Multicasting, where common information is transmitted from a source to multiple destinations, is the core component of many network applications such as multimedia distribution, information update, group conferencing, etc. Creative encoding of network trac at the intermediate terminals can significantly improve the throughput of a multicast over conventional replicate-and-forward approaches. Due to the open nature of the wireless medium, communication throughput of a wireless link depends on its transmission power and on the interference generated by nearby network terminals. The goal of this research is to develop a systematic framework for maximizing a general multicast utility function via the joint optimization of transmission power, rate, and schedule, within the framework of network coding.
The investigators model a wireless ad hoc network by means of a topology graph, which contains point-to-point links and point-to-multipoint hyperarc links with coupled link throughput capacities. Under the assumption of optimal network coding, the research first develops an iterative gradient-steering" optimization framework. A network utility maximization problem is converted to a transmission scheduling problem that maximizes an approximated utility in its gradient direction, coupled with a steering vector update that continuously updates the approximated utility and its instantaneous gradient direction. The research then extends the framework to utility maximization for a network with multiple multicast sessions. Finally, the research develops distributed algorithms to optimize a global utility of a large scale network using local controllers. In addition to the planned research, the investigators will also try to extend the algorithm to ad hoc networks with time varying channels where utility maximization requires efficient exploitation of the channel diversity gain.
