On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization
Authors: Y.Ben Jemaa, M.Jaidane
Abstract:
In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.
Keywords: Adaptive Decision Feedback Equalizer, PerformanceAnalysis, Finite Alphabet Case, Ill-Convergence, Convergence speed.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1078687
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[1] R.A. Kennedy, B.D.O. Anderson and R.R. Bitmead, "Blind adaptation of decision feedback equalizers : Gross convergence properties", Int.J.of Adaptive Control and Signal Processing, Vol.7, pp497-523, 1993.
[2] Rodney A. Kennedy, Brian D.O Anderson and Robert R. Bitmead, "Tight bounds on the error probabilities of decision Feedback Equalizer", IEEE Trans. on communications, Vol.35, N10, pp1022-1028, October 1987.
[3] Rodney A. Kennedy and Brian D.O Anderson, "Recovery times of Decision Feedback Equalizer on noiseless channels", IEEE Trans. on communications, Vol.35, N10, pp1012-1021, October 1987.
[4] T.J.Willink, P.H.Wittke and L.Lorne Campbell, "Evaluation of the effects of InterSymbol Iinterference in Decision Feedback Equalizer", IEEE trans. on Communications, Vol.48, N4, pp629-636, April 2000.
[5] S. Cherif, S. Marcos and M. Jaidane, "Analysis of Blind Decision Feedback Equalizer Convergence: Interest of a soft decision", Int J. on Signal Processing, Vol.4, N 1, pp168-174, 2007.
[6] H.Besbes, M. Jaidane and J. Ezzine, "On Exact Convergence Results of adaptive Filters: the finite alphabet case", Int.J.Signal Processing of EURASIP, December 1999.
[7] H. Besbes, Y. Ben Jemaa, and M. Jaidane, "Exact Convergence Analysis of Affine Projection Algorithm : the finite alphabet case", ICASSP, Vol.3, pp1669-1672, March 1999.
[8] J.G. Proakis, "Digital communications", MC Graw Hill, New York, N.Y., 3rd edition 1995.
[9] F.P. Tontan, J.P. Conzalez, M.J.S. Ferreiro and A.V. Castro, "Complex enveloppe three-state Markov model based simulation for narrow-band LMS Channel", Int.J.Satellite Communications, Vol.15, N1, pp1-15, Jan/Feb 1997.
[10] C.Yeh and JR. Barry, "Adaptive minimum Bit Error Rate equalization for binary signaling", IEEE trans. on Communications, Vol.48, N 7, pp1226-1235, July 2000.
[11] R.A.Kennedy, "Blind adaptation of Decision Feedback Equalizers: gross convergence properties", Int.J.Adaptive Control and Signal Processing, Vol.7, pp497-523, 1993.
[12] J.W.Brewer, "Kronecker products and matrix calculus in system theory", IEEE trans. on Circuit and System, Vol.Cas-25, N9, pp772-781, September 1978.
[13] M. Kallel, Y.Ben Jemaa and M.Jaidane, "On exact PLL performances results for digital transmission context", IEEE ISCCSP, Hammamet, Mars 2004.
[14] C.Anton-Haro and J A.R. Fanollosa, "Blind channel estimation and data detection using Hidden Markov Models", IEEE trans. on Signal Processing, Vol.45, N1, pp241-246, January 1997.
[15] O.Macchi and E. Eweda, "Convergence analysis of self-adaptive equalizers", IEEE trans. on information Theory, Vol.30, N3, pp161-176, March 1984.
[16] Sanchey-Perez R, Casajus-Quiros F.J and Pasupathy S, "Robust DFE for limiter-discriminator based Hiperlan receivers", IEEE VTC, Vol.6, pp2979-2986, Boston, September 2000.