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Victor Quintero

dblp:159/1748 · also Victor Manuel Quintero Florez · DBLP profile ↗
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5ranked-venue papers
5as first author
0since 2021 · last 2018
0000-0003-1897-1908ORCID · verified

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

Theory of computation · 3 · 3 first-authorComputer networks · 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
2 papers
Information theory · 100%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information theory
channel capacity
0.722018
Approximate Capacity Region of the Two-User Gaussian Interference Channel With Noisy Channel-Output Feedback · IEEE Trans. Inf. Theory 2018
When Does Output Feedback Enlarge the Capacity of the Interference Channel? · IEEE Trans. Commun. 2018
Information theory › network information theory › interference channel
gaussian interference channel
0.722018
Approximate Capacity Region of the Two-User Gaussian Interference Channel With Noisy Channel-Output Feedback · IEEE Trans. Inf. Theory 2018
When Does Output Feedback Enlarge the Capacity of the Interference Channel? · IEEE Trans. Commun. 2018
Information theory › network information theory
interference channel
0.722018
Approximate Capacity Region of the Two-User Gaussian Interference Channel With Noisy Channel-Output Feedback · IEEE Trans. Inf. Theory 2018
When Does Output Feedback Enlarge the Capacity of the Interference Channel? · IEEE Trans. Commun. 2018
Information theory › channel capacity
feedback capacity
0.312018
When Does Output Feedback Enlarge the Capacity of the Interference Channel? · IEEE Trans. Commun. 2018

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

linear deterministic approximation · 0.7rate splitting · 0.3genie-aided bounds · 0.3block-markov superposition coding · 0.3backward decoding · 0.3
YearPublicationVenuePosition
2018 Approximate Nash Region of the Gaussian Interference Channel with Noisy Output Feedback
abstract
In this paper, an achievable η-Nash equilibrium (η-NE) region for the two-user Gaussian interference channel with noisy channel-output feedback is presented for all η ≥ 1. This result is obtained in the scenario in which each transmitter-receiver pair chooses its own transmit-receive configuration in order to maximize its own individual information transmission rate. At an η-NE, any unilateral deviation by either of the pairs does not increase the corresponding individual rate by more than η bits per channel use.
Victor Quintero, Samir Perlaza, Jean-Marie Gorce, H. Vincent Poor
ITW1
2018 When Does Output Feedback Enlarge the Capacity of the Interference Channel?
abstract
In this paper, the benefits of channel-output feedback in the Gaussian interference channel (G-IC) are studied under the effect of additive Gaussian noise. Using a linear deterministic (LD) model, the signal to noise ratios (SNRs) in the feedback links beyond which feedback plays a significant role in terms of increasing the individual rates or the sum-rate are approximated. The relevance of this work lies in the fact that it identifies the feedback SNRs for which in any G-IC, one of the following statements is true: (a) feedback does not enlarge the capacity region; (b) feedback enlarges the capacity region and the sum-rate is greater than the largest sum-rate without feedback; and (c) feedback enlarges the capacity region but no significant improvement is observed in the sum-rate.
Victor Quintero, Samir Perlaza, Inaki Esnaola, Jean-Marie Gorce
IEEE Trans. Commun.1
2018 Approximate Capacity Region of the Two-User Gaussian Interference Channel With Noisy Channel-Output Feedback
abstract
In this paper, the capacity region of the linear deterministic interference channel with noisy channel-output feedback (LD-IC-NF) is fully characterized. The proof of achievability is based on random coding arguments and rate splitting, block-Markov superposition coding, and backward decoding. The proof of the converse reuses some of the existing outer bounds and includes new ones obtained using genie-aided models. Following the insight gained from the analysis of the LD-IC-NF, an achievability region and a converse region for the two-user Gaussian interference channel with noisy channel-output feedback (G-IC-NF) are presented. Finally, the achievability region and the converse region are proven to approximate the capacity region of the G-IC-NF to within 4.4 bits.
Victor Quintero, Samir Perlaza, Inaki Esnaola, Jean-Marie Gorce
IEEE Trans. Inf. Theory1
2017 Nash region of the linear deterministic interference channel with noisy output feedback
abstract
In this paper, the η-Nash equilibrium (η-NE) region of the two-user linear deterministic interference channel (IC) with noisy channel-output feedback is characterized for all η > 0. The η-NE region, a subset of the capacity region, contains the set of all achievable information rate pairs that are stable in the sense of an η-NE. More specifically, given an η-NE coding scheme, there does not exist an alternative coding scheme for either transmitter-receiver pair that increases the individual rate by more than η bits per channel use. Existing results such as the η-NE region of the linear deterministic IC without feedback and with perfect output feedback are obtained as particular cases of the result presented in this paper.
Victor Quintero, Samir Perlaza, Jean-Marie Gorce, H. Vincent Poor
ISIT1
2016 Approximate capacity of the Gaussian interference channel with noisy channel-output feedback
abstract
In this paper, an achievability region and a converse region for the two-user Gaussian interference channel with noisy channel-output feedback (G-IC-NOF) are presented. The achievability region is obtained using a random coding argument and three well-known techniques: rate splitting, superposition coding and backward decoding. The converse region is obtained using some of the existing perfect-output feedback outer-bounds as well as a set of new outer-bounds that are obtained by using genie-aided models of the original G-IC-NOF. Finally, it is shown that the achievability region and the converse region approximate the capacity region of the G-IC-NOF to within a constant gap in bits per channel use.
Victor Quintero, Samir Perlaza, Inaki Esnaola, Jean-Marie Gorce
ITW1