标题： 用于增强RIS辅助的无蜂窝大规模MIMO聚合信道估计的改进差分进化算法 显示英文标题

标题： Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO

摘要： 基于可重构智能表面（RIS）的支持，研究了无基站的大规模多输入多输出（MIMO）系统。 在存在空间相关性的情况下，设计了RIS相位偏移以改进信道估计。 具体而言，我们使用线性最小均方误差（LMMSE）估计来推导聚合信道的信道估计和估计误差表达式。 然后，制定了一个优化问题，在实际相位偏移约束下最小化平均归一化均方误差（NMSE）。 为了克服固有的非凸性问题，我们构思了差分进化算法的一种增强版本，该算法通过引入应用于一些高性能差分进化（DE）个体的增强算子，能够避免局部最小值。 数值结果表明，我们提出的算法可以显著提高现有最先进基准的信道估计质量。 显示英文摘要

摘要： Cell-Free Massive multiple-input multiple-output (MIMO) systems are investigated with the support of a reconfigurable intelligent surface (RIS). The RIS phase shifts are designed for improved channel estimation in the presence of spatial correlation. Specifically, we formulate the channel estimate and estimation error expressions using linear minimum mean square error (LMMSE) estimation for the aggregated channels. An optimization problem is then formulated to minimize the average normalized mean square error (NMSE) subject to practical phase shift constraints. To circumvent the problem of inherent nonconvexity, we then conceive an enhanced version of the differential evolution algorithm that is capable of avoiding local minima by introducing an augmentation operator applied to some high-performing Diffential Evolution (DE) individuals. Numerical results indicate that our proposed algorithm can significantly improve the channel estimation quality of the state-of-the-art benchmarks.