PCA-based Antenna Impedance Estimation in Rayleigh Fading Channels

TL;DR

This paper introduces a new real-time antenna impedance estimation method for Rayleigh fading channels, improving capacity by enabling adaptive matching at MISO receivers.

Contribution

It derives the optimal ML estimator for antenna impedance in correlated Rayleigh fading and proposes a computationally efficient principal-components approach for practical implementation.

Findings

The estimator achieves near-optimal performance in simulations.

Adaptive impedance matching significantly boosts ergodic capacity.

The method is computationally efficient for real-time applications.

Abstract

Impedance matching between receive antenna and front-end significantly impacts channel capacity in wireless channels. To implement capacity-optimal matching, the receiver must know the antenna impedance. But oftentimes this impedance varies with loading conditions in the antenna near-field. To mitigate this variation, several authors have proposed antenna impedance estimation techniques. However, the optimality of these techniques remains unclear. In this paper, we consider antenna impedance estimation at MISO receivers over correlated Rayleigh fading channels. We derive in closed-form the optimal ML estimator under i.i.d. fading and then show it can be found via a scalar optimization in generally correlated fading channels. Numerical results suggest a computationally efficient, principal-components approach that estimates antenna impedance in real-time for all Rayleigh fading channels. Furthermore, ergodic capacity can be significantly boosted at originally poorly matched receivers with adaptive matching using our proposed approach.