In this paper, we propose an optimization framework for rate splitting (RS) techniques in multiple-input multiple-output (MIMO) reconfigurable intelligent surface (RIS)-assisted systems, possibly with I/Q imbalance (IQI). This framework can be applied to any optimization problem in which the objective and/or constraints are linear functions of the rates and/or transmit covariance matrices. Such problems include minimum-weighted and weighted-sum rate maximization, total power minimization for a target rate, minimum-weighted energy efficiency (EE) and global EE maximization. The framework may be applied to any interference-limited system with hardware impairments. For the sake of illustration, we consider a multicell MIMO RIS-assisted broadcast channel (BC) in which the base stations (BSs) and/or the users may suffer from IQI. Since IQI generates improper noise, we consider improper Gaussian signaling (IGS) as an interference-management technique that can additionally compensate for IQI. We show that RS when combined with IGS can substantially improve the spectral and energy efficiency of overloaded networks (i.e., when the number of users per cell is larger than the number of transmit/receive antennas).

翻译：在本文中,我们提议一个最佳框架,用于多投入多输出(MSIMO)可重新配置智能表面辅助系统(RIS)的分率技术(RS)的优化框架,可能的话可以使用I/Q不平衡(IQI)。这个框架可以适用于目标或限制是费率线性功能和(或)传输共差矩阵的任何优化问题。这些问题包括:最小加权和加权总利率最大化、目标速率的全功率最小化、最小加权能效和全球EEE最大化。这个框架可以适用于任何有硬件缺陷的干扰有限系统。为了说明起见,我们考虑建立一个多细胞IMO-辅助广播频道(BC),基站和(或)用户可能因IQI而受害。由于IQI产生不适当的噪音,我们认为高频信号(IGS)不适当,是一种干扰管理技术,可以进一步补偿IQI。我们表明,如果与IGS(E)结合,可以大幅度提高超载天线网络的光谱和能量效率(i.e.i.i.)的用户数目大于每个传输的频率,则显示RS(e.e.)。