Huffman Encoding Architecture with Self-Optimizing Performance and Multiple CAM-Match Utilization

This paper presents a method for achieving high speed and high compression ratio of Huffman encoding by updating and optimizing the code word table. A shadow code word table is continuously reconstructed according to the frequency distribution of the currently encoded symbols and used to replace the active code word table in real-time, if the compression ratio degrades. Multiple-matches in a content addressable memory (CAM) are additionally exploited to improve encoding speed to real-time requirements. A higher compression ratio can be obtained by optimizing the update timing. This paper also estimates the best method for the updating of the code word table by the simulation. As a result the compressed data size is up to 22.6% smaller than with the conventional Huffman encoding architecture, which uses a standard encoding table