Joint Transmit Precoding and Reflect Beamforming Design for IRS-Assisted MIMO Cognitive Radio Systems

In this paper, we consider an intelligent reflecting surface (IRS)-assisted downlink cognitive radio (CR) system, in which a secondary access point (SAP) communicates with multiple secondary users (SUs) without affecting multiple primary users (PUs) in the primary network and all nodes are equipped...

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Bibliographic Details
Published inIEEE transactions on wireless communications Vol. 21; no. 6; pp. 3617 - 3631
Main Authors Jiang, Weiheng, Zhang, Yu, Zhao, Jun, Xiong, Zehui, Ding, Zhiguo
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
alternating optimization (AO)
Array signal processing
Base stations
Beamforming
Codes
Cognitive radio
cognitive radio (CR)
Complexity
Intelligent reflecting surface (IRS)
MIMO communication
multiple-input multiple-output (MIMO)
Optimization
Precoding
resource allocation
Signal to noise ratio
Wireless communication
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Summary:In this paper, we consider an intelligent reflecting surface (IRS)-assisted downlink cognitive radio (CR) system, in which a secondary access point (SAP) communicates with multiple secondary users (SUs) without affecting multiple primary users (PUs) in the primary network and all nodes are equipped with multiple antennas. Our design objective is to maximize the achievable weighted sum rate (WSR) of SUs subject to the total transmit power constraint at the SAP and the interference constraints at PUs, by jointly optimizing the transmit precoding at the SAP and the reflecting coefficients at the IRS. To deal with the complex objective function, the problem is reformulated by employing the well-known weighted minimum mean-square error (WMMSE) method and an alternating optimization (AO)-based algorithm is proposed. Furthermore, a special scenario with only a single PU and multiple SUs is considered and AO algorithm is adopted again. It is worth mentioning that the proposed algorithm has a much lower computational complexity than the above algorithm without the performance loss. Finally, some numerical simulations have been provided to demonstrate that the proposed algorithm outperforms other benchmark schemes.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2021.3122959