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Ori Peled

dblp:204/4272 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0002-0698-320XORCID · reported

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

Theory of computation · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 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.

Theoretical computer science
1 paper
Coding theory · 60% Information theory · 40%

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

TopicWeightPapersLastEvidence papers
Information theory
channel capacity
0.412019
Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC · IEEE Trans. Inf. Theory 2019
Coding theory
channel coding
0.412019
Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC · IEEE Trans. Inf. Theory 2019
Coding theory
constrained coding
0.412019
Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC · IEEE Trans. Inf. Theory 2019
Information theory › channel capacity
feedback capacity
0.412019
Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC · IEEE Trans. Inf. Theory 2019
Coding theory › constrained coding
runlength-limited codes
0.412019
Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC · IEEE Trans. Inf. Theory 2019
YearPublicationVenuePosition
2019 Feedback Capacity and Coding for the (0, k)-RLL Input-Constrained BEC
Ori Peled, Oron Sabag, Haim H. Permuter
IEEE Trans. Inf. Theory1
2017 Feedback capacity and coding for the (0, k)-RLL input-constrained BEC
abstract
The input-constrained binary erasure channel (BEC) with strictly causal feedback is studied. The channel input sequence must satisfy the (0, k)-runlength limited (RLL) constraint, i.e., no more than k consecutive `0's are allowed. The feedback capacity of this channel is derived for all k ≥ 1, and is given by C(0,k)fb(ε) = max ε̅H2(δ0)+Σi=1k-1(εi+1H2(δi) Πm=0i-1δm)/1+Σi=0k-1(ε̅i+1Πm=0iδm) where ε is the erasure probability, ε̅ = 1 - ε and H2(·) is the binary entropy function. The maximization is only over δk-1, while the parameters δifor i ≤ k - 2 are straightforward functions of δk-1. The lower bound is obtained by constructing a simple coding for all k ≥ 1. It is shown that the feedback capacity can be achieved using zero-error, variable length coding. For the converse, an upper bound on the non-causal setting, where the erasure is available to the encoder just prior to the transmission, is derived. This upper bound coincides with the lower bound and concludes the search for both the feedback capacity and the non-causal capacity. As a result, non-causal knowledge of the erasures at the encoder does not increase the feedback capacity for the (0, k)-RLL input-constrained BEC. This property does not hold in general: the (2, ∞)-RLL input-constrained BEC, where every `1' is followed by at least two `0's, is used to show that the feedback capacity can be strictly smaller than the non-causal capacity.
Ori Peled, Oron Sabag, Haim H. Permuter
ISIT1