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Shahid Mumtaz

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#reinforcement learning Open access Nov 2026

Energy-aware routing in underwater wireless sensor networks via temporal graph neural network and reinforcement learning

Underwater wireless sensor networks (UWSN) are characterized by dynamic network topology, limited node energy, and constrained communication capabilities, which make reliable and energy-efficient data transmission a significant challenge in time-varying underwater environments. Conventional routing approaches, usually...

Cai-Xia Cai, Chao-Yun Pu, Wen-Yang Gan et al. · 0 citations
2026

Spectral Efficiency Maximization for STAR-RIS-Assisted mmWave-NOMA Downlink Communication Systems

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can reconstruct indirect links when the direct link is blocked for millimeter wave (mmWave) communications. Moreover, the spectral efficiency of non-orthogonal multiple access (NOMA) can benefit from the highly directional transmis...

Fuyuan Xu, Ruirui Chen, Yong-Tao Liu et al. · 0 citations
2026

Robust Secure Precoding for Wireless Information and Power Transfer in RSMA-Based LEO Satellite Communications

Satellite-terrestrial integrated networks with simultaneous wireless information and power transfer (SWIPT) provide wide-area connectivity and sustainable service support, but they also face serious security challenges due to the broadcast nature of satellite links and the possibility that an energy receiver may act as...

Meng-Yan Huang, Xing-Wang Li, Chengjun Jiang et al. · 0 citations
2026

Energy-Aware Federated Distillation via Quantum-Driven Task Offloading in LEO Satellite Networks

Low earth orbit (LEO) satellite networks have emerged as a key enabler for delivering real-time and global services to distributed terrestrial nodes, particularly in remote regions. To preserve data privacy, federated learning (FL) provides a decentralized framework for advancing artificial intelligence (AI) in complex...

Pengxiang Qin, Dongyang Xu, Lei Liu et al. · 0 citations

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