A Principled Framework for Narrowband Mobile Digital Communications

  • Michael P. Fitz
  • James P. Seymour
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 309)


This paper developes a model-based framework for narrowband communications. First, we derive the optimum (MAP) demodulation algorithm for M-QAM signaling in the frequency flat time-varying Rayleigh fading channel. This recursive structure allows for symbol-by-symbol data decisions to be made in an efficient manner. The complexity problem inherent to optimal detection schemes is addressed and approximations to optimal detection are considered which reduce complexity to practical levels yet still provide near-optimal performance levels. Reduced complexity algorithms are obtained through the use of decision feedback, thresholding and a novel state partitioning which allow for higher order modulations such as 16-QAM and 64-QAM to be implemented. The algorithms presented exhibit favorable advantages over pilot symbol assisted modulation techniques in performance, bandwidth efficiency and the necessary decoding delay. This principled approach to narrowband mobile digital communications provides a unified framework which incorporates diversity combining techniques, array signal processing, forward error control decoding and optimum demodulation in a single demodulation architecture. Performance characterizations of the algorithms presented are obtained via Monte Carlo simulation and the results show that near-optimal BEP levels are achieved.


Fading Channel Pilot Symbol Decision Feedback Doppler Spread Error Control Code 
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]
    A. Aghamohammadi and H. Meyr, “A New Method for Phase Synchronization and Automatic Gain Control for Linearly Modulated Signals on Frequency Flat Fading Channels,” IEEE Trans. Commun., vol. COM-38, January 1991, pp. 25–29.CrossRefGoogle Scholar
  2. [2]
    M.L. Moher and J.H. Lodge, “TCMP — A Modulation and Coding Scheme for Rician Fading Channels,” IEEE J. Select. Areas Commun., vol. SAC-7, December 1989, pp. 1347–1355.CrossRefGoogle Scholar
  3. [3]
    A. Bateman, “Feedforward Transparent Tone-in-Band: Its Implementations and Applications,” IEEE Trans. on Veh. Technol., vol. VT-39, August 1990, pp. 235–243.CrossRefGoogle Scholar
  4. [4]
    F. Davarian, “Mobile Digital Communication Via Tone Calibration,” IEEE Trans. Veh. Tech., vol. VT-36, May 1987, pp. 55–62.CrossRefGoogle Scholar
  5. [5]
    M. Yokohama, “BPSK System with Sounder to Combat Rayleigh Fading in Mobile Radio,” IEEE Trans. Veh. Tech., vol. VT-34, February 1985, pp. 35–40.CrossRefGoogle Scholar
  6. [6]
    M.P. Fitz, “A Dual-Tone Reference Digital Demodulator for Mobile Digital Communications,” IEEE Trans. Veh. Technol., vol. VT-42, May 1993, pp. 156–165.CrossRefGoogle Scholar
  7. [7]
    K. Abend and B.D. Fritchman, “Statistical Detection for Communication Channels with Intersymbol Interference,” Proc. IEEE, vol. 58, May 1970, pp. 779–785.CrossRefGoogle Scholar
  8. [8]
    J.K. Cavers, “An Analysis of Pilot Symbol Assisted Modulation for Rayleigh Faded Channels,” IEEE Trans. Veh. Technol., vol. VT-40, November 1991, pp. 686–693.CrossRefGoogle Scholar
  9. [9]
    R.W. Chang and J.C. Hancock, “On Receiver Structures for Channels Having Memory,” IEEE Trans. Info. Theory, vol. IT-12, October 1966, pp. 463–468.CrossRefGoogle Scholar
  10. [10]
    P.R. Kumar and P. Varaiya, Stochastic Systems: Estimation, Identification, and Adaptive Control, Prentice-Hall, Englewood Cliffs, NJ, 1986.zbMATHGoogle Scholar
  11. [11]
    H.V. Poor, An Introduction to Signal Detection and Estimation, Springer-Verlag, New York, 1988.zbMATHGoogle Scholar
  12. [12]
    J.P. Seymour and M.P. Fitz, “Improved Synchronization in the Mobile Communications Environment,” Technical Report, School of Electrical Engineering, Purdue University, West Lafayette, IN, 1994.Google Scholar
  13. [13]
    V.M. Eyuboglu and S.U.H. Qureshi, “Reduced-State Sequence Estimation with Set Partitioning and Decision Feedback,” IEEE Trans. Commun., vol. COM-36, January 1988, pp. 13–20.CrossRefGoogle Scholar
  14. [14]
    E. Biglieri, et al., Introduction to Trellis-Coded Modulations with Applications, Macmillan, New York, 1991.Google Scholar
  15. [15]
    P. Ho, J. Cavers, and J. Varaldi, “The Effect of Constellation Density on Trellis Coded Modulation in Fading Channels,” IEEE Trans. Veh. Technol., vol. VT-42, August 1993, pp. 318–325.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1995

Authors and Affiliations

  • Michael P. Fitz
    • 1
  • James P. Seymour
    • 1
  1. 1.School of Electrical EngineeringPurdue UniversityWest LafayetteUSA

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