14 papers
Dual-Mode Wireless Devices for Adaptive Pull and Push-Based Communication
Sara Cavallero, Fabio Saggese, Junya Shiraishi +4
This paper introduces a dual-mode communication framework for wireless devices that integrates query-driven (pull) and event-driven (push) transmissions within a unified time-frame…
Medium Access for Push-Pull Data Transmission in 6G Wireless Systems
Shashi Raj Pandey, Fabio Saggese, Junya Shiraishi +2
Medium access in 5G systems was tailored to accommodate diverse traffic classes through network resource slicing. 6G wireless systems are expected to be significantly reliant on Ar…
Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts
Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3
In this work, we present OCLADS, a novel communication framework with continual learning (CL) for Internet of Things (IoT) anomaly detection (AD) when operating in non-stationary e…
Link-Aware Energy-Frugal Continual Learning for Fault Detection in IoT Networks
Henrik C. M. Frederiksen, Junya Shiraishi, Cedomir Stefanovic +2
The use of lightweight machine learning (ML) models in internet of things (IoT) networks enables resource constrained IoT devices to perform on-device inference for several critica…
Wireless Memory Approximation for Energy-efficient Task-specific IoT Data Retrieval
Junya Shiraishi, Shashi Raj Pandey, Israel Leyva-Mayorga +1
The use of Dynamic Random Access Memory (DRAM) for storing Machine Learning (ML) models plays a critical role in accelerating ML inference tasks in the next generation of communica…
Online Reliable Anomaly Detection via Neuromorphic Sensing and Communications
Junya Shiraishi, Jiechen Chen, Osvaldo Simeone +1
This paper proposes a low-power online anomaly detection framework based on neuromorphic wireless sensor networks, encompassing possible use cases such as brain-machine interfaces…