Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges

F Tang, B Mao, N Kato, G Gui - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

A Proposed Quantum Classification Algorithm for Symbol Detection with Noisy Observation

S Koya, MR Laskar, AK Dutta - 2023 IEEE 97th Vehicular …, 2023 - ieeexplore.ieee.org
Quantum machine learning (QML) and quantum communication (QC) are emerging areas of
research for complexity-efficient data processing, information retrieval, system, and …

Experimental Validation of Zero Padding in SEFDM Systems Using Over-the-Air Transmission

W Ozan, R Grammenos… - 2022 13th International …, 2022 - ieeexplore.ieee.org
Non-orthogonal spectrally efficient frequency division multiplexing (SEFDM) saves
bandwidth by compressing the frequency spacing between the subcarriers. This is at the …

Using zero padding for robust channel Estimation in SEFDM systems

W Ozan, R Grammenos… - 2020 12th International …, 2020 - ieeexplore.ieee.org
In spectrally efficient frequency division multiplexing (SEFDM) systems, the subcarrier
spacing is compressed below the orthogonality limit, to enhance the bandwidth utilisation …

Alignment Signal Aided CP-Free SEFDM

B Sun, W Ozan, T Levanen, B Tan… - 2020 IEEE 31st …, 2020 - ieeexplore.ieee.org
This paper proposes a cyclic prefix (CP) free spectral efficiency frequency division
multiplexing (SEFDM) wireless signal transmission and reception method based on …