Reconfigurable intelligent surfaces (RISs) have emerged as a prospective technology for next-generation wireless networks due to their potential in coverage and capacity enhancement. The analysis and optimization of ergodic capacity for RIS-assisted communication systems have been investigated extensively. However, the Rayleigh or Rician channel model is usually utilized in the existing work, which is not suitable for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. Thus, we fill the gap and consider the ergodic capacity of RIS-assisted mmWave MIMO communication systems under the Saleh-Valenzuela channel model. Firstly, we derive tight approximations of ergodic capacity and a tight upper bound in high signal-to-noise ratio regime. Then, we aim to maximize the ergodic capacity by jointly designing the transmit covariance matrix at the base station and the reflection coefficients at the RIS. Specifically, the transmit covariance matrix is optimized by the water-filling algorithm and the reflection coefficients are optimized using the Riemanian conjugate gradient algorithm. Simulation results validate the tightness of the derived ergodic capacity approximations and the effectiveness of the proposed algorithms.
翻译:重新配置的智能表面(RIS)由于在覆盖面和能力增强方面的潜力,已成为下一代无线网络的潜在技术,因此成为下一代无线网络的潜在技术。分析和优化了RIS辅助通信系统的人造能力,已经进行了广泛的调查,然而,Raylei或Rician频道模型通常用于现有工作,不适用于毫米波(mmWave)多输入多输出(MIMO)系统。因此,我们填补了缺口,并审议了在Saleh-Valenzuela频道模型下,RIS-辅助毫米Wave MIMO通信系统的超能力。首先,我们得出了ERGadi能力近似值,高信号至噪音比率制度的高度约束。然后,我们的目标是通过联合设计基地站的传输常变异矩阵和RIS的反射系数,最大限度地扩大电子能力。具体地说,通过填水算法优化了传输变异矩阵,而反系数则利用Riemanigate 梯度梯度计算法的优化了Riemanicatealgalations 。Simgoalationalationalations 。