Early HARQ using LLR Trend Analysis

Narayan Prasad Kusi, Jiho Kim, Dong Ho Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

One of the key usage scenarios in the scope of 5G is ultra-reliable and low-latency communications (URLLC) and HARQ is one of the inherent parts to make the service reliable and efficient. In this work, we proposed a new and reliable metric for the subcode based early HARQ prediction which adopts NMS (Normalized Min Sum) LDPC decoder. It provides flexible iterative decoding with sub-codes of different lengths for early HARQ prediction using the substructure LDPC parity matrix. The proposed Early HARQ prediction analyses the changing trend of LLR values of variable nodes during iterations and predicts feedback of the decodability based on the trend analysis of posterior LLR values after some iterations. The early HARQ prediction using the LLR trend analysis enables us to provide reliable and earlier feedback making faster retransmissions.

Original languageEnglish
Title of host publicationICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
Subtitle of host publicationExploring the Frontiers of ICT Innovation
PublisherIEEE Computer Society
Pages285-287
Number of pages3
ISBN (Electronic)9798350313277
DOIs
StatePublished - 2023
Event14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of
Duration: 11 Oct 202313 Oct 2023

Publication series

NameInternational Conference on ICT Convergence
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Country/TerritoryKorea, Republic of
CityJeju Island
Period11/10/2313/10/23

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