Capacity and Sensitivity Analysis of MISO Receivers with Antenna Impedance Estimation

This paper presents a novel, fast algorithm for ML estimation of antenna impedance in MISO systems under correlated Rayleigh fading. Our analysis reveals how ergodic capacity depends on the precision of antenna impedance estimates, channel estimation errors, and mismatches in the channel correlation matrix and noise variances. In a numerical simulation, we demonstrate that our proposed algorithm can recover 4 to 5 dB of loss due to impedance mismatch, using only a few training sequences. It also surpasses a state-of-the-art method by approximately 9 dB in capacity at low SNR. These results underscore the effectiveness of our approach in improving system performance in real-time scenarios.