An analytical framework for the design of intelligent algorithms for adaptive-rate MPEG video encoding in next-generation time-varying wireless networks

Adaptive rate video encoding is required to maximize efficiency when wireless links are involved in the communication. In fact, wireless channels are characterized by high, time-varying bit error rates. To cope efficiently with this problem adaptive forward error correction schemes have been proposed. These schemes introduce an amount of redundancy dependent on the channel conditions. Accordingly, the bandwidth available at the application layer changes: it increases when channel conditions improve, and decreases when channel conditions worsen. Obviously, the encoding parameters must be tuned to adapt the video source transmission rate to the available bandwidth. This adaptation is achieved by means of appropriate feedback laws, which are relationships between the encoding parameters to be used and other variables representing the state of the system. An analytical framework is introduced which can be used for the design of the feedback laws. To this purpose both the channel and the video source are modeled by means of Markov models. The resulting model of the whole system is denoted as SBBP/SBBP/1/K. Analysis is derived which allows to evaluate the most significant performance measures and, therefore, to design optimal feedback laws.