Kalman Filter Based Channel Tracking for RIS-Assisted Multi-User Networks
Kalman Filter Based Channel Tracking for RIS-Assisted Multi-User Networks
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DOI：
10.1109/twc.2023.3312426
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发表时间：
2024-04
影响因子：
10.4
通讯作者：
Danyang Yu;Gan Zheng;Arman Shojaeifard;S. Lambotharan;Yi Liu
中科院分区：
文献类型：
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作者：
Danyang Yu;Gan Zheng;Arman Shojaeifard;S. Lambotharan;Yi Liu
在本文中，我们研究了可重构智能表面（RIS）辅助多用户网络中的信道估计，同时考虑了用户的移动性。基于时变信道模型，我们利用卡尔曼滤波器（KF），它能够利用时间相关性来跟踪级联信道。为了保持相对较低的导频开销，我们提出了一种基于多个子阶段的传输协议，其中每个子阶段中的导频序列的数量小于用户的数量，即存在导频污染。为了实用性，我们直接利用离散傅里叶变换（DFT）矩阵作为相移矩阵。我们分析归一化均方误差并提供一些渐近结果。还考虑了收发器和 RIS 处存在硬件损伤 (HWI) 的更实际场景。由于HWI也是测量矩阵的一部分并且对于基站来说是未知的，因此我们提出信道和HWI的联合估计。在这种联合估计框架下，底层状态空间模型变得非线性。我们开发了一种扩展的 KF (EKF) 算法来解决非线性问题，通过该算法可以对模型进行线性化。数值结果表明，所提出的 KF 和 EKF 算法在各种场景下都优于基准方案。
In this paper, we investigate channel estimation in a reconfigurable intelligent surface (RIS) assisted multi-user network while taking the mobility of users into consideration. Based on a time-varying channel model, we utilize Kalman filter (KF) that is able to exploit temporal correlation to track cascaded channel. In order to maintain a relatively low pilot overhead, we present a multiple sub-phases based transmission protocol where the number of pilot sequences in each sub-phase is less than the number of users, i.e., pilot contamination exists. For the sake of practicality, we directly utilize discrete Fourier transform (DFT) matrix as phase shift matrix. We analyze normalized mean square error and provide some asymptotic results. A more practical scenario with hardware impairments (HWI) at the transceiver and the RIS is also considered. Since HWI is also part of the measurement matrix and is unknown to the base station, we propose a joint estimation of the channel and HWI. Under this joint estimation framework, the underlying state space model becomes nonlinear. We develop an extended KF (EKF) algorithm to tackle the nonlinearity through which the model can be linearized. Numerical results show that the proposed KF and EKF algorithms outperform benchmark schemes under various scenarios.