Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …
position in providing Internet access thanks to their freedom of deployment and configuration …
Combined RF-based drone detection and classification
S Basak, S Rajendran, S Pollin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Despite several beneficial applications, unfortunately, drones are also being used for illicit
activities such as drug trafficking, firearm smuggling or to impose threats to security-sensitive …
activities such as drug trafficking, firearm smuggling or to impose threats to security-sensitive …
Finding waldo in the cbrs band: Signal detection and localization in the 3.5 ghz spectrum
Opening the Citizen Broadband Radio Service (CBRS) band in the US to secondary users
offers unprecedented opportunities to LTE and 5G networks, as long as incumbent radar …
offers unprecedented opportunities to LTE and 5G networks, as long as incumbent radar …
WRIST: Wideband, real-time, spectro-temporal RF identification system using deep learning
RF emissions' detection, classification, and spectro-temporal localization are essential not
only for understanding, managing, and protecting the radio frequency resources, but also for …
only for understanding, managing, and protecting the radio frequency resources, but also for …
A dynamic time warping based method to synchronize spectral and protocol domains for troubleshooting wireless communication
V Jain, V Fokow, J Wicht, U Wetzker - Ieee Access, 2023 - ieeexplore.ieee.org
An increase in popularity of wireless networks, mainly in industrial automation and
manufacturing, has escalated the need for reliable wireless networks. One subtle way of …
manufacturing, has escalated the need for reliable wireless networks. One subtle way of …
[HTML][HTML] Spectral decision analysis and evaluation in an experimental environment for cognitive wireless networks
DA Giral-Ramírez, CA Hernández-Suarez… - Results in …, 2021 - Elsevier
Dynamic spectrum allocation is the crucial aspect in Cognitive Radio Networks (CRN) to
improve spectral efficiency where the selection of the target frequency channel plays a …
improve spectral efficiency where the selection of the target frequency channel plays a …
[HTML][HTML] Self-supervised learning for clustering of wireless spectrum activity
In recent years, much work has been done on processing of wireless spectrum data
involving machine learning techniques in domain-related problems for cognitive radio …
involving machine learning techniques in domain-related problems for cognitive radio …
A Hybrid Deep Learning Spectrum Sensing Architecture for IoT Technologies Classification
In recent years, there has been a significant expansion of the Internet of Things concept,
because of its versatile and extensive range of applications across various industries such …
because of its versatile and extensive range of applications across various industries such …
Fast target tracking based on improved deep sort and YOLOv3 fusion algorithm
Y Wang, Z Liang, X Cheng - Data Science: 7th International Conference of …, 2021 - Springer
Aiming at fast moving targets, such as ships, high-speed vehicles and athletes, this paper
discusses a series of target detection algorithms based on neural network, YOLOv3 and …
discusses a series of target detection algorithms based on neural network, YOLOv3 and …
RiSi: Spectro-temporal RAN-agnostic Modulation Identification for OFDMA Signals
D Kurmantayev, D Kwun, H Kim… - 2024 IEEE 25th …, 2024 - ieeexplore.ieee.org
RAN-agnostic communications can identify intrinsic features of the unknown signal without
any prior knowledge, with which incompatible RANs in the same unlicensed band could …
any prior knowledge, with which incompatible RANs in the same unlicensed band could …