326 citations · 618 across the 55 of their papers we have counts for
61 papers
Energy-Latency Trade-offs in O-RAN with Distributed Baseband Processing and AI Inference
Urooj Tariq, Rishu Raj, Shashi Raj Pandey +3
The Open Radio Access Network (O-RAN) architecture introduces flexible functional splits and open interfaces that enable distributed and centralized deployment of baseband processi…
Quantum Compression for Distributed Entanglement
Jan Østergaard, Shashi Raj Pandey, Christophe Biscio +2
We study compression strategies for multipartite entanglement distribution under uncertainty in the partitioning of the quantum state. When the partition is not known at the time o…
Multi-Agent Conformal Prediction with Personalized Statistical Validity
Martin V. Vejling, Christophe A. N. Biscio, Adrien Mazoyer +2
Uncertainty quantification is essential in high-stakes machine learning tasks. However, one of the principled solutions, conformal prediction, faces challenges under limited local…
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…
Goal-Oriented Access Optimization for ISAC-Enabled Digital Twins
Fabio Saggese, Federico Chiariotti, Shashi Raj Pandey +3
Digital twins (DTs) of physical systems enable real-time remote tracking, control, and learning, but require to be updated with environmental sensory data to maintain alignment wit…
Type-Based Unsourced Federated Learning With Client Self-Selection
Kaan Okumus, Khac-Hoang Ngo, Unnikrishnan Kunnath Ganesan +3
We address the client-selection problem in federated learning over wireless networks under data heterogeneity. Existing client-selection methods often rely on server-side knowledge…
Reliable Explanations or Random Noise? A Reliability Metric for XAI
Poushali Sengupta, Sabita Maharjan, Frank Eliassen +2
In recent years, explaining decisions made by complex machine learning models has become essential in high-stakes domains such as energy systems, healthcare, finance, and autonomou…
Context Dependence and Reliability in Autoregressive Language Models
Poushali Sengupta, Shashi Raj Pandey, Sabita Maharjan +1
Large language models (LLMs) generate outputs by utilizing extensive context, which often includes redundant information from prompts, retrieved passages, and interaction history.…
Explainability of Complex AI Models with Correlation Impact Ratio
Poushali Sengupta, Rabindra Khadka, Sabita Maharjan +5
Complex AI systems make better predictions but often lack transparency, limiting trustworthiness, interpretability, and safe deployment. Common post hoc AI explainers, such as LIME…
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…
ISAC-Powered Distributed Matching and Resource Allocation in Multi-band NTN
Israel Leyva-Mayorga, Shashi Raj Pandey, Petar Popovski +3
Scalability is a major challenge in non-geostationary orbit (NGSO) satellite networks due to the massive number of ground users sharing the limited sub-6 GHz spectrum. Using K- and…
Energy-Efficient Federated Learning with Relay-Assisted Aggregation in IIoT Networks
Hamid Reza Hashempour, Mostafa Nozari, Gilberto Berardinelli +4
This paper presents an energy-efficient transmission framework for federated learning (FL) in industrial Internet of Things (IIoT) environments with strict latency and energy const…
Real-Time Inference for Distributed Multimodal Systems under Communication Delay Uncertainty
Victor Croisfelt, João Henrique Inacio de Souza, Shashi Raj Pandey +2
Connected cyber-physical systems perform inference based on real-time inputs from multiple data streams. Uncertain communication delays across data streams challenge the temporal f…
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…
Microsecond Federated SVD on Grassmann Manifold for Real-time IoT Intrusion Detection
Tung-Anh Nguyen, Van-Phuc Bui, Shashi Raj Pandey +3
This paper introduces FedSVD, a novel unsupervised federated learning framework for real-time anomaly detection in IoT networks. By leveraging Singular Value Decomposition (SVD) an…
1Q: First-Generation Wireless Systems Integrating Classical and Quantum Communication
Petar Popovski, Čedomir Stefanović, Beatriz Soret +8
We introduce the concept of 1Q, the first wireless generation of integrated classical and quantum communication. 1Q features quantum base stations (QBSs) that support entanglement…
Conformal Data Contamination Tests for In-distribution Data Acquisition
Martin V. Vejling, Shashi Raj Pandey, Christophe A. N. Biscio +1
The amount of quality data in many machine learning tasks is limited to what is available locally to data owners. The set of quality data can be expanded through trading or sharing…
Extreme Value Theory-based Distributed Interference Prediction for 6G Industrial Sub-networks
Pramesh Gautam, Sushmita Sapkota, Carsten Bockelmann +2
Interference prediction that accounts for extreme and rare events remains a key challenge for ultra-densely deployed sub-networks (SNs) requiring hyper-reliable low-latency communi…
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…
Scalable Data Transmission Framework for Earth Observation Satellites with Channel Adaptation
Van-Phuc Bui, Shashi Raj Pandey, Israel Leyva-Mayorga +1
The immense volume of data generated by Earth observation (EO) satellites presents significant challenges in transmitting it to Earth over rate-limited satellite-to-ground communic…
Experimental Study of Low-Latency Video Streaming in an ORAN Setup with Generative AI
Andreas Casparsen, Van-Phuc Bui, Shashi Raj Pandey +2
Current Adaptive Bit Rate (ABR) methods react to network congestion after it occurs, causing application layer buffering and latency spikes in live video streaming. We introduce a…
Time-constrained Federated Learning (FL) in Push-Pull IoT Wireless Access
Van Phuc Bui, Junya Shiraishi, Petar Popovski +1
Training a high-quality Federated Learning (FL) model at the network edge is challenged by limited transmission resources. Although various device scheduling strategies have been p…
Digital Twin for Autonomous Guided Vehicles based on Integrated Sensing and Communications
Van-Phuc Bui, Pedro Maia de Sant Ana, Soheil Gherekhloo +2
This paper presents a Digital Twin (DT) framework for the remote control of an Autonomous Guided Vehicle (AGV) within a Network Control System (NCS). The AGV is monitored and contr…