful guidance for unlocking the full potential of IRS for achieving efficient spectrum sharing for future wireless networks.

Keywords: intelligent reflecting surface; spectrum sharing; channel estimation; passive beamforming

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