4 citations · 4 across the 3 of their papers we have counts for
5 papers
Conditional Denoising Diffusion Autoencoders for Wireless Semantic Communications
Mehdi Letafati, Samad Ali, Matti Latva-aho
Semantic communication (SemCom) systems aim to learn the mapping from low-dimensional semantics to high-dimensional ground-truth. While this is more akin to a "domain translation"…
A Bayesian Framework of Deep Reinforcement Learning for Joint O-RAN/MEC Orchestration
Fahri Wisnu Murti, Samad Ali, Matti Latva-aho
Multi-access Edge Computing (MEC) can be implemented together with Open Radio Access Network (O-RAN) over commodity platforms to offer low-cost deployment and bring the services cl…
Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models
Mehdi Letafati, Samad Ali, Matti Latva-aho
Diffusion models are at the vanguard of generative AI research with renowned solutions such as ImageGen by Google Brain and DALL.E 3 by OpenAI. Nevertheless, the potential merits o…
Denoising Diffusion Probabilistic Models for Hardware-Impaired Communications
Mehdi Letafati, Samad Ali, Matti Latva-aho
Generative AI has received significant attention among a spectrum of diverse industrial and academic domains, thanks to the magnificent results achieved from deep generative models…
Diffusion Models for Wireless Communications
Mehdi Letafati, Samad Ali, Matti Latva-aho
A comprehensive study on the applications of denoising diffusion models for wireless systems is provided. The article highlights the capabilities of diffusion models in learning co…