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A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks

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Published in:IEEE Access
Format: Online Article RSS Article
Published: 2026
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spellingShingle A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Computer Science & Information Science
Computer Science & IT
Engineering & Technology
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
subject_facet Computer Science & Information Science
Computer Science & IT
Engineering & Technology
title A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_auth A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_full A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_fullStr A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_full_unstemmed A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_short A Hybrid Quantum-Meta Reinforcement Learning and Graph Attention Transformer Approach for Low-Latency and a Secure D2D Routing in 6G Cellular Networks
title_sort a hybrid quantum-meta reinforcement learning and graph attention transformer approach for low-latency and a secure d2d routing in 6g cellular networks
topic Computer Science & Information Science
Computer Science & IT
Engineering & Technology
url http://ieeexplore.ieee.org/document/11396630