Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

TL;DR

This paper introduces analog-domain LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems, reducing digital computation and hardware costs while maintaining estimation performance.

Contribution

It proposes novel analog-domain training schemes for channel estimation in MiLAC-aided MIMO systems, enabling fully analog processing with reduced hardware and computational complexity.

Findings

Achieves digital-equivalent estimation performance in analog domain

Reduces hardware complexity and power consumption

Numerical results confirm effectiveness and advantages

Abstract

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the benefits offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing training precoders and combiners implemented by MiLACs, both LS and MMSE estimation are performed fully in the analog domain, achieving identical performance to their digital counterparts while significantly reducing computational complexity, transmit RF chains, analog-to-digital/digital-to-analog converters (ADCs/DACs) resolution requirements, and peak-to-average power ratio (PAPR). Numerical results verify the effectiveness and advantages of the proposed schemes.