Paper Info
Title
Beamforming Design for IRS-assisted Uplink Cognitive Satellite-Terrestrial Networks with NOMA
Abstract
Integrating non-orthogonal multiple access (NOMA) in intelligent reflecting surface (IRS) is expectedly an effective solution to enhance system's spectrum efficiency. In this paper, we investigate joint beamforming and power allocation for uplink NOMA transmission in an IRS-assisted cognitive satellite and terrestrial network operating at millimeter wave frequency band. Specifically, based only on imperfect channel state information in terms of the angular information of both primary users (PUs) and secondary users, we formulate an optimization problem to maximize the sum rate of the PUs in terrestrial network. To handle the resulting intractable optimization problem, we first transform the uncertainty channel vectors into a deterministic form with the aid of angular discretization. Then, by combining successive convex approximation with Taylor expansion and S-procedure methods, we propose an optimization scheme to jointly optimize the beamforming weight vector and power coefficients. Finally, simulation results show that the proposed scheme can achieve outstanding sum rate performance compared to state-of-the-art schemes.
Year
DOI
Venue
2021
10.1109/GLOBECOM46510.2021.9685121
2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)
Keywords
DocType
ISSN
Cognitive satellite and terrestrial networks, intelligent reflecting surface, non-orthogonal multiple access, joint optimization
Conference
2334-0983
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Bai Zhao100.34
Huaicong Kong2104.52
Jian Ouyang312.05
Jun-Bo Wang417730.21
Wei-Ping Zhu515126.21