S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization

  • Authors:

  • Taufik Abrão;Leonardo D. Oliveira;Fernando Ciriaco;Bruno A. Angélico;Paul Jean Jeszensky;Fernando Jose Casadevall Palacio

  • Affiliations:

  • Department of Electrical Engineering (DEEL), State University of Londrina (UEL), Londrina, Brazil 86051-990;Department of Telecommunications and Control Engineering (LCS-PTC), Escola Politécnica of the University of São Paulo (EPUSP), São Paulo, Brazil 05508-900;Department of Telecommunications and Control Engineering (LCS-PTC), Escola Politécnica of the University of São Paulo (EPUSP), São Paulo, Brazil 05508-900;Department of Telecommunications and Control Engineering (LCS-PTC), Escola Politécnica of the University of São Paulo (EPUSP), São Paulo, Brazil 05508-900;Department of Telecommunications and Control Engineering (LCS-PTC), Escola Politécnica of the University of São Paulo (EPUSP), São Paulo, Brazil 05508-900;Department of Signal Theory and Communication (TSC), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain 08034

  • Venue:
  • Wireless Personal Communications: An International Journal
  • Year:
  • 2010

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Abstract

This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.