Multiple-input multiple-output (MIMO) technology provides a means of boosting network capacity without requiring additional spectrum by exploiting spatially multiplexing, interference suppression, and spatial diversity. It has received widespread attention over the past decade from both industry and academic researchers, now forming a key component of nearly all emerging wireless standards. Despite the huge promise and considerable attention, a rigorous algorithm-theoretic framework for maximizing network capacity in multihop wireless MIMO networks is missing in the state of the art. This project establishes both the computational hardness and approximation hardness of maximizing network capacity in multihop wireless MIMO networks, and develops practical approximation algorithms with provably good performance. A polyhedral approach is taken by the project to construct various polynomial approximate capacity subregions of multihop wireless MIMO networks. These approximate capacity subregions not only are the algorithmic foundation of maximizing network capacity in multihop wireless MIMO networks, but also serve as a basis for interesting future projects on cross-layer design and optimizations in multihop wireless MIMO networks. They are also of independent interest to the theoretical computer science community and communications community at large. This project provides scholarships to graduate students and offers research topics for strong dissertation works on multihop wireless networks. The outcome of this project will not only be disseminated to the professional researchers through journals and conference proceedings, but also be integrated into the lecture notes targeted for senior undergraduate students and graduate students.
