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Xiaowen Gong
Researcher at Auburn University
Publications - 69
Citations - 1901
Xiaowen Gong is an academic researcher from Auburn University. The author has contributed to research in topics: Wireless network & Edge computing. The author has an hindex of 21, co-authored 63 publications receiving 1380 citations. Previous affiliations of Xiaowen Gong include University of Alberta & Arizona State University.
Papers
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Journal ArticleDOI
Exploiting social ties for cooperative D2D communications: a mobile social networking case
TL;DR: A coalitional game-theoretic framework is developed to devise social-tie-based cooperation strategies for D2D communications and results corroborate that the proposed mechanism can achieve significant performance gain over the case without D1D cooperation.
Journal ArticleDOI
When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multitimescale Resource Management for Multiaccess Edge Computing in 5G Ultradense Network
TL;DR: In this article, the authors proposed an intelligent UDEC (I-UDEC) framework, which integrates blockchain and artificial intelligence (AI) into 5G UDEC networks, and designed a novel two-timescale deep reinforcement learning (2Ts-DRL) approach.
Proceedings ArticleDOI
Social trust and social reciprocity based cooperative D2D communications
TL;DR: A coalitional game theoretic framework is developed to devise social-tie based cooperation strategies for device-to-device communications and a network assisted relay selection mechanism is developed that can achieve up-to 122% performance gain over the case without D2D cooperation.
Journal ArticleDOI
Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity Under Fading Channels in Cognitive Radio Networks
TL;DR: This paper studies optimal bandwidth and power allocation in a cognitive radio network where multiple secondary users (SUs) share the licensed spectrum of a primary user (PU) under fading channels using the frequency division multiple access scheme.
Journal ArticleDOI
Intelligent Cooperative Edge Computing in Internet of Things
TL;DR: The prototype-based evaluation indicates that the intelligent cooperative edge (ICE) computing architecture enables a benign combination of AI and edge computing, which helps some key issues of edge computing achieve a better solution using the localized AI.