MM Alam, T Ahmed, M Hossain, MH Emo… - Future Generation …, 2023 - Elsevier
Abstract Transport Mode Detection (TMD) has become a crucial part of Intelligent Transportation Systems (ITS) thanks to the recent advancements in Artificial Intelligence and …
Machine learning-based semantic communication is a promising enabler for future- generation wireless network systems such as 6G networks. In practice, effective semantic …
In this paper, a federated learning (FL) based system is investigated with non-independent and identically distributed (non-IID) dataset, where multiple devices participate in the global …
The cloud-based solutions are becoming inefficient due to considerably large time delays, high power consumption, and security and privacy concerns caused by billions of connected …
In federated learning (FL), model weights must be updated at local users and the base station (BS). These weights are subjected to uplink (UL) and downlink (DL) transmission …
S Zhou, GY Li - arXiv preprint arXiv:2110.15318, 2021 - arxiv.org
Federated learning has shown its advances over the last few years but is facing many challenges, such as how algorithms save communication resources, how they reduce …
R Zhong, X Liu, Y Liu, Y Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A novel framework of reconfigurable intelligent surfaces (RISs)-enhanced indoor wireless networks is proposed, where an RIS mounted on the robot is invoked to enable mobility of …
Federated learning (FL) has found many successes in wireless communications; however, the implementation of FL has been hindered by the energy limitation of mobile devices …
Model-free techniques, such as machine learning (ML), have recently attracted much interest toward the physical layer design (eg, symbol detection, channel estimation, and …