Low-complexity detection for large MIMO systems using partial ML detection and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Pavol Svac and Florian Meyer and Erwin Riegler and 
                 Franz Hlawatsch",
  booktitle =    "13th IEEE International Workshop on Signal Processing
                 Advances in Wireless Communications (SPAWC 2012)",
  title =        "Low-complexity detection for large MIMO systems using
                 partial ML detection and genetic programming",
  year =         "2012",
  pages =        "585--589",
  keywords =     "genetic algorithms, genetic programming, MIMO
                 communication, maximum likelihood detection, phase
                 shift keying, quadrature amplitude modulation, BPSK,
                 MIMO system, QAM constellation, low-complexity
                 detection, multiple-input multiple-output system,
                 partial ML detection, soft values generation,
                 soft-input genetic optimisation, Cascading style
                 sheets, Complexity theory, Detectors, MIMO, Signal to
                 noise ratio, Vectors",
  DOI =          "doi:10.1109/SPAWC.2012.6292977",
  ISSN =         "1948-3244",
  abstract =     "We propose a low-complexity detector for
                 multiple-input multiple-output (MIMO) systems using
                 BPSK or QAM constellations. The detector operates at
                 the bit level and is especially advantageous for large
                 MIMO systems. It consists of three stages performing
                 partial ML detection, generation of soft values, and
                 soft-input genetic optimisation. For the last stage, we
                 present a genetic programming algorithm that uses the
                 soft values computed by the second stage. Simulation
                 results demonstrate that for large systems, our
                 detector can outperform state-of-the-art methods, and
                 its complexity scales roughly cubically with the system
  notes =        "Also known as \cite{6292977}",

Genetic Programming entries for Pavol Svac Florian Meyer Erwin Riegler Franz Hlawatsch