Open Access

Practical Quantize-and-Forward Schemes for the Frequency Division Relay Channel

EURASIP Journal on Wireless Communications and Networking20082007:020258

DOI: 10.1155/2007/20258

Received: 6 April 2007

Accepted: 13 November 2007

Published: 8 January 2008

Abstract

We consider relay channels in which the source-destination and relay-destination signals are assumed to be orthogonal and thus have to be recombined at the destination. Assuming memoryless signals at the destination and relay, we propose a low-complexity quantize-and-forward (QF) relaying scheme, which exploits the knowledge of the SNRs of the source-relay and relay-destination channels. Both in static and quasistatic channels, the quantization noise introduced by the relay is shown to be significant in certain scenarios. We therefore propose a maximum likelihood (ML) combiner at the destination, which is shown to compensate for these degradations and to provide significant performance gains. The proposed association, which comprises the QF protocol and ML detector, can be seen, in particular, as a solution for implementing a simple relaying protocol in a digital relay in contrast with the amplify-and-forward protocol which is an analog solution.

[123456789101112131415161718192021]

Authors’ Affiliations

(1)
CNRS, Supéléc
(2)
Worcester Polytechnic Institute

References

  1. El Gammal A, Mohseni M, Zahedi S: Bounds on capacity and minimum energy-per-bit for AWGN relay channels. IEEE Transactions on Information Theory 2006,52(4):1545-1561.View ArticleMathSciNetMATHGoogle Scholar
  2. Laneman JN, Tse DNC, Wornell GW: Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE Transactions on Information Theory 2004,50(12):3062-3080. 10.1109/TIT.2004.838089MATHMathSciNetView ArticleGoogle Scholar
  3. Cover TM, El Gamal AA: Capacity theorems for the relay channel. IEEE Transactions on Information Theory 1979,25(5):572-584. 10.1109/TIT.1979.1056084MATHMathSciNetView ArticleGoogle Scholar
  4. Khojastepour MA, Sabharwal , Aazhang B: Lower bounds on the capacity of gaussian relay channel. Proceedings of the 38th Conference on Information Sciences and Systems, March 2004, Princeton, NJ, USA 597-602.Google Scholar
  5. Katz M, Shamai S: Relaying protocols for two colocated users. IEEE Transactions on Information Theory 2006,52(6):2329-2344.MATHMathSciNetView ArticleGoogle Scholar
  6. Liu Z, Stanković V, Xiong Z: Wyner-ziv coding for the half-duplex relay channel. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '05), 2005 5: 1113-1116.Google Scholar
  7. Hu R, Li J: Exploiting slepian-wolf codes in wireless user cooperation. IEEE Workshop on Signal Processing Advances in Wireless Communications, (SPAWC '05), 2005 2005: 275-279.Google Scholar
  8. Chakrabarti A, De Baynast A, Sabharwal A, Aazhang B: Half-duplex estimate-and-forward relaying: bounds and code design. IEEE International Symposium on Information Theory (ISIT '06), July 2006, Seattle, Wash, USA 1239-1243.Google Scholar
  9. Kurtenbach A, Wintz P: Quantizing for noisy channels. IEEE Transactions on Communications 1969, 17: 291-302. 10.1109/TCOM.1969.1090091View ArticleGoogle Scholar
  10. Farvardin N, Vaishampayan V: Optimal quantizer design for noisy channels: an approach to combine source-channel coding. IEEE Transactions on Information Theory 1987,33(6):827-837. 10.1109/TIT.1987.1057373MATHMathSciNetView ArticleGoogle Scholar
  11. Farvardin N: Study of vector quantization for noisy channels. IEEE Transactions on Information Theory 1990,36(4):799-809. 10.1109/18.53739MathSciNetView ArticleGoogle Scholar
  12. Wang T, Cano A, Giannakis GB, Laneman JN: High-performance cooperative demodulation with decode-and-forward relays. IEEE Transactions on Communications 2007,55(7):1427-1438.View ArticleGoogle Scholar
  13. Vaishampayan V, Farvardin N: Joint design of block source codes and modulation signal sets. IEEE Transactions on Information Theory 1992, 38: 1230-1248. 10.1109/18.144704MATHView ArticleGoogle Scholar
  14. Liu FH, Ho P, Cuperman V: Joint source and channel coding using a non-linear receiver. Proceedings of the IEEE International Conference on Communications, 1993 1502-1507.View ArticleGoogle Scholar
  15. Skinnemoen H: Modulation organized vector quantization, MOR-VQ. Proceedings of the IEEE International Symposium on Information Theory, June 1994 238.Google Scholar
  16. Linde YL, Buzo A, Gray RM: An algorithm for vector quantizer design. IEEE Transactions on Communications 1980, 28: 84-95. 10.1109/TCOM.1980.1094577View ArticleGoogle Scholar
  17. Hamkins J, Zeger K: Gaussian source coding with spherical codes. NASA Technical Report 2005.Google Scholar
  18. Abou-Faycal I, Médard M: Optimal uncoded regeneration for binary antipodal signaling. Proceedings of the IEEE International Conference on Communications, June 2004 2: 742-746.Google Scholar
  19. Gomadam KS, Jafar SA: On the capacity of memoryless relay networks. Proceedings of the IEEE International Conference on Communications, June 2006, Istanbul, TurkeyGoogle Scholar
  20. Huang TC: Signaling performance over a piecewise linear limited channel in the presence of interference and gaussian noise. IEEE Transactions on Communications 1983,31(7):861-870. 10.1109/TCOM.1983.1095908MATHView ArticleGoogle Scholar
  21. Djeumou B, Lasaulce S, Klein AG: Combining decoded-and-forwarded signals in gaussian cooperative channels. Proceedings of the IEEE International Symposium on Signal Processing and Information Technology (ISSPIT '06), August 2006, Vancouver, Canada 622-627.Google Scholar

Copyright

© B. Djeumou et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.