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

Abstract

For frequency division duplex channels, a simple pilot loop-back procedure has been proposed that allows the estimation of the UL & DL channels at an antenna array without relying on any digital signal processing at the terminal side. For this scheme, we derive the maximum likelihood (ML) estimators for the UL & DL channel subspaces, formulate the corresponding Cramér-Rao bounds and show the asymptotic efficiency of both (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 & DL channels have on average the same gain, we formulate the ML estimator for the channel norm, and illustrate its robustness against strong noise by means of simulations.

Submitted to IEEE Transactions on Signal Processing, 12 pages, 7 figures

References in corpus (2)

• Distributed Compressive CSIT Estimation and Feedback for FDD Multi-user Massive MIMO Systems
• Joint CSIT Acquisition Based on Low-Rank Matrix Completion for FDD Massive MIMO Systems

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