Near-optimal joint antenna selection for amplify-and-forward relay networks

  • Authors:

  • Yangyang Zhang;Gan Zheng;Chunlin Ji;Kai-Kit Wong;David J. Edwards;Tiejun Cui

  • Affiliations:

  • Department of Electrical and Electronic Engineering, University College London, London, UK;Department of Electrical and Electronic Engineering, University College London, London, UK;Department of Statistical Science, Duke University, Durham, North Carolina;Department of Electrical and Electronic Engineering, University College London, London, UK;Department of Engineering Science, University of Oxford, Oxford, UK;State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, China

  • Venue:
  • IEEE Transactions on Wireless Communications
  • Year:
  • 2010

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Abstract

This paper considers a joint antenna selection method in amplify-and-forward (AF) relay networks where the source, relay and destination terminals are all equipped with multiple antennas. The fact that the system's full diversity can be maintained by antenna selection at each terminal makes it a promising solution to reduce the hardware complexity of multiple-input multiple-output (MIMO) terminals while realizing the diversity benefits of MIMO in relay networks. Since the exhaustive search for antenna subset selection is computationally prohibitive, we devise a low-complexity near-optimal joint antenna selection algorithm based on a constrained cross entropy optimization (CCEO) method to maximize the achievable rate and the convergence is guaranteed. Simulation results reveal both the effectiveness and the efficiency of the proposed algorithm and the significant performance improvement over other benchmark selection techniques. Finally, it is illustrated that the proposed CCEO algorithm can always achieve near-optimal results regardless of the number of selected antennas, outage probabilities and the signal-to-noise ratios (SNRs) at the terminals.