Channel Training for Analog FDD Repeaters: Optimal Estimators and Cramér–Rao Bounds

View Researcher's Other Codes

Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).

Please contact us in case of a broken link from here

Authors Stefan Wesemann, T. Marzetta
Journal/Conference Name IEEE Transactions on Signal Processing
Paper Category
Paper Abstract For frequency division duplex channels, a simple pilot loop-back procedure has been proposed that allows the estimation of the uplink (UL) and downlink (DL) channel subspaces between an antenna array and a fully analog repeater. For this scheme, we derive the maximum likelihood (ML) estimators for the UL and DL subspaces, formulate the corresponding Cramér–Rao bounds, and show the asymptotic efficiency of both (singular value decomposition (SVD) based) estimators by means of Monte Carlo simulations. In addition, we illustrate how to compute the underlying (rank-1) SVD with quadratic time complexity by employing the power iteration method. To enable power control for the data transmission, knowledge of the channel gains is needed. Assuming that the UL and DL channels have on average the same gain, we formulate the ML estimator for the uplink channel vector norm, and illustrate its robustness against strong noise perturbations by means of simulations.
Date of publication 2017
Code Programming Language R

Copyright Researcher 2022