A Joint Typicality Approach to Compute-Forward SCIE SCOPUS

Cited 8 time in WEB OF SCIENCE Cited 9 time in Scopus
Title
A Joint Typicality Approach to Compute-Forward
Author(s)
Lim, Sung Hoon; Feng, Chen; Pastore, Adriano; Nazer, Bobak; Gastpar, Michael
Publication Year
2018-12
Abstract
This paper presents a joint typicality framework for encoding and decoding nested linear codes in multi-user networks. This framework provides a new perspective on compute-forward within the context of discrete memoryless networks. In particular, it establishes an achievable rate region for computing a linear combination over a discrete memoryless multiple-access channel (MAC). When specialized to the Gaussian MAC, this rate region recovers and improves upon the lattice-based compute-forward rate region of Nazer and Gastpar, thus providing a unified approach for discrete memoryless and Gaussian networks. Furthermore, our framework provides some valuable insights on establishing the optimal decoding rate region for compute-forward by considering joint decoders, progressing beyond most previous works that consider successive cancellation decoding. Specifically, this paper establishes an achievable rate region for simultaneously decoding two linear combinations of nested linear codewords from K senders.
ISSN
0018-9448
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/799
DOI
10.1109/TIT.2018.2872053
Bibliographic Citation
IEEE TRANSACTIONS ON INFORMATION THEORY, v.64, no.12, pp.7657 - 7685, 2018
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Subject
ACHIEVABLE RATE REGION; MULTIPLE-ACCESS CHANNEL; DISTRIBUTED COMPRESSION; APPROXIMATE CAPACITY; GROUP CODES; INTERFERENCE; FREEDOM; SUM; INFORMATION; STRATEGIES
Keywords
Linear codes; joint decoding; compute-forward; multiple-access channel; relay networks
Type
Article
Language
English
Document Type
Article
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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