Iterative Optimization for Joint Design of Source and Channel Codes Using Genetic Algorithms

This 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.