| MA Junchi(马俊驰),GAO Jing,YANG Maolin,SUN Haonan,CHEN Bing.[J].高技术通讯(英文),2024,30(4):415~423 |
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| On the achievable rate for double intelligent reflecting surface enhanced cognitive radio network |
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| DOI：10. 3772 / j. issn. 1006-6748. 2024. 04. 009 |
| 中文关键词: |
| 英文关键词: intelligent reflective surface ( IRS), cognitive radio ( CR), distributed IRS,beamforming, alternating optimization (AO) |
| 基金项目: |
| Author Name | Affiliation | | MA Junchi(马俊驰) | (Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University,Tianjin 300382, P. R. China) | | GAO Jing | | | YANG Maolin | | | SUN Haonan | | | CHEN Bing | |
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| 中文摘要: |
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| 英文摘要: |
| Intelligent reflecting surface (IRS) can efficiently improve the performance of wireless communication networks by intelligently reconfiguring the wireless propagation environment. Recently, IRS has been integrated with cognitive radio (CR) network in order to improve the resource utilization of communication systems. It is a challenging issue for IRS-assisted CR networks to improve the rate performance of the secondary user ( SU) through the rational design of IRS passive beamforming while limiting the interference to the primary network. This paper investigates the optimization of downlink rate of SU in a double-IRS-assisted CR network. The achievable rate is maximized by jointly optimizing the active beamforming vector at the secondary transmitter (SU-TX) and the cooperatively passive reflective beamforming at the two distributed IRSs. To solve the proposed non-convex joint optimization problem, the alternating optimization ( AO) and semidefinite relaxation (SDR) techniques are then adopted to iteratively optimize the two variables. Numerical results validate that the proposed double-IRS assisted system can significantly improve the performance of the CR network compared with the existing single-IRS assisted CR system. |
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