论文标题

6G无线通信的能源有效的IRS辅助NOMA波束成形

Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications

论文作者

Ihsan, Asim, Chen, Wen, Asif, Muhammad, Khan, Wali Ullah, Li, Jun

论文摘要

该手稿为6G无线通信提供了基于智能反射表面(IRS)的智能反射表面(IRS)的智能优化框架。具体而言,这项工作为NOMA-BF系统提出了一个基于IRS的集中式设计,以优化发射机在第一阶段的发射器的主动横梁形成和功率分配系数(PAC),并在第二阶段在IRS上进行无源波束成形,以最大程度地提高网络的能量效率(EE)。但是,使用NOMA-BF系统的支持用户数量增加将导致NOMA用户干扰和集群间干扰(ICI)。为了减轻ICI的效果,利用了第一个零效率以及有效的用户聚类算法的效果,然后通过提出的迭代算法有效地解决了NOMA用户干扰,该算法通过在所需的系统约束下通过简化的封闭形式表达来计算NOMA用户的PAC。在第二阶段,通过基于频率差(DC)编程和连续的凸近近似(SCA)的技术解决了被动横梁形成的问题。仿真结果表明,提出的针对IRS辅助IRS辅助的NOMA-BF系统的交替框架可以在几次迭代中获得收敛性,并在系统的EE中提供有效的性能,其复杂性较低。

This manuscript presents an energy-efficient alternating optimization framework based on intelligent reflective surfaces (IRS) aided non-orthogonal multiple access beamforming (NOMA-BF) system for 6G wireless communications. Specifically, this work proposes a centralized IRS-enabled design for the NOMA-BF system to optimize the active beamforming and power allocation coefficient (PAC) of users at the transmitter in the first stage and passive beamforming at IRS in the 2nd stage to maximize the energy efficiency (EE) of the network. However, an increment in the number of supportable users with the NOMA-BF system will lead to NOMA user interference and inter-cluster interference (ICI). To mitigate the effect of ICI, first zero-forcing beamforming along with efficient user clustering algorithm is exploited and then NOMA user interference is tackled efficiently through a proposed iterative algorithm that computes PAC of NOMA user through simplified closed-form expression under the required system constraints. In the 2nd stage, the problem of passive beamforming is solved through a technique based on difference-of-convex (DC) programming and successive convex approximation (SCA). Simulation results demonstrate that the proposed alternating framework for energy-efficient IRS-assisted NOMA-BF system can achieve convergence within a few iterations and provide efficient performance in terms of EE of the system with low complexity.

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