Demo Data from EDBT 2026 / reviewers in the wild / expert
Jeremy Turner
dblp:29/8707
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author
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.
| Computer networks
1 paper |
Physical-layer communications · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications
channel coding and estimation |
0.1 | 1 | 2009 | Reduced complexity decoding of space time trellis codes in the frequency selective channel · IEEE Trans. Commun. 2009 |
Physical-layer communications › equalization
joint equalization and decoding |
0.1 | 1 | 2009 | Reduced complexity decoding of space time trellis codes in the frequency selective channel · IEEE Trans. Commun. 2009 |
Physical-layer communications
MIMO |
0.1 | 1 | 2009 | Reduced complexity decoding of space time trellis codes in the frequency selective channel · IEEE Trans. Commun. 2009 |
Physical-layer communications › channel coding › decoding algorithms
reduced-complexity decoding |
0.1 | 1 | 2009 | Reduced complexity decoding of space time trellis codes in the frequency selective channel · IEEE Trans. Commun. 2009 |
Methods — techniques the papers use, named apart from their topics
soft-output viterbi algorithm · 0.1partitioned viterbi algorithm · 0.1maximum-likelihood decoding · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Reduced complexity decoding of space time trellis codes in the frequency selective channelabstractAn iterative approach is developed for decoding space time trellis codes (STTCs) in frequency selective multiple input multiple output (MIMO) channels. The method uses the partitioned Viterbi algorithm (PVA) as an equaliser for the MIMO system. It is used iteratively with a STTC decoder that provides soft outputs using the soft output Viterbi algorithm (SOVA). It is shown through simulation that the iterative procedure achieves a performance within 2.0 dB of maximum likelihood (ML) decoding, at a FER of 10-2, but suffers a small diversity loss. It is also shown that the complexity of the iterative approach is lower than that of ML decoding. Jeremy Turner, Desmond P. Taylor |
IEEE Trans. Commun. | 1 |