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Antenna Impedance Estimation in Correlated Rayleigh Fading Channels
July 07, 2023 Β· Declared Dead Β· π IEEE International Conference on Acoustics, Speech, and Signal Processing
"No code URL or promise found in abstract"
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Authors
Shaohan Wu, Brian Hughes
arXiv ID
2307.03600
Category
cs.IT: Information Theory
Cross-listed
eess.SP
Citations
1
Venue
IEEE International Conference on Acoustics, Speech, and Signal Processing
Last Checked
4 months ago
Abstract
We formulate antenna impedance estimation in a classical estimation framework under correlated Raleigh fading channels. Based on training sequences of multiple packets, we derive the ML estimators for antenna impedance and channel variance, treating the fading path gains as nuisance parameters. These ML estimators can be found via scalar optimization. We explore the efficiency of these estimators against Cramer-Rao lower bounds by numerical examples. The impact of channel correlation on impedance estimation accuracy is investigated.
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