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Author

Muhammad Usman

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#machine learning Preprint Oct 2026

Energy Saving in 5G and Beyond Networks: A Quantum Reinforcement Learning Approach

Energy saving has become a critical challenge in 5G and beyond networks. The rapid growth of connected devices has increased the overall network energy demand, driving operational expenditure to unsustainable heights. The Base Station (BS) accounts for the largest share of energy usage, typically consuming around 60-70...

Muhammad Usman, H. V. Nguyen, M. Lezzi et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Quantum Reinforcement Learning for Cost and Delay Tradeoffs in Quantum Cloud Orchestration

Quantum cloud computing, delivered through the quantum-as-a-service (QaaS) model, provides access to quantum computing resources. However, applying uniform time-based pricing across fundamentally heterogeneous quantum resources significantly complicates task orchestration, particularly when addressing the tradeoff betw...

An N. H. Phan, Dang van Huynh, Muhammad Usman et al. · 0 citations

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