Soft-decision syndrome-based decoder for convolutional codes

Details Soft-decision syndrome-based decoder for convolutional codes Soft-decision syndrome-based decoder for convolutional codes

1997-06-18

1999-12-28

Moise, Emmanuel L.

Error detection/correction and fault detection/recovery

Pulse or data error handling

Digital data error correction

714786, G01R 3128

Patent

active

060095520

ABSTRACT:
A soft-decision decoder computes a maximum likelihood estimated transmitted code from a demodulated received signal with less complexity compared to a conventional Viterbi soft-decision decoder. A symbol-by-symbol detector determines a hard-decision vector from a demodulated received signal vector. A syndrome calculator multiplies the hard-decision vector by a scalar parity check matrix to calculate a syndrome vector. A syndrome modifier examines the syndrome vector for predetermined syndrome patterns corresponding to isolated errors in the hard-decision vector. Syndrome patterns are removed from the syndrome vector to create a modified syndrome vector, and the corresponding error in the hard-decision vector is recorded in an estimated error vector. A syndrome-based decoder uses the modified syndrome vector to create a simplified error trellis to produce a remaining error vector. Subtracting the estimated error vector and the remaining error vector from the hard-decision vector creates a maximum likelihood estimated transmitted code vector.

REFERENCES:
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patent: 5278871 (1994-01-01), Rasky et al.
patent: 5598422 (1997-01-01), Longwell et al.
Meir Ariel and Jakov Snyders, Soft Syndrome Decoding of Binary Convolutional Codes, IEEE Transactions On Communications, vol. 43, No. 2/3/4, Feb./Mar./Apr. 1995, pp. 288-297.

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