Complex-Valued Neural Network Based Federated Learning for Multi-User Indoor Positioning Performance Optimization
In this article, the use of channel state information (CSI) for indoor positioning is studied. In
the considered model, a server equipped with several antennas sends pilot signals to users …
the considered model, a server equipped with several antennas sends pilot signals to users …
Feature fusion federated learning for privacy-aware indoor localization
Abstract In recent years, Indoor Positioning Systems (IPS) have emerged as a critical
technology to enable a diverse range of Location-based Services (LBS) across different …
technology to enable a diverse range of Location-based Services (LBS) across different …
Differentially Private GANs for Generating Synthetic Indoor Location Data
The advent of location-based services has led to the widespread adoption of indoor
localization systems, which enable location tracking of individuals within enclosed spaces …
localization systems, which enable location tracking of individuals within enclosed spaces …
Federated Learning-Enabled Cooperative Localization in Multi-agent System
Cooperative localization plays a significant role in various applications, such as emergency
rescue and navigation path planning. The advent of swarm intelligence has opened doors to …
rescue and navigation path planning. The advent of swarm intelligence has opened doors to …
A Three-level Federated Learning Framework for CSI Fingerprint based Indoor Localization in Multiple Servers Environment
J Yan, Y Cui, W Wang - IEEE Communications Letters, 2024 - ieeexplore.ieee.org
This letter develops a federated learning (FL) framework for indoor localization using
channel state information (CSI) fingerprint, aiming to (a) design a FL framework for multiple …
channel state information (CSI) fingerprint, aiming to (a) design a FL framework for multiple …
Federated approach for privacy-preserving traffic prediction using graph convolutional network
S Lonare, R Bhramaramba - Journal of Shanghai Jiaotong University …, 2024 - Springer
Existing traffic flow prediction frameworks have already achieved enormous success due to
large traffic datasets and capability of deep learning models. However, data privacy and …
large traffic datasets and capability of deep learning models. However, data privacy and …
[PDF][PDF] Bayesian data fusion for distributed learning
P Wu - 2024 - researchgate.net
Bayesian data fusion for distributed learning by Peng Wu Doctor of Philosophy in Electrical
and Computer Engineering Northeastern University, April 2024 Prof. Pau Closas, Advisor …
and Computer Engineering Northeastern University, April 2024 Prof. Pau Closas, Advisor …
Optimizing federated learning approaches with hybrid Convolutional Neural Networks‐Bidirectional Encoder Representations from Transformers for precise …
R Lakshminarayanan, S Dhanasekaran… - International Journal of … - Wiley Online Library
Wireless sensor networks (WSNs) require precise node location in order to function
properly, and they are essential in many different applications. In this research, we propose …
properly, and they are essential in many different applications. In this research, we propose …