Dynamic spectrum access (DSA) allows new wireless systems to reuse the spectrum currently occupied exclusively by primary systems. A DSA system must be intelligent enough to detect primary system's activity and be flexible enough to allow new and advanced technology to be adopted to compete for spectrum access. The intelligence and flexibility make DSA system to have complex dynamic behaviors such as oscillation and fluctuation that are quite different from what was intended. They also make it difficult to guarantee the coexistence of heterogeneous DSA systems. This project develops a theoretical framework for modeling and analyzing the dynamic behavior and the coexistence of heterogeneous DSA systems. It employs many methodologies from theoretical ecology to study the cooperation, competition, altruism, selfishness, and other intelligent human-like behaviors. Two approaches are exploited to study such complex interactions among multiple spectrum access strategies: an evolutionary game theoretic approach based on an efficient Markov-model bank, and a population dynamic approach based on a spectrum-usage model. In addition, this project initiates pioneering research on DSA policy modeling and analysis by applying the two approaches.
This project builds the underlying theoretical foundation to support the development of new DSA techniques, new heterogeneous DSA systems, and new DSA policies that enhance the efficiency and fairness of spectrum access. The theoretical methodologies are useful for the development of many other heterogeneous and intelligent systems in general. This project stimulates the integration of the two traditionally disparate areas: wireless communications and theoretical ecology, in both research and education.
