On the Primal Feasibility in Dual Decomposition Methods Under Additive and Bounded Errors
With the unprecedented growth of signal processing and machine learning application domains, there has been a tremendous expansion of interest in distributed […]
Optimized Data Sampling and Energy Consumption in IIoT
Real-time environment monitoring is a key application in Industrial Internet of Things where sensors proactively collect and transmit environmental data to the […]
Time-Triggered Federated Learning Over Wireless Networks
The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner. However traditional […]
Deep data plane programming and AI for zero-trust self-driven networking in beyond 5G
Along with the high demand for network connectivity from both end-users and service providers networks have become highly complex; and so has […]
Federated Learning with Correlated Data
While information delivery in industrial Internet of things demands reliability and latency guarantees, the freshness of the controller’s available information, measured by […]
Federated Learning-Based Content Popularity Prediction in Fog Radio Access Networks
In this paper the content popularity prediction problem in fog radio access networks (F-RANs) is investigated. In order to obtain accurate prediction […]
Distributed Learning in Wireless Networks
The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected […]
Joint Client Scheduling and Resource Allocation Under Channel Uncertainty in Federated Learning
The performance of federated learning (FL) over wireless networks depend on the reliability of the client-server connectivity and clients’ local computation capabilities. […]
Intelligent Radio Signal Processing
Intelligent signal processing for wireless communications is a vital task in modern wireless systems, but it faces new challenges because of network […]
Bayesian Inference Federated Learning for Heart Rate Prediction
The advances of sensing and computing technologies pave the way to develop novel applications and services for wearable devices. For example, wearable […]