The focus of this project is on optimal resource allocation and control in collaborative cognitive radio networks (CRNs). Through opportunistic access to the available spectrum, CRNs aim at improving the utilization of network resources by achieving higher spatial reuse, programmable connectivity, and increased network availability. The research agenda includes centralized analytical formulations that aim at optimizing the operation of the bottom three layers as well as distributed routing and medium access protocols that implement the outcomes of such optimization. Joint optimization of spectrum, transmission powers, and rates for CR communications will be considered in the presence of several primary (spectrum-licensed) radio networks (PRNs).

No feedback from the PRNs will be assumed. Several formulations will be studied, which differ in the assumptions made on the channel dynamics (indirectly, user mobility), optimization window (packet vs. flow time scale), and availability or otherwise of power masks. Besides one-hop optimizations, the project will also consider multi-channel, multi-path optimizations at the packet and the flow time scales. The optimization results will then be integrated into the design of distributed channel access and path discovery/maintenance protocols for opportunistic CRNs. Depending on the frequency bands of interest, fixed power masks on CR transmissions may or may not be available. Protocols will be developed for both cases. In the absence of a fixed power mask, statistical modeling of PR interference will be conducted and used in the design of a MAC protocol that supports a probabilistic guarantee on the outage rate of PR receptions. The treatment will extend to both connectionless and connection-oriented applications. The cross-disciplinary nature of this project is expected to have a profound impact on many wireless technologies used in both civilian and military applications, including sensor networks, mesh networks, military radios, and wireless LANs. The optimization framework provides a general methodology that can significantly improve the performance, connectivity, and inter-operability of resource-constrained wireless networks in general.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Application #
0721935
Program Officer
Joseph Lyles
Project Start
Project End
Budget Start
2007-09-01
Budget End
2011-08-31
Support Year
Fiscal Year
2007
Total Cost
$344,394
Indirect Cost
Name
University of Arizona
Department
Type
DUNS #
City
Tucson
State
AZ
Country
United States
Zip Code
85721