Wireless Application

Wireless application research currently focuses on improving efficiency and reliability through advanced signal processing and machine learning techniques. Key areas include developing robust deep learning models for accurate radio propagation prediction, optimizing federated learning algorithms for resource-constrained wireless devices, and enhancing active noise control systems via wireless signal transmission. These advancements aim to improve the performance and scalability of wireless networks, impacting applications ranging from indoor localization and network security to the deployment of next-generation wireless technologies.

Papers

August 22, 2024

Empowering Wireless Network Applications with Deep Learning-based Radio Propagation Models
Stefanos Bakirtzis, Cagkan Yapar, Marco Fiore, Jie Zhang, Ian Wassell
Propagation Environment Next Generation Wireless Network Wireless Application Dual Propagation

August 12, 2024

Online-Score-Aided Federated Learning: Taming the Resource Constraints in Wireless Networks
Md Ferdous Pervej, Minseok Choi, Andreas F. Molisch
Time Varying Wireless Network Resource Constraint FL Algorithm Wireless Application

May 21, 2024

A Survey of Integrating Wireless Technology into Active Noise Control
Xiaoyi Shen, Dongyuan Shi, Zhengding Luo, Junwei Ji, Woon-Seng Gan
Timely Survey Noise Reduction Active Noise Control Wireless Application Noise Source

May 17, 2024

Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection
Han Zhang, Akram Bin Sediq, Ali Afana, Melike Erol-Kantarci
Large Language Model Context Learning Pre Trained Intrusion Detection Generative Pre Trained Transformer Network Intrusion Detection Different Context Wireless Application

May 9, 2024

Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint
Jun Li, Weiwei Zhang, Kang Wei, Guangji Chen, Long Shi, Wen Chen
Graph Neural Network Gene Level GNN Lyapunov Function Wireless Network Wireless Application

April 15, 2024

An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
Yujia Mu, Xizixiang Wei, Cong Shen
Federated Learning Digital Modulation Air Computation Wireless Application Deep Learned Constellation Descriptor

March 13, 2023

Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues
Mohamed Akrout, Amal Feriani, Faouzi Bellili, Amine Mezghani, Ekram Hossain
Machine Learning Model Domain Generalization Supervised Learning State of the Art Concept Identification Data Driven Machine Learning Wireless Application

January 29, 2023

ADL-ID: Adversarial Disentanglement Learning for Wireless Device Fingerprinting Temporal Domain Adaptation
Abdurrahman Elmaghbub, Bechir Hamdaoui, Weng-Keen Wong
Disentanglement Learning Wi Fi Radio Frequency Fingerprinting FL Algorithm Wireless Application FL Framework

December 23, 2021

Hierarchical Multi-Building And Multi-Floor Indoor Localization Based On Recurrent Neural Networks
Abdalla Elmokhtar Ahmed Elesawi, Kyeong Soo Kim
Recurrent Neural Network Indoor Localization Wi Fi Wireless Application

Wireless Application

Papers

Empowering Wireless Network Applications with Deep Learning-based Radio Propagation Models

Online-Score-Aided Federated Learning: Taming the Resource Constraints in Wireless Networks

A Survey of Integrating Wireless Technology into Active Noise Control

Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint

An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning

Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues

ADL-ID: Adversarial Disentanglement Learning for Wireless Device Fingerprinting Temporal Domain Adaptation

Hierarchical Multi-Building And Multi-Floor Indoor Localization Based On Recurrent Neural Networks