Name
Abstract | ||
|---|---|---|
Distribution matching is a fixed-length invertible mapping from a uniformly distributed bit sequence to shaped amplitudes and plays an important role in the probabilistic amplitude shaping framework. With conventional constant-composition distribution matching (CCDM), all output sequences have identical composition. In this paper, we propose multiset-partition distribution matching (MPDM), where the composition is constant over all output sequences. When considering the desired distribution as a multiset, MPDM corresponds to partitioning this multiset into equal-sized subsets. We show that MPDM allows addressing more output sequences and, thus, has a lower rate loss than CCDM in all nontrivial cases. By imposing some constraints on the partitioning, a constructive MPDM algorithm is proposed which comprises two parts. A variable-length prefix of the binary data word determines the composition to be used, and the remainder of the input word is mapped with a conventional CCDM algorithm, such as arithmetic coding, according to the chosen composition. Simulations of 64-ary quadrature amplitude modulation over the additive white Gaussian noise channel demonstrate that the block-length saving of MPDM over CCDM for a fixed gap to capacity is approximately a factor of 2.5–5 at medium to high signal-to-noise ratios. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TCOMM.2018.2881091 | IEEE Transactions on Communications |
Keywords | DocType | Volume |
Forward error correction,Encoding,Probabilistic logic,Modulation,Partitioning algorithms,Signal to noise ratio,Distributed databases | Journal | 67 |
Issue | ISSN | Citations |
3 | 0090-6778 | 3 |
PageRank | References | Authors |
0.43 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Fehenberger | 1 | 52 | 8.59 |
| David S. Millar | 2 | 9 | 7.73 |
| Toshiaki Koike-Akino | 3 | 610 | 67.09 |
| Keisuke Kojima | 4 | 16 | 13.05 |
| Kieran Parsons | 5 | 38 | 13.60 |