| Paper: | SPCOM-P4.2 | ||
| Session: | Iterative Decoding Algorithms and Architectures | ||
| Time: | Wednesday, May 19, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing for Communications: Detection, Estimation, and Demodulation | ||
| Title: | SWITCHING LMS LINEAR TURBO EQUALIZATION | ||
| Authors: | Seok-jun Lee; University of Illinois at Urbana-Champaign | ||
| Andrew C. Singer; University of Illinois at Urbana-Champaign | |||
| Naresh Shanbhag; University of Illinois at Urbana-Champaign | |||
| Abstract: | Turbo equalization using linear filters for data detection hasbeen shown to perform nearly as well as those based on the original maximum a posteriori probability (MAP) detectionapproach. Such linear equalization methods have taken on manyforms in the literature, from simple least-mean-square (LMS)-based adaptive filtering approaches, to minimum meansquare error (MMSE)-based methods that arerecursively computed for each output symbol for each iteration.In this paper, we consider a class of turbo equalizationalgorithms in which complexity requirements dictate that a fixedset of filter coefficients must be used for all symbols and for all iterations. By computing one such set of coefficients viathe LMS algorithm assuming unreliable soft information, and another set assuming highly reliable soft information, we show that a switching strategy can be employed, nearly achieving the performance of recomputing the coefficients at each iteration. | ||
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