Cognitive Tactical Radios: Cognition Through Learning and Strategy (CLearStrategy)
Abstract
This project aims to address and solve key sensing, learning, strategic decision and resource allocation issues in the design of a cognitive tactical radio (CTR). Such a tactical radio has superior ability in learning its spectrum environment, possibly highly dynamic, and can behave intelligently and strategically in the presence of multiple other completing or collaborating tactical radios. Our research agenda consists of the following four integral tasks: (T1) robust spectrum sensing of multiple channels using adaptive group testing, (T2) multiuser learning and its regret, (T3) convergence of multiuser learning to pure Nash equilibrium (PNE) in spatial congestion games, and (T4) globally optimal spectrum sharing through game-theoretic and mechanism design-theoretic frameworks. We have successfully completed these tasks. The research undertaken by the project can have significant impact both theoretically and in practice. In particular, our contributions in the areas of game theory and online learning theory are quite general and therefore more broadly applicable to other areas of networking as well as decentralized multi-agent systems, well beyond the context of cognitive radio design.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 08, 2012
- Accession Number
- ADA586790
Entities
People
- Mingyan Liu
Organizations
- University of Michigan