291 citations · 340 across the 4 of their papers we have counts for
8 papers
A Low Complexity Learning-based Channel Estimation for OFDM Systems with Online Training
Kai Mei, Jun Liu, Xiaoying Zhang +3
In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of the es…
Deep Contextual Bandits for Fast Neighbor-Aided Initial Access in mmWave Cell-Free Networks
Insaf Ismath, Samad Ali, Nandana Rajatheva +1
Access points (APs) in millimeter-wave (mmWave) and sub-THz-based user-centric (UC) networks will have sleep mode functionality. As a result of this, it becomes challenging to solv…
Scoring the Terabit/s Goal:Broadband Connectivity in 6G
Nandana Rajatheva, Italo Atzeni, Simon Bicais +26
This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up…
White Paper on Broadband Connectivity in 6G
Nandana Rajatheva, Italo Atzeni, Emil Bjornson +22
This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity wit…
An Alternating Algorithm for Uplink Max-Min SINR in Cell-Free Massive MIMO with Local-MMSE Receiver
W. A. Chamalee Wickrama Arachchi, K. B. Shashika Manosha, N. Rajatheva +1
The problem of max-min signal-to-interference plus noise ratio (SINR) for uplink transmission of cell-free massive multiple-input multiple-output (MIMO) system is considered. We as…
Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems
Samad Ali, Hossein Asgharimoghaddam, Nandana Rajatheva +2
In this paper, a novel approach based on the concept of opportunistic spatial orthogonalization (OSO) is proposed for interference management between machine type communications (M…