DocumentCode :
2460461
Title :
A Hybrid RNS Adaptive Filter for Channel Equalization
Author :
Bernocchi, G.L. ; Cardarilli, G.C. ; Del Re, A. ; Nannarelli, A. ; Re, M.
Author_Institution :
Dept. of Electron., Univ. of Rome Tor Vergata, Rome
fYear :
2006
fDate :
Oct. 29 2006-Nov. 1 2006
Firstpage :
1706
Lastpage :
1710
Abstract :
In this work a hybrid residue number system (RNS) implementation of an adaptive FIR filter is presented. The used adaptation algorithm is the least mean squares (LMS). The filter has been designed to meet the constraints of specific class of applications. In fact, it is suitable for applications requiring a large number of taps where a serial updating of the filter coefficients is feasible (channel equalization or echo cancellation). In the literature, it has been shown that the RNS implementation of FIR filters grants earnings in area ad power consumption due to the introduced arithmetic simplifications. Vice versa, the RNS implementation of the adaptation algorithm needs scaling circuits that are complex and expensive in RNS arithmetic. For this reason, a serial binary implementation of the adaptation algorithm is chosen. The advantages in terms of area and speed of the RNS adaptive filter with respect to the two´s complement one have been evaluated for a standard cells implementation.
Keywords :
FIR filters; adaptive equalisers; adaptive filters; echo suppression; least mean squares methods; residue number systems; adaptation algorithm; adaptive FIR filter; channel equalization; echo cancellation; hybrid RNS adaptive filter design; least mean square method; residue number system; scaling circuits; serial binary implementation; Adaptive equalizers; Adaptive filters; Arithmetic; Circuits; Digital signal processing; Echo cancellers; Energy consumption; Finite impulse response filter; Least squares approximation; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2006. ACSSC '06. Fortieth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
1-4244-0784-2
Electronic_ISBN :
1058-6393
Type :
conf
DOI :
10.1109/ACSSC.2006.355052
Filename :
4176862
Link To Document :
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