A CSI Compression Scheme Using Context Trees

Abstract

We propose novel compression algorithms for timevarying channel state information (CSI) in wireless communications. The proposed schemes combine (lossy) vector quantisation and (lossless) compression. The vector quantisation technique is based on data-adapted parametrised companders applied on each component of the normalised vector. Then, the sequences of quantisation indices are compressed according to estimated distributions computed with a context-tree approach. The algorithms have low complexity, are linear-time in spatial dimension and time duration, and can be implemented in an online fashion. We run numerical experiments to demonstrate the effectiveness of the proposed algorithms in such scenarios.