Hybrid Maximum Likelihood Decoding for Linear Block Codes

Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Enterprise Software
Format: PDF
In this paper, the authors propose a hybrid Maximum Likelihood Decoding (MLD) for linear block codes. For the reliable data transmission over noisy channels, convolutional and block codes are widely used in most digital communication systems. Much more efficient algorithms have been found for using channel measurement information in the decoding of convolutional codes than in the decoding of block codes. Word correlation method can be utilized to use channel measurement information in the decoding of block codes. However as the number of code words become larger, the decoding complexity increases dramatically to the power of the number of information bits.

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