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Jeremy Turner

dblp:29/8707 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel coding and estimation
0.112009
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
0.112009
Reduced complexity decoding of space time trellis codes in the frequency selective channel · IEEE Trans. Commun. 2009
Physical-layer communications
MIMO
0.112009
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
0.112009
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
YearPublicationVenuePosition
2009 Reduced complexity decoding of space time trellis codes in the frequency selective channel
abstract
An 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