Joint optimal threshold-based relaying and ML detection in cooperative networks

Xiang Nian Zeng, Ali Ghrayeb, Mazen Hasna

Research output: Contribution to journalArticle

10 Citations (Scopus)


This paper proposes two detection schemes for cooperative networks comprising a source, a relay and a destination. The relay is assumed to operate in a half-duplex mode and it employs decode-and-forward (DF) relaying. The proposed schemes involve combining threshold-based relaying and maximum likelihood (ML) detection at the destination. We consider both signal-to-noise ratio (SNR)-based and log-likelihood (LLR)-based thresholding. Assuming binary phase shift keying (BPSK), we first derive the ML detector as a function of the threshold used at the relay node. Then, we obtain the optimal thresholds by minimizing the end-to-end bit error rate performance. In deriving the ML performance, we follow an approach that is different from existing approaches and is more straightforward. We compare the performance of the proposed schemes and show that they significantly outperform all existing counterpart detection methods.

Original languageEnglish
Article number6177194
Pages (from-to)773-776
Number of pages4
JournalIEEE Communications Letters
Issue number6
Publication statusPublished - Jun 2012



  • Cooperative networks
  • error propagation
  • ML detection
  • threshold-based relaying

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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