Tal Kaitz

dblp:16/10713 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
equalization
0.012000
A reduced-complexity algorithm for combined equalization and decoding · IEEE Trans. Commun. 2000
Physical-layer communications › equalization
joint equalization and decoding
0.012000
A reduced-complexity algorithm for combined equalization and decoding · IEEE Trans. Commun. 2000
Physical-layer communications › signal detection › sequence estimation
reduced-state sequence estimation
0.012000
A reduced-complexity algorithm for combined equalization and decoding · IEEE Trans. Commun. 2000

Methods — techniques the papers use, named apart from their topics

estimated future decision-feedback algorithm · 0.0adaptive equalization · 0.0
YearPublicationVenuePosition
2000 A reduced-complexity algorithm for combined equalization and decoding
abstract
This paper presents a new application of a suboptimal trellis decoding algorithm for combined equalization and decoding. The proposed algorithm can outperform the reduced-state sequence estimator (RSSE) of the same order of complexity. The algorithm, termed estimated future decision-feedback algorithm (EFDFA), was originally proposed for the problem of noncoherent decoding with multiple-symbol overlapped observations and is now reformulated for the problem of intersymbol interference inflicted channels. The EFDFA uses the RSSE as a building block. The performance improvement is achieved by using estimated future symbols in the decision process. The estimated future symbols are obtained by RSSE decoding time-reversed blocks of the input. The same technique can be used to greatly enhance the performance of the conventional decision-feedback equalizer. An analysis of the performance of the EFDFA based on the performance of the RSSE is described. The EFDFA can be configured as an adaptive equalizer capable of operating in a time-varying environment, and is shown to perform well in fading conditions. With only minor additional complexity, the EFDFA is also capable of producing soft outputs.
Dan Raphaeli, Tal Kaitz
IEEE Trans. Commun.2