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Creators/Authors contains: "Zhang, Zhi-Li"

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  1. ; ; ; ; ; ; ; (, Transactions on Machine Learning Research)
    Free, publicly-accessible full text available December 1, 2026
  2. ; ; ; ; (, IEEE Milcom 2026)
    In this paper we develop a novel disruptionresilient approach for real-time, high-resolution sensor data delivery over multiple wireless channels for military autonomous systems such as drones, autonomous vehicles and robots. We design two innovative neural multiple description codecs (neural MDCs) which compress and encode images into multiple independently decodable and mutually refineable streams. Our approach not only achieves high compression efficiency, but also enables the effective use of multiple diverse radio channels for real-time delivery of high-resolution sensor data while ensuring disruption resiliency. Using benchmark image/video sensor datasets as well as real-world 5G traces, we evaluate and demonstrate the efficacy of both neural MDC codecs for highresolution sensor data streaming over multiple radio channels under various jamming scenarios. 
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    Free, publicly-accessible full text available October 7, 2026
  3. ; ; ; ; ; ; ; ; ; ; et al (, Proceedings of the ACM on Networking)
    5G and future 6G networks deploy cells with diverse combinations of access technologies, architectures, and radio frequency bands/channels. Cellular operators also employ carrier aggregation for higher data access speeds. We investigate the fundamental question of how to intelligently and dynamically configure and reconfigure a user equipment's serving cells to deliver the best network performance. Through comprehensive measurements across 12 cities in 5 countries, we experimentally show the wide availability, heterogeneity, and untapped performance gains of today's cell deployments. We then present a principled, performance-driven connectivity management framework, dubbed OPCM. It is a centralized solution deployed at the base station, allowing it to coordinate multiple UEs, enforce operator policies, and facilitate user fairness. Extensive evaluations show that OPCM improves the application QoE by up to 65.2%. 
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    Free, publicly-accessible full text available November 24, 2026
  4. ; ; ; (, IEEE Transactions on Cognitive Communications and Networking)
    Full Text Available 
  5. ; ; ; ; ; ; ; ; (, ACM)
    Free, publicly-accessible full text available February 26, 2026
  6. ; ; ; (, IEEE)
    Full Text Available 
  7. ; ; ; ; ; ; ; (, IEEE Transactions on Wireless Communications)
    Full Text Available 
  8. ; ; ; ; ; (, IEEE)
    Full Text Available 
  9. ; ; ; ; ; ; ; (, IEEE)
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  10. ; ; ; ; ; (, IEEE)
    Full Text Available