Matching Theory Framework for 5G Wireless Communications



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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.



Matching theory, 5G communications


Portions of this document appear in: Gu, Yunan, Walid Saad, Mehdi Bennis, Merouane Debbah, and Zhu Han. "Matching theory for future wireless networks: Fundamentals and applications." IEEE Communications Magazine 53, no. 5 (2015): 52-59. And in: Gu, Yunan, Yanru Zhang, Miao Pan, and Zhu Han. "Matching and cheating in device to device communications underlying cellular networks." IEEE Journal on Selected Areas in Communications 33, no. 10 (2015): 2156-2166. And in: Gu, Yunan, Yanru Zhang, Miao Pan, and Zhu Han. "Student admission matching based content-cache allocation." In 2015 IEEE Wireless Communications and Networking Conference (WCNC), pp. 2179-2184. IEEE, 2015. And in: Gu, Yunan, Chunxiao Jiang, Lin X. Cai, Miao Pan, Lingyang Song, and Zhu Han. "Dynamic path to stability in LTE-unlicensed with user mobility: A matching framework." IEEE Transactions on Wireless Communications 16, no. 7 (2017): 4547-4561. And in: Gu, Yunan, Lin X. Cai, Miao Pan, Lingyang Song, and Zhu Han. "Exploiting the stable fixture matching game for content sharing in D2D-based LTE-V2X communications." In 2016 IEEE Global Communications Conference (GLOBECOM), pp. 1-6. IEEE, 2016. And in: Gu, Yunan, Zheng Chang, Miao Pan, Lingyang Song, and Zhu Han. "Joint radio and computational resource allocation in IoT fog computing." IEEE Transactions on Vehicular Technology 67, no. 8 (2018): 7475-7484. And in: Raveendran, Neetu, Yunan Gu, Chunxiao Jiang, Nguyen H. Tran, Miao Pan, Lingyang Song, and Zhu Han. "Cyclic Three-Sided Matching Game Inspired Wireless Network Virtualization." IEEE Transactions on Mobile Computing (2019). And in: Gu, Yunan, Li Wang, Miao Pan, and Zhu Han. "Exploiting the stable fixture matching game for mobile crowd sensing: A local event sharing framework." In 2017 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE, 2017.