2005) Iterative optimization for joint design of source and channel codes using genetic algorithms, Journal of the Chinese Institute of Engineers, 28:5, 803-810, ABSTRACTThis paper presents a novel algorithm for the joint design of source and channel codes. In the algorithm, channel-optimized vector quantization (COVQ) and rate-punctured convolutional coding (RCPC) are used for design of the source code and the channel code, respectively. We employ the genetic algorithm (GA) to prevent the design of COVQ from falling into a poor local optimum. We also adopt the GA to reduce the computational time needed for realizing the unequal error protection scheme best matched to the COVQ. Both the GA-based source coding and channel coding scheme are then iteratively combined to achieve a near global optimal solution for the joint design. Numerical results show that the algorithm can be an effective alternative for applications where high rate-distortion performance and low computational complexity are desired.

A novel error control algorithm for robust video transmission is presented in this paper. In the algorithm, both the source packets and parity packets are delivered in layers. Each receiver, in accordance with its available bandwidth and packet loss rate, employs the optimal policy for subscribing source layers and parity layers minimizing the average distortion of the reconstructed frames. The algorithm is able to perform fast policy adaptation for location-and time-varying network environments. The implementation of the fast adaptive algorithm is based on a novel table look-up process, in which the tables are constructed using a dynamic programming technique. Our experiments show that the algorithm is an effective alternative for video broadcast applications where the robust transmissions over the heterogeneous network environment are desired.