Ming Ding

TL;DR: In this paper, the authors provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks, including the types of consumer UAV currently available off-the-shelf, the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial BSs, challenges and opportunities for assisting cellular communications with UAV-based flying relays and BSs.

TL;DR: Wang et al. as mentioned in this paper proposed a novel framework based on the concept of differential privacy, in which artificial noise is added to parameters at the clients' side before aggregating, namely, noising before model aggregation FL (NbAFL).

TL;DR: In this paper, the potential gains and limitations of network densification and spectral efficiency enhancement techniques in ultra-dense small cell deployments are analyzed. And the top ten challenges to be addressed to bring ultra dense small-cell deployments to reality are discussed.

TL;DR: A novel framework based on the concept of differential privacy, in which artificial noise is added to parameters at the clients’ side before aggregating, namely, noising before model aggregation FL (NbAFL), is proposed and an optimal convergence bound is found that achieves the best convergence performance at a fixed privacy level.

TL;DR: In this paper, a comprehensive survey of the emerging applications of federated learning in IoT networks is provided, which explores and analyzes the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing and IoT privacy and security.