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Anurag Chhetri

dblp:352/3199 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0009-2555-4353ORCID · reported

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

Computer networks · 1 · 1 since 2021

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%
Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
modulation
0.712023
Role of Index Codes in Noisy Broadcasting With Side Information and Index Coded QAM For Prioritized Receivers · IEEE Trans. Commun. 2023
Coding theory › network coding
index coding
0.712023
Role of Index Codes in Noisy Broadcasting With Side Information and Index Coded QAM For Prioritized Receivers · IEEE Trans. Commun. 2023

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

maximum-likelihood decoding · 1.3constellation mapping · 1.3
YearPublicationVenuePosition
2023 Role of Index Codes in Noisy Broadcasting With Side Information and Index Coded QAM For Prioritized Receivers
abstract
This paper considers the problem of broadcasting with side information (BWSI), where a central server broadcasts encoded transmissions using$M$-ary modulation to a set of caching receivers over an additive white Gaussian noise channel. For this problem of noisy index coding with$M$-ary modulated transmission, the ML decoder at any receiver does not involve demodulation to the complex signal point and then index code decoding to the requested message bit. Instead, it decodes directly to the requested message bit, raising the question of whether the central server’s encoding scheme is required to correspond to an index code or if any set of transmissions encoding across the entire library of messages is sufficient. This paper proves that index codes are necessary for solving noisy BWSI problems even with$M$-ary modulated transmission. Further, we look at index-coded QAM for prioritized receivers. An algorithm for mapping index-coded vectors to signal points on a square QAM constellation is presented, which gives mappings that achieve the best ML decoding performance for the prioritized receivers. Expressions for the ML metric seen by the highest priority receiver while using$M$-PSK and$M$-QAM for transmission are derived. For the highest priority receiver,$M$-PSK is shown to outperform$M$-QAM.
Anjana Ambika Mahesh, Anurag Chhetri, B. Sundar Rajan
IEEE Trans. Commun.2