The objective of a digital communication system is to provide accurate transmission of information from one location to another. During transmission, the signal is subjected to noise and other distortions that compromise the integrity of the information. Channel encoding techniques can be employed to reduce this loss of integrity. One technique that has become popular in space and satellite communication systems is convolutional coding.
Channel encoding is only practical if it provides substantial improvement over the uncoded signal with a moderate hardware investment. The optimal approach to decoding convolutional codes is the Maximum-Likelihood method. This method compares the received data sequence to all possible sequences and chooses the sequence that provides the best match. Unfortunately, the number of possible sequences (and the complexity of the decoder) grows exponentially with the length of the message. Therefore, a hardware implementation of this algorithm is impossible. The Viterbi algorithm, on the other hand, uses the recurrent properties of convolutional codes to provide an efficient solution to the Maximum-Likelihood decoding problem.
A new PC-based simulator for the design and analysis of convolutional codes using the Viterbi decoding algorithm is introduced. The simulator allows the user to interactively design and test convolutional codes using a desktop computer. All parameters such as constraint length, decode depth and encoder configuration are accessible through a "user-friendly" menu driven interface. In addition, the theory of convolutional coding, and an explanation of how error correction is achieved are presented. The Maximum-Likelihood decoding algorithm is described and the transformation to the Viterbi algorithm is developed.
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Belkerdid, Madjid A.
Master of Science (M.S.)
College of Engineering
Length of Campus-only Access
Masters Thesis (Open Access)
Rossman, Mark W., "A PC-Based Simulation for Convolutional Codes Using Viterbi Decoding" (1987). Retrospective Theses and Dissertations. 5078.
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