This paper studies the fair transmission design for an intelligent reflecting surface (IRS) aided rate-splitting multiple access (RSMA). IRS is used to establish a good signal propagation environment and enhance the RSMA transmission performance. The fair rate adaption problem is constructed as a max-min optimization problem. To solve the optimization problem, we adopt an alternative optimization (AO) algorithm to optimize the power allocation, beamforming, and decoding order, respectively. A generalized power iteration (GPI) method is proposed to optimize the receive beamforming, which can improve the minimum rate of devices and reduce the optimization complexity. At the base station (BS), a successive group decoding (SGD) algorithm is proposed to tackle the uplink signal estimation, which trades off the fairness and complexity of decoding. At the same time, we also consider robust communication with imperfect channel state information at the transmitter (CSIT), which studies robust optimization by using lower bound expressions on the expected data rates. Extensive numerical results show that the proposed optimization algorithm can significantly improve the performance of fairness. It also provides reliable results for uplink communication with imperfect CSIT.

翻译：本文研究了一种智能反射面（IRS）辅助速率分割多址（RSMA）中的公平传输设计。IRS用于建立良好的信号传播环境并提升RSMA传输性能。将公平速率适配问题构建为最大化最小速率优化问题。为解决该优化问题，我们采用交替优化（AO）算法分别优化功率分配、波束成形和解码顺序。提出广义功率迭代（GPI）方法优化接收波束成形，该方法可提升设备最小速率并降低优化复杂度。在基站（BS）处，提出逐组连续解码（SGD）算法处理上行信号估计，该算法平衡了公平性与解码复杂度。同时，我们还考虑了发射端不完美信道状态信息（CSIT）下的鲁棒通信，通过期望数据速率的低界表达式研究鲁棒优化。大量数值结果表明，所提出的优化算法能显著提升公平性性能，且在不完美CSIT条件下为上行通信提供了可靠结果。