A novel joint time-frequency spectrum resources sustainable risk prediction algorithm based on TFBRL network for the electromagnetic environment

S Li, Y Sun, Y Han, O Alfarraj, A Tolba, PK Sharma - Sustainability, 2023 - mdpi.com
To protect the electromagnetic environment and understand its current state in a timely
manner, monitoring the electromagnetic environment has great practical significance, while …

Broadband Long-Term Spectrum Prediction Based on Trend Based SAX

H Zhang, L Sun, Y Lin - … on Mobile Computing, Applications, and Services, 2022 - Springer
With the development of communication technology and the growth of equipment, spectrum
prediction technology has received more and more attention because of its wide application …

Spectrum occupancy prediction for internet of things via long short-term memory

H Li, X Ding, Y Yang, X Huang… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
With the development of Internet of things (IoT), the demand on spectrum is increasing
rapidly. Moreover, due to lack of power and the feature of short burst, the signals of IoT may …

Research on spectrum prediction technology based on B-LTF

X Wang, Q Chen, X Yu - Electronics, 2023 - mdpi.com
With the rapid development of global communication technology, the problem of scarce
spectrum resources has become increasingly prominent. In order to alleviate the problem of …

A spectrum prediction-based frequency band pre-selection over deteriorating HF electromagnetic environment

X Chen, J Yang - China Communications, 2018 - ieeexplore.ieee.org
As the earliest invented and utilized communication approach, shortwave, known as high
frequency (HF) communication now experience the deterioration of HF electromagnetic …

Spectrum situation awareness based on time-series depth networks for LTE-R communication system

X Cai, C Wu, J Sheng, Y Wang… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
The Long Term Evolution for Railway (LTE-R) communication system is providing a reliable
data link for High-Speed Railway (HSR) communication. However, when the train passes …

MTF2N: Multi-Channel Temporal-Frequency Fusion Network for Spectrum Prediction

S Li, Y Sun, H Zhang, M Wang… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
Radio spectrum prediction is of great significance for dynamic spectrum management and
alleviating spectrum congestion. Based on the real spectrum dataset, this paper constructs a …

Electromagnetic environment portrait based on big data mining

L Guo, M Wang, Y Lin - Wireless Communications and Mobile …, 2021 - Wiley Online Library
With the development of IoT in smart cities, the electromagnetic environment (EME) in cities
is becoming more and more complex. A full understanding of the characteristics of past …

Online spectrum prediction with adaptive threshold quantization

H Li, X Ding, Y Yang, Z Xie, G Zhang - IEEE Access, 2019 - ieeexplore.ieee.org
In this paper, we explore the spectrum inference to achieve the spectrum occupancy in
advance through analyzing the historical spectrum. We have conceived an offline-online …

Deep learning for spectrum prediction from spatial–temporal–spectral data

X Li, Z Liu, G Chen, Y Xu, T Song - IEEE Communications …, 2020 - ieeexplore.ieee.org
Spectrum prediction is challenging owing to its complex inherent dependency and
heterogeneity among the spectrum data. In this letter, we propose a novel end-to-end deep …