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Resource Allocation Design for IRS-Aided Downlink MU-MISO RSMA Systems

机译:IRS辅助下行链路MU-MISO RSMA系统的资源分配设计

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In this paper, we consider the max-min fairness (MMF) transmission for an intelligent reflecting surface (IRS)- aided multi-user multiple-input single-output (MU-MISO) rate splitting multiple access (RSMA) downlink system. Our resource allocation design aims to maximize the minimum transmission rate among multiple single-antenna users via optimizing the transmit beamformers at the transmitter and the reflecting phase shift vector at the IRS. To this end, the algorithm design is formulated as a mixed non-convex and combinatorial optimization problem which takes into account the discrete phase shift and the maximum transmit power budget. To address the intractability of the design optimization problem, the successive convex approximation (SCA) technique, the penalty method, and the alternating optimization (AO) approach are exploited to design a suboptimal iterative algorithm for obtaining an effective solution of the considered problem. Simulation results demonstrate the MMF rate performance gains obtained by the proposed IRS-aided RSMA system compared with several baseline schemes.
机译:在本文中,我们考虑了用于智能反射表面(IRS)的MAX-MIN公平(MMF)传输 - 辅助多用户多输入单输出(MU-MISO)速率分裂多次访问(RSMA)下行链路系统。我们的资源分配设计旨在通过在IRS处优化发射机和反射相移矢量的发射波束形成器来最大化多个单天线用户之间的最小传输速率。为此,将算法设计配制为混合的非凸和组合优化问题,这考虑了离散相移和最大传输功率预算。为了解决设计优化问题的诡计问题,利用连续的凸近似(SCA)技术,惩罚方法和交替优化(AO)方法来设计用于获得所考虑的问题的有效解决方案的次优迭代算法。仿真结果表明,与若干基线方案相比,所提出的IRS辅助RSMA系统获得的MMF速率性能增益。

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