2023 journal article
A Principal-Component Approach to Antenna Impedance Estimation at MISO Receivers
IEEE COMMUNICATIONS LETTERS, 27(1), 288–292.
author keywords: Impedance; Maximum likelihood estimation; Receiving antennas; Training; MISO communication; Antennas; Transmitting antennas; Antenna impedance estimation; maximum-likelihood estimator; eigen-decomposition
TL;DR:
This letter study at MISO receivers over Rayleigh fading channels and derive the optimal ML estimator in closed-form, suggesting a computationally efficient, principal-components approach that estimates antenna impedance in real-time and shows sizable improvement against a reference estimator at low SNR.
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Added: March 13, 2023
Impedance matching between receive antenna and front-end significantly impacts channel capacity in wireless channels. To implement the optimal matching, the receiver must know the antenna impedance. This impedance varies with the antenna’s loading conditions. Techniques are derived to estimate antenna impedance, but the optimality of these techniques remains unclear. In this letter, we study antenna impedance estimation at MISO receivers over Rayleigh fading channels and derive the optimal ML estimator in closed-form. Numerical results suggest a computationally efficient, principal-components approach that estimates antenna impedance in real-time and shows sizable improvement against a reference estimator at low SNR.