A joint typicality approach to compute-forward

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 computin...

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Detalles Bibliográficos
Autores: Lim, SH, Feng, C, Pastore, A, Nazer, B, Gastpar, M
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Repositorio:r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
OAI Identifier:oai:cttc.fundanetsuite.com:p1524
Acceso en línea:https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1524
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054694761&doi=10.1109%2fTIT.2018.2872053&partnerID=40&md5=a3dd063790a50de9736f5d397e90e481
Access Level:acceso abierto
Palabra clave:Communication channels (information theory)
Achievable rate region
Discrete memoryless multiple access channel
Encoding and decoding
Joint decoding
Linear codes
Multiple access channels
Relay network
Successive-cancellation decoding
Decoding
Descripción
Sumario: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. © 2018 IEEE.