GUI for Simulating Convolutional Coding & Viterbi Decoding in MATLAB
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This book describes the way convolutional encoder and Viterbi decoder perform coding and decoding in a communication system using MATLAB. A convolutional code is one of the channel codes used extensively in communication systems in order to ensure error-free at the receiving end. Mobile transmission is not free from channel impairment such as noise, interference, and fading which cause signal distortion and degradation in signal to noise ratio (SNR). To overcome these problems, Convolutional coding and Viterbi decoding was introduced to determine the bit error rate of every single transmitted ...
This book describes the way convolutional encoder and Viterbi decoder perform coding and decoding in a communication system using MATLAB. A convolutional code is one of the channel codes used extensively in communication systems in order to ensure error-free at the receiving end. Mobile transmission is not free from channel impairment such as noise, interference, and fading which cause signal distortion and degradation in signal to noise ratio (SNR). To overcome these problems, Convolutional coding and Viterbi decoding was introduced to determine the bit error rate of every single transmitted signal. A communication channel with the rate convolutional codes and constraint length (K) of 3 were used for both hard decision and Soft decision Viterbi decoding. In order to visualize the effect of hard decision and Soft decision in decoding convolutional codes, simulation method is carried out in MATLAB. The simulation plots of BER versus Energy per bit to noise power spectral density ratio (Eb/No) was used to evaluate the performance of hard decision and soft decision decoding in Additive white Gaussian Noise (AWGN). Further analysis and discussion is made based on the results.
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