Approximate Gibbs algorithm for blind data detection in two‐way relay networks. Issue 8 (25th May 2017)

• Record Type: Journal Article
• Authors: Jiang, Zhe; Shen, Xiaohong; Ge, Yao; Wang, Haiyan
• Is Part Of: IET communications. Volume 11:Issue 8(2017)
• Page Start: 1230
• Page End: 1240
• Publication Date: 2017-05-25
• Subjects: relay networks (telecommunication) -- approximation theory -- amplify and forward communication -- Bayes methods -- parameter estimation -- signal detection; blind data detection -- two‐way relay networks -- amplify‐and‐forward relay strategy -- Bayesian‐based approximate Gibbs algorithm -- truncated Taylor series expansion approximation -- parameter estimation; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2016.0597
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : This study investigates the blind data detection in two‐way relay networks (TWRN) that employ amplify‐and‐forward (AF) relay strategy. To blindly detect the data in TWRN in the presence of uncertain time‐frequency offsets and phase noise, the authors develop a new Bayesian‐based approximate Gibbs algorithm based on truncated Taylor series expansion approximation. In addition, the authors exploit available constraint information on parameters of interest. The authors present three receivers based on three different parameter estimation approaches. The authors further discuss the implementation issue and present diagnostic convergence analysis. The authors' numerical results demonstrate the performance and efficacy of their proposed algorithm.