Search Results for author:
Found 2 papers, 0 papers with code
Foundation Model Based Native AI Framework in 6G with Cloud-Edge-End Collaboration
Future wireless communication networks are in a position to move beyond data-centric, device-oriented connectivity and offer intelligent, immersive experiences based on task-oriented connections, especially in the context of the thriving development of pre-trained foundation models (PFM) and the evolving vision of 6G native artificial intelligence (AI).
Unsupervised Massive MIMO Channel Estimation with Dual-Path Knowledge-Aware Auto-Encoders
In this paper, an unsupervised deep learning framework based on dual-path model-driven variational auto-encoders (VAE) is proposed for angle-of-arrivals (AoAs) and channel estimation in massive MIMO systems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
