Demo Data from EDBT 2026 / reviewers in the wild / expert
David S. Millar
dblp:210/5401
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0002-6381-0604ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
2 papers |
Coding theory · 72% Information theory · 28% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › constrained coding
constant-composition distribution matching |
0.8 | 2 | 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching · IEEE Trans. Commun. 2020 Multiset-Partition Distribution Matching · IEEE Trans. Commun. 2019 |
Information theory
distribution matching |
0.8 | 2 | 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching · IEEE Trans. Commun. 2020 Multiset-Partition Distribution Matching · IEEE Trans. Commun. 2019 |
Coding theory › error-correcting codes › coded modulation
probabilistic amplitude shaping |
0.8 | 2 | 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching · IEEE Trans. Commun. 2020 Multiset-Partition Distribution Matching · IEEE Trans. Commun. 2019 |
Coding theory › error-correcting codes
coded modulation |
0.2 | 2 | 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching · IEEE Trans. Commun. 2020 Multiset-Partition Distribution Matching · IEEE Trans. Commun. 2019 |
Coding theory › error-correcting codes › coded modulation
quadrature amplitude modulation |
0.2 | 2 | 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching · IEEE Trans. Commun. 2020 Multiset-Partition Distribution Matching · IEEE Trans. Commun. 2019 |
Methods — techniques the papers use, named apart from their topics
arithmetic coding · 0.8parallel architecture design · 0.4multiset partitioning · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution MatchingabstractA distribution matcher (DM) maps a binary input sequence into a block of nonuniformly distributed symbols. To facilitate the implementation of shaped signaling, fast DM solutions with high throughput and low serialism are required. We propose a novel DM architecture with parallel amplitudes (PA-DM) for which m-1 component DMs, each with a different binary output alphabet, are operated in parallel in order to generate a shaped sequence with m amplitudes. With negligible rate loss compared to a single nonbinary DM, PA-DM has a parallelization factor that grows linearly with m, and the component DMs have reduced output lengths. For such binary-output DMs, a novel constant-composition DM (CCDM) algorithm based on subset ranking (SR) is proposed. We present SR-CCDM algorithms that are serial in the minimum number of occurrences of either binary symbol for mapping, and fully parallel for demapping. For distributions that are optimized for the additive white Gaussian noise (AWGN) channel, we numerically show that PA-DM combined with SR-CCDM can reduce the number of sequential processing steps by more than an order of magnitude, while having a rate loss that is comparable to conventional nonbinary CCDM with arithmetic coding. Tobias Fehenberger, David S. Millar, Toshiaki Koike-Akino, Keisuke Kojima, Kieran Parsons |
IEEE Trans. Commun. | 2 |
| 2019 | Multiset-Partition Distribution MatchingabstractDistribution 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. Tobias Fehenberger, David S. Millar, Toshiaki Koike-Akino, Keisuke Kojima, Kieran Parsons |
IEEE Trans. Commun. | 2 |