A deep learning-based intelligent receiver for improving the reliability of the MIMO wireless communication system

B Wang, K Xu, S Zheng, H Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multiple-input–multiple-output (MIMO) technology is one of the most widely used
communication technologies. However, with the increasing number of antennas, the …

Bidirectional Deep Learning Decoder for Polar Codes in Flat Fading Channels

MA Aziz, MH Rahman, MAS Sejan, R Tabassum… - IEEE …, 2024 - ieeexplore.ieee.org
One of the main issues facing in the future wireless communications is ultra-reliable and low-
latency communication. Polar codes are well-suited for such applications, and recent …

Learning to denoise and decode: A novel residual neural network decoder for polar codes

H Zhu, Z Cao, Y Zhao, D Li - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
Polar codes are known as the first capacity-achievable codes with low encoding and
decoding complexity. The sequential decoding nature of traditional polar decoding …

Deep learning based decoding for polar codes in Markov Gaussian memory impulse noise channels

SM Tseng, WC Hsu, DF Tseng - Wireless Personal Communications, 2022 - Springer
In previous papers, decoding schemes which did not use machine learning considered
additive white Gaussian noise or memoryless impulse noise. The decoding methods …

AI-Based Beam Management in 3GPP: Optimizing Data Collection Time Window for Temporal Beam Prediction

Y Bai, J Zhang, C Sun, L Zhao, H Li… - IEEE Open Journal of …, 2023 - ieeexplore.ieee.org
Artificial Intelligence (AI) has gained significant attention and extensive research across
various fields in recent years. In the realm of wireless communication, researchers are …

Deep Learning Polar Convolutional Parallel Concatenated (DL-PCPC) Channel Decoding for 6G Communications

AK Ahmed, HS Al-Raweshidy - 2023 International Conference …, 2023 - ieeexplore.ieee.org
The new wireless generation 6G use of intelligent devices, sensors, and new applications
like virtual reality and autonomous driving requires higher demands on the network with …

Adversarial filters for secure modulation classification

A Berian, K Staab, G Ditzler, T Bose… - 2021 55th Asilomar …, 2021 - ieeexplore.ieee.org
Classification (MC) is the problem of classifying the modulation format of a wireless signal. In
the wireless communications pipeline, MC is the first operation performed on the received …

Mine intelligent receiver: MIMO-OFDM intelligent receiver for mine information recovery

A Wang, Z Feng, X Li, Y Pan - Energies, 2022 - mdpi.com
With the advancement of an intellectual and numerical society, the coal mining industry has
also begun to change to intelligence. As an important aspect of intelligent coal mine …

Learning to denoise and decode: A novel residual neural network decoder for polar codes

Z Cao, H Zhu, Y Zhao, D Li - 2020 IEEE 92nd Vehicular …, 2020 - ieeexplore.ieee.org
Polar codes have been adopted as the control channel coding scheme in the fifth generation
new radio (5G NR) standard due to its capacity-achievable property. Traditional polar …

Position-invariant adversarial attacks on neural modulation recognition

Z Yu, Y Xiong, K He, S Huang… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
Deep neural networks (DNNs) are widely used for neural modulation recognition (NMR) in
the electronic field and have been shown to be vulnerable to adversarial examples for NMR …