Convolutional(2,1,6) Encoder with Soft Decision Viterbi Decoder Implementation
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Resource Overview
Previously uploaded version contained errors - now corrected and fully functional. This implementation features a rate 1/2 convolutional encoder with constraint length 6 and soft-decision Viterbi algorithm for optimal decoding performance.
Detailed Documentation
The previously uploaded Convolutional(2,1,6) Encoder and Soft Decision Viterbi Decoder contained some errors that have now been corrected. The implementation now functions properly and is ready for use.
The encoder employs a rate 1/2 convolutional coding scheme with constraint length 6, generating two output bits for each input bit using a shift register structure with polynomial generators. The Viterbi decoder utilizes soft-decision input (typically 3-8 bit quantization) to improve error correction performance by calculating path metrics through additive white Gaussian noise (AWGN) channel models. Key features include traceback decoding for optimal path selection and branch metric computation using Euclidean distance measurements.
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