IEEE

Hybridizing Spiking Neural Networks and Federated Quantum Learning for Resource Optimization in Next-Gen 6G Architectures

Abstract: The call for 6G networks to evolve rapidly into ultra-low latency, high energy efficiency, and intelligent resource allocations is immediate. In this paper, we propose a Holographic Edge ...
IEEE

Reliable Multidimensional Resource Scheduling for Heterogeneous Computing Networks via Coded Distributed Computing and Hypergraph Neural Networks

Abstract: The emergence of 6G applications, such as artificial intelligence, augmented reality, and digital twins has imposed stringent requirements on the high reliability, low latency, and energy ...