18 citations · 20 across the 11 of their papers we have counts for
14 papers
When Simple Is Enough: Resource-Aware Heuristic versus DDQN for O-RAN Mobility Robustness
Ali Deylamy, Nima Afraz
Open Radio Access Network (O-RAN) enables mobility-management xApps, but a learned controller is not necessarily the most effective or efficient handover policy. This paper compare…
Experimental Classification of xApp Conflicts in O-RAN: Slicing vs. Per-UE Scheduling
Rashmi Sharan Sinha, Merim Dzaferagic, Marco Ruffini +1
Concurrent applications (xApps) in the Near-Real-Time RAN Intelligent Controller (Near-RT RIC) of the Open Radio Access Network (O-RAN) can issue control intents that are jointly i…
Online Change-Point Detection in Linear Regression with Autoregressive Errors via Streaming Variational Bayes
Yujin Jeong, Chaeeun Park, Sihyeon Pyeon +2
Large-scale streaming time-series regression requires methods that can detect structural changes while accounting for serially correlated errors and quantifying uncertainty about t…
AI-Driven Multi-Modal Adaptive Handover Control Optimization for O-RAN
Abdul Wadud, Fatemeh Golpayegani, Nima Afraz
Handover optimization in O-RAN faces growing challenges due to heterogeneous user mobility patterns and rapidly varying radio conditions. Existing ML-based handover schemes typical…
AI-Powered Conflict Management in Open RAN: Detection, Classification, and Mitigation
Abdul Wadud, Nima Afraz, Fatemeh Golpayegani
Open Radio Access Network (RAN) was designed with native Artificial Intelligence (AI) as a core pillar, enabling AI- driven xApps and rApps to dynamically optimize network performa…
RU Energy Modeling for O-RAN in ns3-oran
Abdul Wadud, Nima Afraz
This paper presents a detailed and flexible power consumption model for Radio Units (RUs) in O-RAN using the ns3-oran simulator. This is the first ns3-oran model supporting xApp co…
xApp-Level Conflict Mitigation in O-RAN, a Mobility Driven Energy Saving Case
Abdul Wadud, Fatemeh Golpayegani, Nima Afraz
This paper investigates the emerging challenges of conflict detection and mitigation in Open Radio Access Network (O-RAN). Conflicts between xApps can arise that affect network per…
subMFL: Compatiple subModel Generation for Federated Learning in Device Heterogenous Environment
Zeyneddin Oz, Ceylan Soygul Oz, Abdollah Malekjafarian +2
Federated Learning (FL) is commonly used in systems with distributed and heterogeneous devices with access to varying amounts of data and diverse computing and storage capacities.…
Data Sharing at the Edge of the Network: A Disturbance Resilient Multi-modal ITS
Igor Mikolasek, Saeedeh Ghanadbashi, Nima Afraz +1
Mobility-as-a-Service (MaaS) is a paradigm that encourages the shift from private cars to more sustainable alternative mobility services. MaaS provides services that enhances and e…
QACM: QoS-Aware xApp Conflict Mitigation in Open RAN
Abdul Wadud, Fatemeh Golpayegani, Nima Afraz
The advent of Open Radio Access Network (RAN) has revolutionized the field of RAN by introducing elements of native support of intelligence and openness into the next generation of…
An Adaptive System Architecture for Multimodal Intelligent Transportation Systems
Muhammad Farooq, Nima Afraz, Fatemeh Golpayegani
Multimodal intelligent transportation systems (M-ITS) encompass a range of transportation services that utilise various modes of transport and incorporate intelligent technologies…
On the Sum Secrecy Rate Maximisation for Wireless Vehicular Networks
Muhammad Farooq, Le-Nam Tran, Fatemeh Golpayegani +1
Wireless communications form the backbone of future vehicular networks, playing a critical role in applications ranging from traffic control to vehicular road safety. However, the…
Conflict Management in the Near-RT-RIC of Open RAN: A Game Theoretic Approach
Abdul Wadud, Fatemeh Golpayegani, Nima Afraz
Open Radio Access Network (RAN) was introduced recently to incorporate intelligence and openness into the upcoming generation of RAN. Open RAN offers standardized interfaces and th…
The Implications of Decentralization in Blockchained Federated Learning: Evaluating the Impact of Model Staleness and Inconsistencies
Francesc Wilhelmi, Nima Afraz, Elia Guerra +1
Blockchain promises to enhance distributed machine learning (ML) approaches such as federated learning (FL) by providing further decentralization, security, immutability, and trust…