Half-duplex relaying based on quantize-and-forward

Sha Yao, Mikael Skoglund, Tung T. Kim, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The original compress-and-forward relaying scheme uses the technique of random binning at the relay node and successive decoding at the destination node. Recently, a scheme (termed the quantize-and-forward scheme in this paper) without binning and using joint decoding at the destination node has been proposed, which has been shown to achieve the same rate as the original compress-and-forward scheme. Since the previous work focuses on the so-called full duplex relay network, in this paper, an adaption of it for relay networks with a half-duplex relay is provided. Coding schemes and achievable rate results are presented for discrete memoryless half-duplex relay channels and half-duplex additive white Gaussian noise (AWGN) relay channels. Moreover, slow fading channels are considered, for which outage-related performance measures are evaluated. Specifically, the outage probability and the expected rate of the quantize-and-forward scheme are derived and compared with other well-known schemes. Furthermore, the diversity-multiplexing tradeoff is derived. It is shown that the quantize-and-forward scheme is a more suitable scheme than the compress-and-forward scheme over slow fading channels and it achieves the optimal diversity-multiplexing trade-off of a half-duplex relay channel.

Original languageEnglish (US)
Title of host publication2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011
Pages2447-2451
Number of pages5
DOIs
StatePublished - Oct 26 2011
Event2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011 - St. Petersburg, Russian Federation
Duration: Jul 31 2011Aug 5 2011

Other

Other2011 IEEE International Symposium on Information Theory Proceedings, ISIT 2011
CountryRussian Federation
CitySt. Petersburg
Period7/31/118/5/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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