Paper Info
Title
Comparing RLS and LMS adaptive equalizers for nonstationary wireless channels in mobile ad hoc networks.
Abstract
This paper compares performance of finite impulse response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square (LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation results, in terms of steady-state mean-square estimation error (MSE) and average bit-error rate (BER) metrics, are found for the frequency-selective Rayleigh fading wireless channel experienced in a mobile ad hoc network where nodes are lognormally shadowed from each other. For the nonstationary channel models considered, RLS is always found to outperform LMS.
Year
DOI
Venue
2002
10.1109/PIMRC.2002.1045204
PIMRC
Keywords
Field
DocType
FIR filters,Rayleigh channels,ad hoc networks,adaptive equalisers,adaptive filters,error statistics,least mean squares methods,least squares approximations,mean square error methods,mobile radio,scattering,time-varying channels,BER,FIR equalizer,FIR filters,LMS algorithm,MSE,RLS algorithm,Rayleigh fading channel,adaptive equalizers,adaptive filters,bit-error rate,frequency-selective channel,least mean square algorithm,linear equalizers,mean-square estimation error,mobile ad hoc networks,nonstationary wireless channels,recursive least-squares algorithm,scattering wireless channels,time-varying channel
Mobile ad hoc network,Least mean squares filter,Mobile radio,Wireless,Rayleigh fading,Computer science,Algorithm,Real-time computing,Adaptive filter,Wireless ad hoc network,Statistics,Finite impulse response
Conference
Volume
Citations 
PageRank 
3
2
0.55
References 
Authors
4
5
Name
Order
Citations
PageRank
Raymond Wang1418.78
Nihar Jindal24714482.24
Thomas Bruns320.55
Ahmad Bahai460265.90
Donald C. Cox535093.52