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Found 7 papers, 0 papers with code
Self-Supervised Path Planning in UAV-aided Wireless Networks based on Active Inference
This paper presents a novel self-supervised path-planning method for UAV-aided networks.
Interactive Bayesian Generative Models for Abnormality Detection in Vehicular Networks
The following paper proposes a novel Vehicle-to-Everything (V2X) network abnormality detection scheme based on Bayesian generative models for enhanced network self-awareness functionality at the Base station (BS).
Intelligent Resource Allocation for UAV-Based Cognitive NOMA Networks: An Active Inference Approach
This paper investigates the design of joint subchannel and power allocation in an uplink UAV-based cognitive NOMA network.
Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks
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 (NOMA) have been recognized as promising techniques to overcome massive connectivity issues.
Integrated Sensing and Communication for Joint GPS Spoofing and Jamming Detection in Vehicular V2X Networks
This paper proposes a method to jointly detect GPS spoofing and jamming attacks in a V2X network.
Learning Self-Awareness Models for Physical Layer Security in Cognitive and AI-enabled Radios
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.
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach
This work proposes a novel resource allocation strategy for anti-jamming in Cognitive Radio using Active Inference ($\textit{AIn}$), and a cognitive-UAV is employed as a case study.
