Efficient use of limited spectrum is emerging as a major issue in wireless systems. The proposed work focuses on technologies that provide better understanding of wireless networks and greatly enhance spectrum efficiency. with three coupled thrusts: (i) wireless network modeling; (ii) mechanisms for efficient spectrum sharing; and (iii) exploiting enhanced spectrum efficiency for wireless video communications. The project also includes an experimental research component in which the developed approaches will be implemented and tested on the cognitive radio testbed hosted at Virginia Tech and the cooperative networking testbed hosted at NYU-Poly.
The proposed research plans to systematically investigate several of the unique technical challenges and open problems in enhancing radio spectrum efficiency, and supporting emerging video services. This fundamental research will support the development of technologies that achieve new levels of efficiency and quality in wireless broadband services, and will help alleviate the wireless bandwidth limits now being experienced. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the centers portfolio. The PIs plan to disseminate the work to their industry members and the broader industry and academic community via open-source software as wel as introduce the content within their degree and outreach programs.
Please note this was a multi-university, one year project with modest funding -- very small in scope. Despite this, we were able to accomplish three significant outcomes. First, we developed a general spatial model for cellular communication networks based on Determinantal Point Processes (DPPs). The nation's wireless network is one of its most critical technology assets, but the locations of base stations are not well understood. This model is a random model that is flexible and can capture all the key features, enabling improved design and optimization. We also developed new analytical tools for working with these DPPs. Second, we fit real BS data supplied by Crown Castle, one of the nation's largest BS owners, to our model in order to validate and improve it. Third, we have now ported these results over to the case of dynamic spectrum access, managed by a database, as is relevant for the EARS program at NSF (of interest to FCC and many others). We submitted a novel proposal to EARs based on this work, and expect that the outcomes in that direction will bear significant fruit in the years to come. For example, we will be able to show the blocking probabilities if licensed spectrum users share the spectrum with new "best effort" users.
