The emerging cognitive radio (CR) technology opens the doorway to secondary spectrum market and significantly lowers the threshold of entry to the wireless service business. It is foreseeable that a large number of small secondary wireless service providers will appear, transforming the wireless service business from one dictated by few giant carriers to a much more competitive service market, bringing better benefits to end users. Although the allocation and utilization of secondary spectrum by CRs has been extensively studied from an engineering perspective, their economic implications are far less well understood. Because in reality the economic factor always dominates the actual deployment of technology, there is a need to revisit the secondary spectrum issues from a network economics perspective to ensure the successful deployment of CR technology in the real world. This project fulfills this need, with an emphasis on the competitive-and-cooperative relationship among various entities of the secondary spectrum eco-system, including primary spectrum providers, secondary service providers/operators, and end users.

The main intellectual merit outcome of this project includes:

1. A strategic network infrastructure sharing (NIS) framework has been proposed for contractual backup reservation between a small/local operator of limited resources and uncertain demands, and one resourceful operator with potentially redundant capacity. We have characterized the bargaining between the operators in terms of the optimal reservation prices and resource reservation quantities with considerations of the competitions between operators in market share. The conditions under which competitive operators will cooperate have also been explored.

2. A novel network sharing framework has been proposed to support coexistence of both massive IoT and high-speed cellular services in cellular spectrum. Two radio access network sharing strategies have been studied: spectrum pooling and spectrum leasing. To incentivize operators to participate sharing, we have considered two fairness criteria, namely proportional fairness and shapley value, for fair revenue division among operators. A non-orthogonal multiple access (NOMA) mechanism is also proposed to improve resource utilization efficiency for the coexistence between cellular UEs and massive IoT.

3.  We have developed a novel incentive mechanism to crowdsourcing that combines an external financial reward in the form of service price discount and users' intrinsic demand/desire for better service. Leveraging the interdependence between the service and the users in crowdsourcing, an optimal reward is derived to maximize the service provider's expected profit. The impacts of competition between service providers are also investigated.

4. A solution to the economically-optimal privacy-preserving participatory sensing problem has been developed, by which a service provider is able to recruit an optimal set of smartphones to perform a participatory sensing task covering a certain area at the minimum cost, without the need of candidate smartphone users revealing their geographic location information to the service provider, and also without the need of service provider revealing its task area to candidate smartphone users.

5. The role of information in security problem has been studied from a network economic perspective, when the target information is sold by a data broker to multiple competitive attackers. A novel multi-stage game model is proposed to characterize both the cooperative and competitive interactions of the data broker and attackers. Both the attackers' competitive equilibrium solutions and data broker's optimal pricing strategy are obtained. The study contributes to the literature by characterizing the cooperative-and-competitive behaviors of the attackers with labor specialization, providing quantitative measures of information value from an economic perspective, and thus promoting a better understanding of the profit-seeking underground community.

The broader impact outcomes of this project include:

1. This project has generated new knowledge on the network economics of the secondary spectrum eco-system. The models, algorithms, and findings developed in this project have laid a theoretical foundation for developing a more efficient secondary spectrum eco-system by leveraging the economic relationship among various constituents of the system. In addition, this project is interdisciplinary and draws methods from game theory, optimization, signal processing, networking, wireless communication, and cyber security. This research enriches all these disciplines.

2. The research outcome has been disseminated to the wireless community via publications, talks, and posters. Some of the research results have been integrated into the course materials taught by the PI at the undergraduate and graduate levels. This project has also been introduced to many high-school students at E-days of the Auburn University. This helps to foster the high-school students' interests in taking science and technology as their future career.

3. This project has supported several Ph.D. students, including three female students. Through this project, they have received rigid training in game theory, programming, statistics and random process, optimization, wireless networking, machine learning, and cyber security. In addition, they also acquired hands-on experience in the simulation and testbed development. The above training and hands-on experience will lay a solid foundation for their future career development.

Last Modified: 12/30/2019
Modified by: Tao Shu