NeTS: Small: Spectrum Sensing and Resource Allocation for Cognitive Radio Networks

George Mason University, Fairfax VA

Investigators

Abstract

Radio spectrum has become an increasingly expensive and scarce resource due to the exponential growth of the wireless industry and the rapid proliferation of wireless devices over the past couple of decades. Ironically, studies of spectrum usage have shown that much of the available spectrum is highly underutilized, due to the current policy of static allocation, which partitions the spectrum into various licensed bands. The main goal of this project is to develop a cost-effective solution to the spectrum scarcity issue based on emerging cognitive radio technology, which has the potential to allow unlicensed users to reclaim unused spectrum in the licensed bands. A cognitive radio is capable of detecting unused or idle spectrum and dynamically tuning its transmission and reception activities to the so-called spectrum holes. A group of unlicensed users equipped with cognitive radios can form a network and communicate with each other via such spectrum holes. This research focuses on developing efficient and accurate methods for cognitive radios to identify spectrum holes and allocate this spectrum to enable communications among unlicensed users without causing harmful interference to the licensed users of a spectrum band. A major challenge of this work lies in how to perform spectrum sensing and resource allocation in a cognitive radio network to maximize its capacity while managing the additional interference and overhead incurred by the cognitive radios. If the project is successful, the research results should have a significant impact on increasing the capacity and performance of future wireless networks. The research is expected to advance the field of cognitive radio and contribute towards its adoption in commercial applications. The results of this research will be applicable to future infrastructured wireless networks, as well as wireless communications in emergency scenarios such as disaster relief. An experimental platform will be developed to prototype and evaluate the effectiveness of the proposed dynamic spectrum access approach in practical wireless environments. Students, including some from underrepresented groups, will gain practical experience from working with the cognitive radio testbed. New course materials will be developed to teach the basics of cognitive radio technology to students at the graduate level. The technical approach of this research centers on a joint consideration of spectrum sensing and resource allocation, taking into account the three main dimensions of spectrum holes, i.e., time, space, and frequency. A multidimensional characterization of spectrum holes will be developed, which incorporates a bivariate Markov chain to model temporal dynamics, power control in the context of spatial spectrum sensing, and frequency-domain search for spectrum holes in the wideband regime. A model of a cognitive radio network based on simplicial homology will be developed to allocate spectrum resources among cognitive radio nodes, as well as the communication and computational resources required for spectrum sensing, to optimize performance from a networking perspective. Interference modeling and management for the cognitive radio network will be addressed in conjunction with resource allocation. The project will study tradeoffs among communications and computational resources within the proposed framework for dynamic spectrum access. An important component of the project is the development of a cognitive radio network testbed based on an open software radio platform, which will be used to prototype and evaluate the performance of the proposed algorithms and protocols in realistic wireless scenarios.