ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Study on the Convergence of the Generalized Decision Feedback Equalizer Algorithm with Error Feedback Filter


Affiliations
1 Kim Chaek University of Technology, Korea, Democratic People's Republic of
2 College of Information Engineering, Wonsan Jogunsil University of technology, Korea, Democratic People's Republic of
     

   Subscribe/Renew Journal


In digital communications, a time-dispersive variation channel causes inter-symbol interference (ISI) and distorts the received signal, thus degrading the system performance. The distortion caused by ISI may be mitigated by passing the received signal through an adaptive equalizer such as linear equalizer, maximum likelihood sequence estimator (MLSE) and decision feedback equalizer (DFE). This paper demonstrates a new approach to improving the convergence of the DFE algorithm with error feedback filter in order to reduce the correlation of error signals and also to decrease the residual error variance. The paper theoretically analyzes the convergence of generalized DFE with error feedback filter, and proves that the minimum mean square error (MMSE) monotonically decreases and stably converges when the order of the error feedback filter increases. The simulation clearly shows that the proposed DFE algorithm results in better ERLE (Echo Return Loss Enhancement) than previous ones and particularly the significant improvement of BER performance in case that the number of taps in the error feedback filter increases under low SNR environment.

Keywords

Decision Feedback Equalizer, Error Feedback Filter, ISI, Convergence, MMSE.
Subscription Login to verify subscription
User
Notifications
Font Size

  • J.G. Proakis, “Digital Communications”, McGraw-Hill, 2000.

  • S. Haykin, “Adaptive Filter Theory”, Prentice-Hall, 1996.

  • G.D. Forney, “Maximum-Likelihood Sequence Estimation of Digital Sequences in the Presence of Intersymbol Interference”, IEEE Transactions on Information Theory, Vol. 18, No. 2, pp. 363-378, 1972.

  • K. Okanoue, A. Ushirokawa, H. Tomita and Y. Furuya, “Fast Tracking Adaptive MLSE for TDMA Digital Cellular Systems”, IEICE Transactions on Communications, Vol. 77, No. 5, pp. 557-564, 1994.

  • K. Jamal, G. Brismark, and B. Gudmundson, “Adaptive MLSE Performance on the D-AMPS 1900 Channel”, IEEE Transactions on Vehicular Technology, Vol. 46, No. 3, pp. 73-75, 1997.

  • J. F. Doherty and R.J. Mammone, “An Adaptive Algorithm for Stable Decision-Feedback Filtering”, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol. 40, No. 1, pp. 1-9, 1993.

  • M. Rupp and A. Bahai, “Training and tracking of adaptive DFE algorithms under IS-136”, Proceedings of 1st IEEE Signal Processing Workshop Signal Processing Advances in Wireless Communications, pp. 341-344, 1997.

  • R. Lopez-Valcarce, “Realizable Linear and Decision Feedback Equalizers: Properties and Connections”, IEEE Transactions on Signal Processing, Vol. 52, No. 1, pp. 757-773, 2004.

  • D.L. Duttweiler, J.E. Mazo and D.G. Messerschmitt, “An Upper Bound on the Error Probability in Decision-Feedback Equalization”, IEEE Transactions on Information Theory, Vol. 20, No. 4, pp. 490-497, 1974.

  • J. Palicot, “A Weighted Decision Feedback Equalizer with Limited Error Propagation”, Proceedings of International Conference on Communications, pp. 1-5, 2000.

  • J. Palicot and Alban Goupil, “Performance Analysis of the Weighted Decision Feedback Equalizer”, Signal Processing, Vol. 88, No. 2, pp. 284-295, 2008.

  • T.I. Laakso and I.O. Hartimo, “Noise Reduction in Recursive Digital Filters using High-Order Error Feedback”, IEEE Transactions on Signal Processing, Vol. 40, No. 5, pp. 1096-1106, 1992.

  • S.K. Jagtap, M.S. Mulye and M.D. Uplane, “Speech Coding Techniques”, Procedia Computer Science, Vol. 49, pp. 253-263, 2015.

  • Jagreeti Kaur and Baljit Singh, “Comparison of LSB and Predictive Coding using PSNR and MSE”, International Journal of Computer Applications, Vol. 98, No. 7, pp. 1-12, 2014.

  • Feng Wen Jiang, “Performance Analysis of a Decision Feedback Equalizer using Error Feedback”, Information and Electronic Engineering, Vol. 4, No. 2, pp. 107-110, 2006.

  • A.Y. Hassan, “A Wide Band QAM Receiver based on DFE to Reject ISI in Wireless Time Varying Fading Channel”, International Journal of Electronics and Communications, Vol. 69, No. 1, pp. 332-343, 2015.


Abstract Views: 309

PDF Views: 0




  • Study on the Convergence of the Generalized Decision Feedback Equalizer Algorithm with Error Feedback Filter

Abstract Views: 309  |  PDF Views: 0

Authors

Jong Sam Lee
Kim Chaek University of Technology, Korea, Democratic People's Republic of
Yong Chan Lee
College of Information Engineering, Wonsan Jogunsil University of technology, Korea, Democratic People's Republic of

Abstract


In digital communications, a time-dispersive variation channel causes inter-symbol interference (ISI) and distorts the received signal, thus degrading the system performance. The distortion caused by ISI may be mitigated by passing the received signal through an adaptive equalizer such as linear equalizer, maximum likelihood sequence estimator (MLSE) and decision feedback equalizer (DFE). This paper demonstrates a new approach to improving the convergence of the DFE algorithm with error feedback filter in order to reduce the correlation of error signals and also to decrease the residual error variance. The paper theoretically analyzes the convergence of generalized DFE with error feedback filter, and proves that the minimum mean square error (MMSE) monotonically decreases and stably converges when the order of the error feedback filter increases. The simulation clearly shows that the proposed DFE algorithm results in better ERLE (Echo Return Loss Enhancement) than previous ones and particularly the significant improvement of BER performance in case that the number of taps in the error feedback filter increases under low SNR environment.

Keywords


Decision Feedback Equalizer, Error Feedback Filter, ISI, Convergence, MMSE.

References