An Algorithm for Convolutional Codes Recognition Based on Sectionally Extracting Soft-decision Weighted Walsh HadamardTransform

doi:10.3969/j.issn.1000-1093.2015.12.012

Abstract

Abstract: An algorithm for convolutional code recognition based on sectionally extracting soft-decision weighted Walsh Hadamard transform(WHT) is proposed for the issue of convolutional code recognition in the low signal-to-noise ratio(SNR) environment. The proposed algorithm is used to obtain a soft-decision frequency sequence by using received bits’ soft-decision information, and construct a weighted Walsh Hadamard matrix to recognize the basic check sequence. The code memory length and basic generated matrix are recognized based on the construction rule of basic encoding matrixt. The algorithm has the reduced run storage space. Simulation results show that the algorithm could recognize the convolutional codes with different coding rates in the low SNR environment, and has good fault-tolerant performance, which is improved greatly especially in recognition of long restraint-length convolutional codes.

Key words: information processing technology, convolutional codes recognition, low signal-to-noise ratio, soft-decision information, weighted Walsh Hadamard transform, section extraction

CLC Number:

TN911.7

ZHANG Dai, ZHANG Yu, YANG Xiao-jing, FAN Bin-bin. An Algorithm for Convolutional Codes Recognition Based on Sectionally Extracting Soft-decision Weighted Walsh HadamardTransform[J]. Acta Armamentarii, 2015, 36(12): 2298-2305.

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