Iterative decoding of convolutionally encoded signals over multipath Rayleigh fading channels

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2001-09-01

Author

Berthet, AO
Unal, BS
Visoz, R

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In this paper, we analyze and compare several strategies for iteratively decoding trellis-encoded signals over channels with memory. Soft-in/soft-out extensions of reduced-complexity trellis search algorithms such as delayed decision-feedback sequence estimating (DDFSE) or parallel decision-feedback decoding (PDFD) algorithms are used instead of conventional BCJR and min-log-BCJR algorithms. It has been shown that for long channel impulse responses and/or high modulation orders where the BCJR algorithm becomes prohibitively complex, the proposed algorithms offer very good performance with low complexity. The problem of channel estimation in practical implementation of turbo detection schemes is studied in the second part. Two methods of channel reestimation are proposed: one based on the expectation-maximization (EM) algorithm and the second on a simple Bootstrap technique. Both algorithms are shown to dramatically improve the performance of the classical pseudo-inverse channel estimation performed initially on a training sequence.

Subject Keywords

Bootstrap algorithm, Delayed decision-feedback estimation (DDFSE), Expectation-maximization (EM) algorithm, Iterative decoding, Parallel decision-feedback decoding (PDFD), Turbo detection, Turbo reestimation

URI

https://hdl.handle.net/11511/66599

Journal

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS

DOI

https://doi.org/10.1109/49.947037

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

A. Berthet, B. Unal, and R. Visoz, “Iterative decoding of convolutionally encoded signals over multipath Rayleigh fading channels,” IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, pp. 1729–1743, 2001, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66599.