DocumentCode :
1554086
Title :
Dynamic algorithm transforms for low-power reconfigurable adaptive equalizers
Author :
Goel, Manish ; Shanbhag, Naresh R.
Author_Institution :
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Volume :
47
Issue :
10
fYear :
1999
fDate :
10/1/1999 12:00:00 AM
Firstpage :
2821
Lastpage :
2832
Abstract :
In this paper, we present low-power reconfigurable adaptive equalizers derived via dynamic algorithm transforms (DATs). The principle behind DAT is that conventional signal processing systems are designed for the worst case and are not energy-optimum on average. Therefore, significant energy savings can be achieved by optimally reconfiguring the hardware in these situations. Practical reconfiguration strategies for adaptive filters are presented. These strategies are derived as a solution to an optimization problem. The optimization problem has energy as the objective function and a constraint on the algorithm performance (specifically the SNR). The DAT-based adaptive filter is employed as an equalizer for a 51.84 Mb/s very high speed digital subscriber loop (VDSL) over 24-pair BKMA cable. The channel nonstationarities are due to variations in cable length and number of far end crosstalk (FEXT) interferers. For this application, the traditional design is based on 1 kft cable length and 11 FEXT interferers. It was found that up to 81% energy savings can be achieved when cable length varies from 1-0.1 kft and the number of FEXT interferers varies from 11 to 4. On the average, 53% energy savings are achieved as compared with the conventional worst-case design
Keywords :
adaptive equalisers; adaptive filters; crosstalk; digital subscriber lines; optimisation; transforms; BKMA cable; DAT; VDSL; adaptive filters; algorithm performance; cable length; dynamic algorithm transforms; energy savings; far end crosstalk interferers; low-power reconfigurable adaptive equalizers; objective function; optimization; reconfiguration strategies; very high speed digital subscriber loop; Adaptive equalizers; Adaptive filters; Adaptive signal processing; Constraint optimization; DSL; Hardware; Heuristic algorithms; Process design; Signal design; Signal processing algorithms;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.790662
Filename :
790662
Link To Document :
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