A distribution matcher (DM) encodes a binary input data sequence into a sequence of symbols with a desired target probability distribution. Several DMs, including shell mapping and constant-composition distribution matcher (CCDM), have been successfully employed for signal shaping, e.g., in opticalfiber or 5G. The CCDM, like many other DMs, is typically implemented by arithmetic coding (AC). In this work we implement AC based DMs using finite-precision arithmetic (FPA). An analysis of the implementation shows that FPA results in a rate-loss that shrinks exponentially with the number of precision bits. Moreover, a relationship between the CCDM rate and the number of precision bits is derived.
A distribution matcher (DM) encodes a binary input data sequence into a sequence of symbols (codeword) with desired target probability distribution. The set of the output codewords constitutes a codebook (or code) of a DM. Constantcomposition DM (CCDM) uses arithmetic coding to efficiently encode data into codewords from a constant-composition (CC) codebook. The CC constraint limits the size of the codebook, and hence the coding rate of the CCDM. The performance of CCDM degrades with decreasing output length. To improve the performance for short transmission blocks we present a class of multi-composition (MC) codes and an efficient arithmetic coding scheme for encoding and decoding. The resulting multicomposition DM (MCDM) is able to encode more data into distribution matched codewords than the CCDM and achieves lower KL divergence, especially for short block messages.
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