The objective of this project is to design real-time temporal-spatial spectrum sharing, trading and accessing schemes to improve the network performances by fully exploiting the channel availability (e.g., spatial, temporal, and spectral) and quality (e.g., signal to interference plus noise ratio and data rate) diversities. PIs focus on 1) designing a rigorous mathematical model for spectrum sharing; 2) designing efficient auction-based real-time spectrum allocation methods; 3) studying the schedulability of periodic channel usage requests, and the robustness of the designed protocols; 4) designing effective distributed real-time channel sensing, probing, accessing and routing strategies using online optimization techniques for multihop cognitive radio networks; 5) evaluating and testing the performances of proposed algorithms and methodologies using cognitive radio network testbeds.
The intellectual merit is that the proposed research offers both theoretical and systematic methods to address some not well-understood key problems (e.g., zero-regret online spectrum sensing and accessing, robustness of protocols), and propose novel approaches (e.g., networked multi-armed bandit) to tackle these challenging problems. This project further enhances the understanding and designing of efficient real-time algorithms for multihop cognitive radio networks using resources opportunistically with unpredictable online requests and external disturbances.
The broader impacts are that solutions proposed in this study alleviate the spectrum shortage problem and take advantage of the remarkable strength of cognitive radio technology. The proposed research rigorously integrates and thus sheds light on theory, algorithm design and analysis, protocol design and system implementation of cognitive radio networks.
