When fully implemented, sixth generation (6G) wireless systems will constitute intelligent
wireless networks that enable not only ubiquitous communication but also high-accuracy …

With the expansion of intelligent services and applications powered by Artificial Intelligence
(AI), the Internet of Things (IoT) permeates many aspects of our everyday lives. In order to …

This article proposes FedPos, a federated transfer learning framework together with a novel
position estimation method for Wi-Fi indoor positioning. Compared with traditional machine …

Crowdsourced localization plays a significant role for the applications in Internet of Things.
Even though existing studies have proposed privacy-preserving localization algorithms to …

The widespread deployment of machine learning techniques in ubiquitous computing
environments has sparked interests in exploiting the vast amount of data stored on mobile …

Crowdsourcing dramatically benefits WiFi fingerprinting localization in reducing the costs of
collecting received signal strength (RSS) data during offline site survey and has gained …

Clustered federated Multitask learning is introduced as an efficient technique when data is
unbalanced and distributed amongst clients in a non-independent and identically distributed …

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) …

Crowdsourcing Federated learning (CFL) is a new crowdsourcing development paradigm
for the Deep Neural Network (DNN) models, also called “software 2.0”. In practice, the …

Multi-domain localization has emerged as an important learning paradigm for wireless
fingerprinting localization, which leverages data from multiple related domains, known as …