This project centers on investigating network architectures and abstractions for system-level optimization of wireless networks operating in an interference-limited regime. The central idea is to coordinate network transmissions so they are 'aligned' with the character of the traffic and environment.
The research leverages data mining techniques to generate coarse traffic abstractions, capturing the salient characteristics of the spatio-temporally-diverse traffic and environment. These abstract traffic loads drive a slower time-scale system-level optimization of coordinated transmission schedules across neighboring base stations, while allowing faster (local) dynamic scheduling driven by the realizations of individual user traffic and dynamic interference. The research draws on tools from adaptive, robust and stochastic optimization for both analysis and algorithmic development. The research agenda is unique in that it develops an integrated view and foundational design principles needed to realize the coupling of individual user dynamics with problems ranging from measuring and abstracting user population traffic/environment to network coordination. Preliminary results suggest that this approach has the potential to enable substantial reductions in interference and average power usage, while increasing coverage and service uniformity.
This work can drive beneficial changes in current and future wireless technologies and standards. U.T. Austin's Wireless Networking and Communications Group's (WNCG) strong ties with industry provide concrete opportunities for this work to have a broader impact. In addition, this project includes education-based initiatives, including curriculum development, training of graduate students, and involvement of undergraduates, exposing them to research and industry in an integrated manner.
