The prevalence of high-performance mobile devices such as smartphones and tablets has brought fundamental changes to the existing wireless networks. The growth of multimedia and location-based mobile services has exponentially increased the network congestion and the demands for more wireless resources. The extremely high computational complexity and communication overhead resulting from the conventional centralized resource management methods are no longer suitable to capture the scale of tomorrow’s wireless networks. As a result, the resource management in next-generation networks is shifting from the centralized optimization to the self-organizing solutions. The goal of this thesis is to demonstrate the effectiveness of matching theory, a powerful operational research framework, for solving the wireless resource allocation problems in a distributed manner. Matching theory, as a Nobel-prize winning framework, has already been widely used in many economic fields. More recently, matching theory has been shown to have a promising potential for modeling and analyzing wireless resource allocation problems due to three reasons: (1) it offers suitable models that can inherently capture various wireless communication features; (2) the ability to use notions, such as preference relations, that can interpret complex system requirements; (3) it provides low-complexity and near-optimal matching algorithms while guaranteeing the system stability. This dissertation provides a theoretical research of implementing the matching theory into the wireless communication fields. The main contributions of this dissertation are summarized as follows. An overview of the basic concepts, classifications, and models of the matching theory is provided. Furthermore, comparisons with existing mathematical solutions for the resource allocation problems in the wireless networks are conducted. Applications of matching theory in the wireless communications are studied. Especially, the stable marriage model, the student project allocation model and so on are introduced and applied to solve the resource allocation problems, such as the device-to-device (D2D) communication, LTE-Unlicensed, and so on. Both theoretical and numerical analysis are provided to show that matching theory can model complex system requirements, and also provide semi-distributive matching algorithms to achieve stable and close-optimal results. The potential and challenges of the matching theory for designing resource allocation mechanisms in the future wireless networks are discussed.Electrical and Computer Engineering, Department o
