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Efficient Channel Prediction for Beyond Diagonal RIS-Assisted MIMO Systems with Channel Aging by Ginige, Nipuni; de Sena, Arthur Sousa; Mahmood, Nurul Huda; Rajatheva, Nandana; Latva-aho, Matti is a scholarly article available to read on EtoBox.

What is Efficient Channel Prediction for Beyond Diagonal RIS-Assisted MIMO Systems with Channel Aging about?

Novel reconfigurable intelligent surface (RIS) architectures, known as beyond diagonal RISs (BD-RISs), have been proposed to enhance reflection efficiency and expand RIS capabilities. However, their passive nature, non-diagonal reflection matrix, and the large number of coupled reflecting elements complicate the channel state information (CSI) estimation process. The challenge further escalates in scenarios with fast-varying channels. In this paper, we address this challenge by proposing novel joint channel estimation and prediction strategies with low overhead and high accuracy for two different RIS architectures in a BD-RIS-assisted multiple-input multiple-output system under correlated fast-fading environments with channel aging. The channel estimation procedure utilizes the Tucker2 decomposition with bilinear alternative least squares, which is exploited to decompose the cascade channels of the BD-RIS-assisted system into effective channels of reduced dimension. The channel prediction framework is based on a convolutional neural network combined with an autoregressive predictor. The estimated/predicted CSI is then utilized to optimize the RIS phase shifts aiming at the maximiza

Author

Ginige, Nipuni; de Sena, Arthur Sousa; Mahmood, Nurul Huda; Rajatheva, Nandana; Latva-aho, Matti

Published

2024

Language

EN