100 citations · 295 across the 30 of their papers we have counts for
6 papers · 1 filter
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…
Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications
Mehdi Letafati, Samad Ali, Matti Latva-aho
In this paper, conditional denoising diffusion probabilistic models (DDPMs) are proposed to enhance the data transmission and reconstruction over wireless channels. The underlying…
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…
Probabilistic Constellation Shaping With Denoising Diffusion Probabilistic Models: A Novel Approach
Mehdi Letafati, Samad Ali, Matti Latva-aho
With the incredible results achieved from generative pre-trained transformers (GPT) and diffusion models, generative AI (GenAI) is envisioned to yield remarkable breakthroughs in v…