S Zhou, GY Li - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
Federated learning has shown its advances recently but is still facing many challenges, such as how algorithms save communication resources and reduce computational costs, and …
Z Chen, H Cui, E Wu, X Yu - Electronics, 2023 - mdpi.com
The proliferation of the Internet of Things (IoT) and widespread use of devices with sensing, computing, and communication capabilities have motivated intelligent applications …
In this paper, we develop a dynamic detection network (DDNet) based detector for multiple- input multiple-output (MIMO) systems. By constructing an improved DetNet (IDetNet) …
MB Driss, E Sabir, H Elbiaze, W Saad - arXiv preprint arXiv:2312.04688, 2023 - arxiv.org
Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of wireless systems, such as sixth-generation (6G) mobile network. However, massive data …
The emergence of new services and applications in emerging wireless networks (eg, beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Conventional frequentist federated learning (FL) schemes are known to yield overconfident decisions. Bayesian FL addresses this issue by allowing agents to process and exchange …
Z Ji, Z Qin - ICC 2022-IEEE International Conference on …, 2022 - ieeexplore.ieee.org
In cellular networks, resource allocation is performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhead. This …
R Xie, C Li, X Zhou, Z Dong - ICASSP 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Real-time License Plate Recognition plays a significant role in traffic congestion control and road safety monitoring. Practically, a network camera may capture multiple license plates in …
Federated learning (FL) as a new decentralized learning/computing technique has potential advantages (eg, accelerating computation task processing and protecting user privacy) for …