MIMO Systems with Reconfigurable Antennas: Joint Channel Estimation and Mode Selection

TL;DR

This paper introduces a low-complexity iterative mode selection algorithm and a channel estimation scheme for reconfigurable antenna MIMO systems, improving efficiency and reducing overhead in wireless communications.

Contribution

It presents a novel joint mode selection and channel estimation framework tailored for RA-MIMO systems, addressing computational complexity and estimation overhead challenges.

Findings

The proposed algorithm reduces mode selection complexity.

Channel estimation accuracy improves with the subset training approach.

Achievable sum-rate increases with optimized mode selection and SNR.

Abstract

Reconfigurable antennas (RAs) are a promising technology to enhance the capacity and coverage of wireless communication systems. However, RA systems have two major challenges: (i) High computational complexity of mode selection, and (ii) High overhead of channel estimation for all modes. In this paper, we develop a low-complexity iterative mode selection algorithm for data transmission in an RA-MIMO system. Furthermore, we study channel estimation of an RA multi-user MIMO system. However, given the coherence time, it is challenging to estimate channels of all modes. We propose a mode selection scheme to select a subset of modes, train channels for the selected subset, and predict channels for the remaining modes. In addition, we propose a prediction scheme based on pattern correlation between modes. Representative simulation results demonstrate the system's channel estimation error and achievable sum-rate for various selected modes and different signal-to-noise ratios (SNRs).