Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
At the Dawn of Generative AI Era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence
A Celik, AM Eltawil - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
As we transition from the 5G epoch, a new horizon beckons with the advent of 6G, seeking a
profound fusion with novel communication paradigms and emerging technological trends …
profound fusion with novel communication paradigms and emerging technological trends …
Generative AI for integrated sensing and communication: Insights from the physical layer perspective
As generative artificial intelligence (GAI) models continue to evolve, their generative
capabilities are increasingly enhanced, and being used extensively in content generation …
capabilities are increasingly enhanced, and being used extensively in content generation …
Score-based source separation with applications to digital communication signals
We propose a new method for separating superimposed sources using diffusion-based
generative models. Our method relies only on separately trained statistical priors of …
generative models. Our method relies only on separately trained statistical priors of …
Federated quantum neural network with quantum teleportation for resource optimization in future wireless communication
B Narottama, SY Shin - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
The following study introduces FT-QNN, a federated and quantum teleportation–based
quantum neural network, utilized to optimize resource allocation for future wireless …
quantum neural network, utilized to optimize resource allocation for future wireless …
Solving inverse problems with score-based generative priors learned from noisy data
We present SURE-Score: an approach for learning score-based generative models using
training samples corrupted by additive Gaussian noise. When a large training set of clean …
training samples corrupted by additive Gaussian noise. When a large training set of clean …
Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …
Generative ai for unmanned vehicle swarms: Challenges, applications and opportunities
With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms
have received great attention from both academia and industry due to their potential to …
have received great attention from both academia and industry due to their potential to …
Generative Artificial Intelligence Assisted Wireless Sensing: Human Flow Detection in Practical Communication Environments
Groundbreaking applications such as ChatGPT have heightened research interest in
generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation …
generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation …
Temporally correlated compressed sensing using generative models for channel estimation in unmanned aerial vehicles
Bayesian modelling of the channel distribution is a crucial step before channel recovery
specially in the underdetermined scenario in multiple input multiple output (MIMO) antenna …
specially in the underdetermined scenario in multiple input multiple output (MIMO) antenna …