Joint active and passive beamforming optimization for IRS-assisted downlink MISO-URLLC in max–min fairness.
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| Title: | Joint active and passive beamforming optimization for IRS-assisted downlink MISO-URLLC in max–min fairness. |
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| Authors: | Ye, Changqing1,2 (AUTHOR), Jiang, Hong1 (AUTHOR) hjiangpho@163.com, Xu, Hongliang1 (AUTHOR), Shi, Haoxin1 (AUTHOR), Deng, Liping1 (AUTHOR) |
| Source: | Wireless Networks (10220038). Apr2024, Vol. 30 Issue 3, p1479-1491. 13p. |
| Subjects: | Multiuser computer systems, Beamforming, Fairness, Computational complexity, Miso |
| Abstract: | In this paper, we propose a max–min fairness optimization scheme for a downlink multiuser multiple-input single-output (MISO) ultra-reliable and low-latency communication (URLLC) system assisted by an intelligence reflecting surface (IRS). In particular, we formulate a max–min fairness problem to jointly optimize the active beamforming vector at the base station (BS) and the passive beamforming vector at the IRS under the perfect channel state information (CSI). This problem is a non-convex optimization problem with highly coupled variables, making it challenging to obtain the global optimal solution. Subsequently, we propose a computationally-efficient iterative algorithm to obtain a suboptimal solution to this problem. In each iteration, we adopt methods such as the successive convex approximation (SCA) method, semi-positive definite relaxation (SDR) technology, and alternating optimization (AO) method to handle the internal optimization problem. Our simulation results reveal the following: (1) the proposed scheme provides a URLLC rate that is quite close to the Shannon rate, while also exhibiting low computational complexity; (2) the proposed scheme outperforms the random IRS scheme with a performance gain of up to 55%; (3) compare with conventional MISO systems without IRS, the proposed scheme offers a significant performance gain. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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