AuthorBienz, Richard Alan.
Committee ChairSchooley, Larry C.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe cascading or concatenation of error control codes is a well-established technique in digital communications. This type of code can yield excellent bit error rate performance. Concatenated codes that contain short memory convolutional codes are applicable to many communication links. The applications include the various combinations of modulations with memory, channels with memory and coding with memory. The Viterbi decoder is the decoder of choice for these concatenated coding schemes. Unfortunately, Viterbi decoders produce only hard decisions. The Viterbi decoders near the channel (inner decoders) therefore do not send all the available symbol information (soft decisions) to the outer decoders. Also, there are no practical decoders that produce this symbol information. The result is an unrealized coding gain. The principal contribution of this dissertation is to present a new decoder design that can be used as an inner decoder in a concatenated convolutional coding scheme. This decoder is a modified Viterbi decoder that generates soft decisions. The decoder has been named the Maximum Likelihood Paths Comparison (MLPC) decoder. The MLPC decoder uses a subset of the operations performed by a normal Viterbi decoder and therefore it is practical. The performance of the new decoder in a communication link is determined by simulation. The link uses a concatenated code that contains two convolutional codes. Both codes have a base code constraint length of 7 and rates of 1/2. The outer code is punctured to a few higher rates. Various results from these simulations are presented. The bit error rate performance of the code is excellent. The code performance also matches the theoretical upper bit error rate bound very closely for the signal-noise-ratios simulated. The complexity of the overall concatenated code system is compared to the complexity of a single convolutional code with equal performance. Using certain reasonable assumptions, the complexity of the concatenated code is roughly an order of magnitude less than the complexity of the single code.
Degree ProgramElectrical and Computer Engineering