This paper discusses the unambiguous estimation of high-order BOC signals in the cloud based on signal snapshots gathered by low-end SDR receivers. In particular, the sensitivity and distortion problems are introduced, assessing the probability of false lock when using a conventional ML-based estimator (based on the search of the absolute maximum of the cross-correlation function) and a post-correlation ML-based estimator exploiting the a priori known distortion of the cross-correlation function introduced by the filtering stage of the SDR receiver. The simulation results show that, while distortion issues can be handled, sensitivity remains a problem at low C/No conditions and when limited snapshot lengths are considered.

Peer Reviewed