Modulation Diversity for Wireless Communications: Impact of Channel Estimation Errors and Doppler Effects on System Performance

  • Waslon Terllizzie A. Lopes
  • Marcelo S. Alencar
  • Juraci F. Galdino
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 712)


The performance of wireless communications systems can be significantly improved using the modulation diversity technique which is, basically, based on the combination of a suitable choice of the reference angle of an MPSK constellation with independent interleaving of the symbol components. This technique presents good performance assuming the absence of estimation errors for channels characterized by flat fading. In this article, the performance of this recent technique is analyzed taking into account the effects of channel estimation errors. It is shown, by simulation, that the efficiency of this technique is maintained even under this assumption. Additionally, the impact of the Doppler effect on the system performance is treated and a trade-off between the interleaving depth and the error probability is achieved.


Fading Channel Channel Estimation Modulation Diversity Network Security Reference Constellation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    V. M. DaSilva and E. S. Sousa. ”Fading-Resistant Modulation Using Several Transmitter Antennas,” IEEE Transactions on Communications, vol. 45, no. 10, pp. 1236–1244, October 1997.CrossRefGoogle Scholar
  2. [2]
    G. J. Foschini and M. J. Gans. ”On Limits of Wireless Communications in a Fading Environment When Using Multiple Antennas,” Wireless Personal Communications, vol. 6, no. 3, pp. 311–335, March 1998.CrossRefGoogle Scholar
  3. [3]
    V. Tarokh, N. Seshadri and A. R. Calderbank. ”Space-Time Codes for High Data Rate Wireless Communication: Performance Criterion and Code Construction,” IEEE Transactions on Information Theory, vol. 44, no. 2, pp. 744–765, March 1998.MathSciNetMATHCrossRefGoogle Scholar
  4. [4]
    J. H. Winters and R. D. Gitlin. ”The Impact of Antenna Diver-sity on the Capacity of Wireless Communications Systems,” IEEE Transactions on Communications, vol. 42, no. 2/3/4, pp. 1740 – 1751, February/March/April 1994.CrossRefGoogle Scholar
  5. [5]
    N. Seshadri and C. W. Sundberg. ”Multilevel Trellis Coded Modulations for the Rayleigh Fading Channel,” IEEE Trans. Communications, vol. 41, no. 9, September 1993.Google Scholar
  6. [6]
    J. Wu and S. Lin. ”Multilevel Trellis MPSK Modulation Codes for the Rayleigh Fading Channel,” IEEE Transactions on Communications, vol. 41, no. 9, September 1993.Google Scholar
  7. [7]
    K. J. Kerpez. ”Constellations for Good Diversity Performance,” IEEE Transactions on Comm munications, vol. 41, no. 9, pp. 1412 – 1421, September 1993.MATHCrossRefGoogle Scholar
  8. [8]
    S. B. Slimane. ”An Improved PSK Scheme for Fading Channels,” IEEE Transactions on Vehicular Technology, vol. 47, no. 2, pp. 703–710, May 1998.CrossRefGoogle Scholar
  9. [9]
    J. Boutros and E. Viterbo. ”Signal Space Diversity: A Power- and Bandwidth-Efficient Diversity Technique for the Rayleigh Fading Channel,” IEEE Transactions on Information Theory, vol. 44, no. 4, pp. 1453–1467, July 1998.MathSciNetMATHCrossRefGoogle Scholar
  10. [10]
    W. T. A. Lopes and M. S. Alencar. ”Space-Time Coding Performance Improvement Using a Rotated Constellation,” In XVIII Brazilian Telecommunication Symposium (SBrT’2000), Gramado, RS, Brazil, September 2000.Google Scholar
  11. [11]
    J. D. Parsons. The Mobile Radio Propagation Channel. John Wiley, 1992.Google Scholar
  12. [12]
    W. T. A. Lopes and M. S. Alencar. ”Performance of a Rotated QPSK Based System in a Fading Channel Subject to Estimation Errors,” In IEEE International Microwave and Optoelectronics Conference (IMOC’2001), pp. 27–30, Belém, PA, Brazil, August 2001.Google Scholar
  13. [13]
    S. S. Haykin. Adaptive Filter Theory. Prentice Hall, 1991.MATHGoogle Scholar
  14. [14]
    J. G. Proakis. Digital Communications. McGraw-Hill, New York, 1989.Google Scholar
  15. [15]
    W. T. A. Lopes, ”Desempenho de um Sistema QPSK com Rotacao na Constelacao em Canais com Desvanecimento Raido Sujeito a Erros de Estimacao de Canal,” Technical report RT00271/01, Departamento de Engenharia Elétrica, Universidade Federal da Paraíba, Campina Grande, PB, Brazil, 2001.Google Scholar
  16. [16]
    P. Koufalas. ”State Variable Approach to Carrier Phase Recovery and Fine Automatic Gain Control on Flat Fading Channels,” Master’s thesis, University of South Australia, 1996.Google Scholar
  17. [17]
    A. G. Guimarães, C. J. A. Silva, J. F. Galdino and E. L. Pinto ”Comparacão de Desempenho de Simuladores de Canais com Desvanecimento Rápido: Parte I — Avaliacão Númerica,” In XV Brazilian Telecommunication Symposium (SBT’97), pp. 426–430, Recife, PE, Brazil, September 1997.Google Scholar
  18. [18]
    A. Müller. ”Simulation of Multipath Fading Channels using the Monte-Carlo Method,” In Proceedings of the IEEE International Conference on Communications (ICC’94), pp. 1536–1540, 1994.Google Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Waslon Terllizzie A. Lopes
    • 1
  • Marcelo S. Alencar
    • 1
  • Juraci F. Galdino
    • 2
  1. 1.Laboratório de Comunicacoes, Departamento de Engenharia ElétricaUniversidade Federal da ParaíbaCampina GrandeBrazil
  2. 2.Departamento de Engenharia ElétricaInstituto Militar de EngenhariaRio de JaneiroBrazil

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