Interference Suppression Research Of Sequential Image Transmission In Wireless Channel

The sequential image must be compressed before it can be transmitted in wireless channel, because of the large amount of image data. But most of the image compression algorithms are highly sensitive to channel noise, it is necessary to use error correction coding if we use compression to the sequential image. As far as image Communication is considered, both high reliability and good real-time performance are needed. In this thesis, the code used in the channel is convolutional code. Two main decoding method, Viterbi Algorithm and Sequential Algorithm, are experimented respectively. Viterbi Algorithm is used for short constraint convolutional codes, but its error correction ability is limited. Sequential Algorithm can be used for long constraint convolutional codes, to obtain better error correction performance than Viterbi Algorithm does. Moreover, this algorithm can adjust amount of computation according to the degree of noise interference, and save as much decoding time as possible. So its real-time performance is good. Because Sequential Algorithm only searches one path, whenencountering severe noise interference, it may easily lose correct path. A new method of combining both Genetic Algorithm and Sequential Algorithm is proposed in this thesis. This method uses population search strategy and processes several paths simultaneously, so it can obtain good error correction effect.