Deep learning-based cellular random access framework
Random access (RA) or preamble collision is one of the crucial problems in massive internet-
of-things (IoT) at the network entry stage. Since a massive number of IoT nodes …
of-things (IoT) at the network entry stage. Since a massive number of IoT nodes …
Deep learning-based packet detection and carrier frequency offset estimation in IEEE 802.11 ah
V Ninkovic, A Valka, D Dumic, D Vukobratovic - IEEE Access, 2021 - ieeexplore.ieee.org
Wi-Fi systems based on the IEEE 802.11 standards are the most popular wireless interfaces
that use Listen Before Talk (LBT) method for channel access. The distinctive feature of a …
that use Listen Before Talk (LBT) method for channel access. The distinctive feature of a …
A general approach for traffic classification in wireless networks using deep learning
Traffic Classification (TC) systems allow inferring the application that is generating the traffic
being analyzed. State-of-the-art TC algorithms are based on Deep Learning (DL) and have …
being analyzed. State-of-the-art TC algorithms are based on Deep Learning (DL) and have …
Timing synchronization based on supervised learning of spectrogram for ofdm systems
This paper proposes a supervised convolutional neural network (CNN) based symbol timing
synchronization method using the spectrogram image for preamble-less orthogonal …
synchronization method using the spectrogram image for preamble-less orthogonal …
Toward the simulation of WiFi Fine Time measurements in NS3 network simulator
A Zubow, C Laskos, F Dressler - Computer Communications, 2023 - Elsevier
WiFi has become the most widely used indoor positioning technology. The Fine Time
Measurement (FTM) protocol introduced in the IEEE 802.11-2016 standard uses radio …
Measurement (FTM) protocol introduced in the IEEE 802.11-2016 standard uses radio …
Wi-Fi frame detection via spiking neural networks with memristive synapses
With increasing performance of deep learning, researchers have employed Deep Neural
Networks (DNNs) for wireless communications. In particular, mechanisms for detecting Wi-Fi …
Networks (DNNs) for wireless communications. In particular, mechanisms for detecting Wi-Fi …
Radio Frequency Fingerprint Identification Based on Transfer Learning
L Chen, C Zhao, Y Zheng… - 2021 IEEE/CIC …, 2021 - ieeexplore.ieee.org
Given the current radio frequency (RF) fingerprint identification methods based on deep
learning, there is a problem of poor recognition performance in the scene of RF fingerprint …
learning, there is a problem of poor recognition performance in the scene of RF fingerprint …
RIS-Assisted Joint Preamble Detection and Localization
P Nuti, KJ Kim, P Wang, T Koike-Akino… - 2023 IEEE 9th …, 2023 - ieeexplore.ieee.org
Reconfigurable intelligent surface (RIS) is envisioned to be a key enabling technology for
future wireless systems and is currently being developed and studied for various …
future wireless systems and is currently being developed and studied for various …
PRONTO: Preamble Overhead Reduction With Neural Networks for Coarse Synchronization
In IEEE 802.11 WiFi-based waveforms, the receiver performs coarse time and frequency
synchronization using the first field of the preamble known as the legacy short training field …
synchronization using the first field of the preamble known as the legacy short training field …
Deep Learning-based Channel Estimation in High-Speed Wireless Systems With Imperfect Frame Synchronization
This paper considers an application of deep learning for channel estimation with imperfect
frame synchronization in mobile communication systems. Without prior knowledge of the …
frame synchronization in mobile communication systems. Without prior knowledge of the …