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arXiv 2108.09002eess.SP
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智能反射面辅助多用户MISO系统的级联信道估计

Cascaded Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser MISO Systems

Huayan Guo, Vincent K. N. Lau

摘要:

研究了智能反射面(IRS)辅助的多用户多输入单输出系统上行链路级联信道估计。我们专注于一个子-6 GHz的情况下,信道传播不是稀疏的,IRS元素的数量可以大于BS天线的数量。提出了一种新的信道估计协议,该协议不需要进行开-关幅度控制以避免反射功率损失。此外,通过利用公共链路结构来分解级联的信道系数,通过将公共链路变量与用户特定变量相乘,大大减少了导频开销。然而,这两种类型的变量是高度耦合的,这使得它们难以估计。为了解决这个问题,我们制定了一个基于优化的联合信道估计问题,它只利用级联信道的协方差。然后,我们设计了一个低复杂度的交替优化算法的非凸优化问题的有效初始化,它实现了局部最优解。为了进一步提高估计精度,我们提出了一种新的配方,以优化所提出的协议的训练相移配置,然后使用逐次凸逼近算法求解。综合仿真验证了所提出的算法具有最高的性能相比,各种国家的最先进的基线计划。

英文摘要:

This paper investigates the uplink cascaded channel estimation for intelligent-reflecting-surface (IRS)-assisted multi-user multiple-input-single-output systems. We focus on a sub-6 GHz scenario where the channel propagation is not sparse and the number of IRS elements can be larger than the number of BS antennas. A novel channel estimation protocol without the need of on-off amplitude control to avoid the reflection power loss is proposed. In addition, the pilot overhead is substantially reduced by exploiting the common-link structure to decompose the cascaded channel coefficients by the multiplication of the common-link variables and the user-specific variables. However, these two types of variables are highly coupled, which makes them difficult to estimate. To address this issue, we formulate an optimization-based joint channel estimation problem, which only utilizes the covariance of the cascaded channel. Then, we design a low-complexity alternating optimization algorithm with efficient initialization for the non-convex optimization problem, which achieves a local optimum solution. To further enhance the estimation accuracy, we propose a new formulation to optimize the training phase shifting configuration for the proposed protocol, and then solve it using the successive convex approximation algorithm. Comprehensive simulations verify that the proposed algorithm has supreme performance compared to various state-of-the-art baseline schemes.

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