Nonbinary Convolutional Coding For Multimedia Data Transmission

ABSTRACT: In this thesis, the performance of nonbinary convolutional coding technique is investigated and new nonbinary codes with better performance are proposed. Nonbinary convolutional coding technique is a coding technique which is similar to the binary convolutional codes with the same decoding strategy but they are designed for general nonbinary sources. The nonbinary convolutional coding technique is described and simulated under various channel conditions. Synthetic nonbinary source sequences are produced by using Markov processes. The channels used in the experimental simulations include additive white Gaussian noise (AWGN) and flat fading channel models. Coded image and video sequences are transmitted over the channels by using binary phase shift keying (BPSK) modulation technique. The Viterbi decoding algorithm is used for decoding the encoded sequences. Viterbi decoding employs hard and soft decision metrics. The soft metric is updated to include the source statistics. This enables the decoder to use the source redundancy for improved decoding performance. Results show that nonbinary convolutional coding which uses the source statistic is effective in reducing bit error rate (BER). New nonbinary convolutional coding is optimized to increase the code distance (). The optimized codes are shown to perform better at low BER.freedv. Keywords: Error Control coding, Convolutional codes, Source metric. ……………………………………………………………………………………………………………………………………………………………………………………………………………………