6 citations · 6 across the 4 of their papers we have counts for
8 papers
Supervised Learning based Sparse Channel Estimation for RIS aided Communications
Dilin Dampahalage, K. B. Shashika Manosha, Nandana Rajatheva +1
An reconfigurable intelligent surface (RIS) can be used to establish line-of-sight (LoS) communication when the direct path is compromised, which is a common occurrence in a millim…
Untrained DNN for Channel Estimation of RIS-Assisted Multi-User OFDM System with Hardware Impairments
Nipuni Ginige, K. B. Shashika Manosha, Nandana Rajatheva +1
Reconfigurable intelligent surface (RIS) is an emerging technology for improving performance in fifth-generation (5G) and beyond networks. Practically channel estimation of RIS-ass…
Deep Learning-based Power Control for Cell-Free Massive MIMO Networks
Nuwanthika Rajapaksha, K. B. Shashika Manosha, Nandana Rajatheva +1
A deep learning (DL)-based power control algorithm that solves the max-min user fairness problem in a cell-free massive multiple-input multiple-output (MIMO) system is proposed. Ma…
Intelligent Reflecting Surface Aided Vehicular Communications
Dilin Dampahalage, K. B. Shashika Manosha, Nandana Rajatheva +1
We investigate the use of an intelligent reflecting surface (IRS) in a millimeter-wave (mmWave) vehicular communication network. An intelligent reflecting surface consists of passi…
Deep Contextual Bandits for Fast Initial Access in mmWave Based User-Centric Ultra-Dense Networks
Insaf Ismath, K. B. Shashika Manosha, Samad Ali +2
Millimeter wave (mmWave) based multiple-input multiple-output (MIMO) capable user-centric (UC) ultra-dense (UD) networks are suggested to facilitate high throughput requirements of…
An Initial Access Optimization Algorithm for millimeter Wave 5G NR Networks
A. Indika Perera, K. B. Shashika Manosha, Nandana Rajatheva +1
The millimeter wave (mmWave) communication uses directional antennas. Hence, achieving fine alignment of transmit and receive beams at the initial access phase is quite challenging…