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Found 10 papers, 2 papers with code
Dynamic Online Modulation Recognition using Incremental Learning
This issue renders DL-based modulation recognition models inapplicable in real-world scenarios because the dynamic nature of communication systems necessitate the effective adaptability to new modulation schemes.
Faster and Accurate Neural Networks with Semantic Inference
In short, SINF (i) identifies the semantic cluster the object belongs to using a small additional classifier and (ii) executes the subgraph extracted from the base DNN related to that semantic cluster for inference.
Attention-based Open RAN Slice Management using Deep Reinforcement Learning
As emerging networks such as Open Radio Access Networks (O-RAN) and 5G continue to grow, the demand for various services with different requirements is increasing.
A Meta-learning based Generalizable Indoor Localization Model using Channel State Information
Indoor localization has gained significant attention in recent years due to its various applications in smart homes, industrial automation, and healthcare, especially since more people rely on their wireless devices for location-based services.
A$^2$-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems
For this reason, we propose a novel A$^2$-UAV framework to optimize the number of correctly executed tasks at the edge.
UAV-Assisted Communication in Remote Disaster Areas using Imitation Learning
The damage to cellular towers during natural and man-made disasters can disturb the communication services for cellular users.
Real-time Framework for Trust Monitoring in aNetwork of Unmanned Aerial Vehicles
Unmanned aerial vehicles (UAVs) have been increasingly utilized in various civilian and military applications such as remote sensing, border patrolling, disaster monitoring, and communication coverage extension.
An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations
This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring.
A Solution for Dynamic Spectrum Management in Mission-Critical UAV Networks
In this paper, we study the problem of spectrum scarcity in a network of unmanned aerial vehicles (UAVs) during mission-critical applications such as disaster monitoring and public safety missions, where the pre-allocated spectrum is not sufficient to offer a high data transmission rate for real-time video-streaming.
A Unified Framework for Joint Mobility Prediction and Object Profiling of Drones in UAV Networks
In recent years, using a network of autonomous and cooperative unmanned aerial vehicles (UAVs) without command and communication from the ground station has become more imperative, in particular in search-and-rescue operations, disaster management, and other applications where human intervention is limited.
