Binary BMST Coding for Near-Lossless Compression of Q-Ary Source

In this paper, we propose a new coding approach to near-lossless compression of $Q$-ary sources by utilizing a sparsifier and block Markov superposition transmission (BMST) codes. The symbols from a $Q$-ary source are mapped to fixedlength binary vectors by the sparsifier such that the symbols with higher probabilities are mapped to vectors of lower weights. The binary sparse sequences are then compressed in a BMST manner. The most distinguished feature of the proposed source coding is that the error propagation can be mitigated in the presence of noise. Numerical results show that the proposed scheme performs well for $Q$-ary sources, providing a universal but simple way to achieve near-lossless coding at rates approaching the source entropy.