Y Wang, T Sun, S Li, X Yuan, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Adversarial attacks and defenses in machine learning and deep neural network (DNN) have been gaining significant attention due to the rapidly growing applications of deep learning in …
H Xie, Z Qin, GY Li, BH Juang - IEEE Transactions on Signal …, 2021 - ieeexplore.ieee.org
Recently, deep learned enabled end-to-end communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make joint …
J Xu, B Ai, W Chen, A Yang, P Sun… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Recent research on joint source channel coding (JSCC) for wireless communications has achieved great success owing to the employment of deep learning (DL). However, the …
S Han, T Xie, I Chih-Lin, L Chai, Z Liu… - IEEE …, 2020 - ieeexplore.ieee.org
As 3GPP has completed Release 16 specifications and worldwide 5G commercialization is speeding up, global interest in 6G is starting to grow. An interesting and important question …
F Zhang, Y Zhang, W Lu, Y Gao, Y Gong, J Cao - Electronics, 2022 - mdpi.com
As human society develops, the population is growing explosively and water and land resources are gradually being exhausted due to pollution. Smart agriculture is regarded as …
Landmark codes underpin reliable physical layer communication, eg, Reed-Muller, BCH, Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a …
There is significant enthusiasm for the employment of Deep Neural Networks (DNNs) for important tasks in major wireless communication systems: channel estimation and decoding …
Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards. However, a sharp characterization of the performance of …