Ludwick Kurz

dblp:165/3708 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1987
—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 · 79% Vehicular, aerial and satellite networks · 21%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
equalization
0.011987
A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels · IEEE Trans. Commun. 1987
Physical-layer communications › equalization
MMSE equalization
0.011987
A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels · IEEE Trans. Commun. 1987
Physical-layer communications
modulation
0.011987
A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels · IEEE Trans. Commun. 1987
Vehicular, aerial and satellite networks › satellite communication
nonlinear channel
0.011987
A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels · IEEE Trans. Commun. 1987
Vehicular, aerial and satellite networks
satellite communication
0.011987
A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels · IEEE Trans. Commun. 1987

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

minimum mean square error estimation · 0.0computer simulation · 0.0
YearPublicationVenuePosition
1987 A Minimum Mean-Square Error Equalizer for Nonlinear Satellite Channels
abstract
The problem of designing and evaluating the performance of a minimum mean-square error equalizer (MMSEE) for binary PSK transmission over band-limited nonlinear satellite channels is considered in this correspondence. The effect of intersymbol interference followed by AM/AM and AM/PM conversions are taken into account while optimizing the performance in the presence of the downlink white Gaussian noise. In analyzing the problem, the decision is made on a typical signal in a received sequence taking into account past and future interfering signals, i.e., ISI. As an illustrative example of the receiver, a typical channel model is considered in details. Based on the analysis, an alternative receiver structure which is more suitable for implementation is introduced. The taps gain coefficients for minimum mean-square error, between the received sample and the actual transmitted bit, are obtained using numerical methods. The performance of the equalizer is evaluated using computer simulation techniques and it is shown that significant performance improvement over the single-sample sign detector can be obtained.
Aly F. Elrefaie, Ludwick Kurz
IEEE Trans. Commun.2