Blind Channel Estimation for Ambient Backscatter Communication Systems

TLDR

The availability of perfect channel state information is assumed in current ambient‑backscatter studies, yet channel estimation differs from traditional wireless systems where training symbols are used. This letter proposes a blind channel estimator based on the expectation‑maximization algorithm to acquire the modulus values of channel parameters. The authors determine suitable initial value ranges for the estimator and derive a modified Bayesian Cramér‑Rao bound. Simulation results confirm the theoretical analysis.

Abstract

The availability of perfect channel state information is assumed in current ambient-backscatter studies. However, the channel estimation problem for ambient backscatter is radically different from that for traditional wireless systems, where it is common to transmit training (pilot) symbols for this purpose. In this letter, we thus propose a blind channel estimator based on the expectation maximization algorithm to acquire the modulus values of channel parameters. We also obtain the ranges of the initial values of the suggested estimator and derive the modified Bayesian Cramér-Rao bound of the proposed estimator. Finally, simulation results are provided to corroborate our theoretical studies.