21 citations · 25 across the 11 of their papers we have counts for
11 papers
LiDAR-based Dynamic Blockage Prediction: A Data-driven Approach for Learning Interactive Bayesian Models
Saleemullah Memon, Ali Krayani, Pamela Zontone +3
Vehicular sensing-based intelligence has made substantial progress in transportation systems, leading to higher levels of safety and sustainability for smart cities and autonomous…
Flying by Inference: Active Inference World Models for Adaptive UAV Swarms
Kaleem Arshid, Ali Krayani, Lucio Marcenaro +2
This paper presents an expert-guided active-inference-inspired framework for adaptive UAV swarm trajectory planning. The proposed method converts multi-UAV trajectory design from a…
Active Inference-Driven World Modeling for Adaptive UAV Swarm Trajectory Design
Kaleem Arshid, Ali Krayani, Lucio Marcenaro +2
This paper proposes an Active Inference-based framework for autonomous trajectory design in UAV swarms. The method integrates probabilistic reasoning and self-learning to enable di…
Bayesian Active Inference for Intelligent UAV Anti-Jamming and Adaptive Trajectory Planning
Ali Krayani, Seyedeh Fatemeh Sadati, Lucio Marcenaro +1
This paper proposes a hierarchical trajectory planning framework for UAVs operating under adversarial jamming conditions. Leveraging Bayesian Active Inference, the approach combine…
Self-Supervised Path Planning in UAV-aided Wireless Networks based on Active Inference
Ali Krayani, Khalid Khan, Lucio Marcenaro +2
This paper presents a novel self-supervised path-planning method for UAV-aided networks. First, we employed an optimizer to solve training examples offline and then used the result…
Interactive Bayesian Generative Models for Abnormality Detection in Vehicular Networks
Nobel J. William, Ali Krayani, Lucio Marcenaro +1
The following paper proposes a novel Vehicle-to-Everything (V2X) network abnormality detection scheme based on Bayesian generative models for enhanced network self-awareness functi…
Intelligent Resource Allocation for UAV-Based Cognitive NOMA Networks: An Active Inference Approach
Felix Obite, Ali Krayani, Atm S. Alam +3
Future wireless networks will need to improve adaptive resource allocation and decision-making to handle the increasing number of intelligent devices. Unmanned aerial vehicles (UAV…
Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks
Felix Obite, Ali Krayani, Atm S. Alam +3
Given the surge in wireless data traffic driven by the emerging Internet of Things (IoT), unmanned aerial vehicles (UAVs), cognitive radio (CR), and non-orthogonal multiple access…
Integrated Sensing and Communication for Joint GPS Spoofing and Jamming Detection in Vehicular V2X Networks
Ali Krayani, Gabriele Barabino, Lucio Marcenaro +1
Vehicle-to-everything (V2X) communication is expected to be a prominent component of the sixth generation (6G) to accomplish intelligent transportation systems (ITS). Autonomous ve…
Learning Self-Awareness Models for Physical Layer Security in Cognitive and AI-enabled Radios
Ali Krayani
Cognitive Radio (CR) is a paradigm shift in wireless communications to resolve the spectrum scarcity issue with the ability to self-organize, self-plan and self-regulate. On the ot…
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach
Ali Krayani, Atm S. Alam, Lucio Marcenaro +2
This work proposes a novel resource allocation strategy for anti-jamming in Cognitive Radio using Active Inference (), and a cognitive-UAV is employed as a case study…