Title :
Performance comparison of RLS and LMS algorithms for tracking a first order Markov communications channel
Author :
Bershad, N.J. ; McLaughlin, S. ; Cowan, C.F.N.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
Abstract :
The performances of recursive-least-squares (RLS) and least-mean-square (LMS) adaptive algorithms for tracking a first-order Markov tapped delay line model of a communications channel whose output is observed in a white Gaussian noise background are studied. The model includes the errors due to the finite memory of the channel. A rigorous analytical evaluation of the misadjustment errors of both RLS and LMS is presented. The misadjustment errors are individually minimized over the RLS forgetting factor and the LMS step size. It is shown that the misadjustment factors are nearly equal (RLS is slightly superior) whether the bandwidth of the channel tap fluctuations is greater than or less than the bandwidth of the adaptation algorithm. Conditions are presented for when the adaptation process should be turned off
Keywords :
Markov processes; adaptive filters; least squares approximations; telecommunication channels; white noise; adaptation algorithm; adaptive algorithms; channel tap fluctuations; communications channel; finite memory; first order Markov communications channel; first-order Markov tapped delay line model; forgetting factor; least-mean-square; misadjustment errors; recursive-least-squares; step size; white Gaussian noise background; Adaptive algorithm; Bandwidth; Communication channels; Delay lines; Filters; Gaussian noise; Least squares approximation; Power system modeling; Resonance light scattering; Statistics;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112009
