DeepWiPHY: Deep learning-based receiver design and dataset for IEEE 802.11 ax systems
In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the
channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) …
channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) …
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 …
Deep learning based channel estimation schemes for IEEE 802.11 p standard
IEEE 802.11 p standard is specially developed to define vehicular communications
requirements and support cooperative intelligent transport systems. In such environment …
requirements and support cooperative intelligent transport systems. In such environment …
DeepMux: Deep-learning-based channel sounding and resource allocation for IEEE 802.11 ax
PK Sangdeh, H Zeng - IEEE Journal on Selected Areas in …, 2021 - ieeexplore.ieee.org
MU-MIMO and OFDMA are two key techniques in IEEE 802.11 ax standard. Although these
two techniques have been intensively studied in cellular networks, their joint optimization in …
two techniques have been intensively studied in cellular networks, their joint optimization in …
A deep learning based channel estimation scheme for IEEE 802.11 p systems
S Han, Y Oh, C Song - ICC 2019-2019 IEEE International …, 2019 - ieeexplore.ieee.org
In this paper, we propose a novel deep learning based channel estimation scheme for IEEE
802.11 p vehicle-to-everything (V2X) communication systems. A major challenge in the V2X …
802.11 p vehicle-to-everything (V2X) communication systems. A major challenge in the V2X …
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 …
Enhancing the ns-3 ieee 802.11 ad model fidelity: Beam codebooks, multi-antenna beamforming training, and quasi-deterministic mmwave channel
Next generation wireless local area networks are envisioned to serve a high number of
devices with heterogeneous capabilities and service requirements. Millimeter-wave …
devices with heterogeneous capabilities and service requirements. Millimeter-wave …
Temporal averaging LSTM-based channel estimation scheme for IEEE 802.11 p standard
In vehicular communications, reliable channel estimation is critical for the system
performance due to the doubly-dispersive nature of vehicular channels. IEEE 802.11 p …
performance due to the doubly-dispersive nature of vehicular channels. IEEE 802.11 p …
IEEE 802.11 ax: Highly efficient WLANs for intelligent information infrastructure
DJ Deng, YP Lin, X Yang, J Zhu, YB Li… - IEEE …, 2017 - ieeexplore.ieee.org
Recently, IEEE 802.11 ax, introducing the fundamental improvement of WLANs, was
approved as the next generation WLAN technology. Satisfying tremendous user demands …
approved as the next generation WLAN technology. Satisfying tremendous user demands …
Deep learning-based channel prediction in realistic vehicular communications
Access to reliable estimates of the wireless channel, such as the channel state information
(CSI) and the received signal strength would open opportunities for timely adaptation of …
(CSI) and the received signal strength would open opportunities for timely adaptation of …