Sensing the State of Voice Sources to Improve Multiplexer Performance

The control of source-coded traac at a multiplexer has been a topic of extensive research. Traditional approaches typically use feedback information on the buuer level in designing the control policy. While important , buuer levels capture only part of the information about the overall system state. By setting up this problem as a Markov decision process, we show that using information on the state (activity) of the sources, in addition to the buuer level, can result in signiicant improvements over traditional approaches. We demonstrate this for a multiplexer fed by {law encoded voice sources. Some of the scenarios we study exhibit a reduction in distortion exceeding 35%. In general, the improvement is heavily dependent on the correlation statistics of the sources. Emulations validate the analysis. The form and characteristics of the optimal control policies are also discussed.