Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts
The fifth generation (5G) wireless communication networks are being deployed worldwide
from 2020 and more capabilities are in the process of being standardized, such as mass …
from 2020 and more capabilities are in the process of being standardized, such as mass …
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 …
Deep reinforcement learning for joint channel selection and power control in D2D networks
Device-to-device (D2D) technology, which allows direct communications between proximal
devices, is widely acknowledged as a promising candidate to alleviate the mobile traffic …
devices, is widely acknowledged as a promising candidate to alleviate the mobile traffic …
SR2CNN: Zero-shot learning for signal recognition
Signal recognition is one of the significant and challenging tasks in the signal processing
and communications field. It is often a common situation that there's no training data …
and communications field. It is often a common situation that there's no training data …
Multi-agent reinforcement learning-based distributed channel access for next generation wireless networks
Z Guo, Z Chen, P Liu, J Luo, X Yang… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
In the next generation wireless networks, more applications will emerge, covering virtual
reality movies, augmented reality, holographic three-dimensional telepresence, haptic …
reality movies, augmented reality, holographic three-dimensional telepresence, haptic …
Realizing intelligent spectrum management for integrated satellite and terrestrial networks
Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-
increasing demands for higher throughput, lower latency, and wider coverage. However …
increasing demands for higher throughput, lower latency, and wider coverage. However …
Lightweight automatic modulation classification based on decentralized learning
Due to the implementation and performance limitations of centralized learning automatic
modulation classification (CentAMC) method, this paper proposes a decentralized learning …
modulation classification (CentAMC) method, this paper proposes a decentralized learning …
Optimal status update for caching enabled IoT networks: A dueling deep R-network approach
In the Internet of Things (IoT) networks, caching is a promising technique to alleviate energy
consumption of sensors by responding to users' data requests with the data packets cached …
consumption of sensors by responding to users' data requests with the data packets cached …
Signal detection and classification in shared spectrum: A deep learning approach
Accurate identification of the signal type in shared-spectrum networks is critical for efficient
resource allocation and fair coexistence. It can be used for scheduling transmission …
resource allocation and fair coexistence. It can be used for scheduling transmission …
智能无线通信技术研究概况
梁应敞， 谭俊杰 - 通信学报, 2020 - infocomm-journal.com
近年来, 人工智能技术已被应用于无线通信领域, 以解决传统无线通信技术面对信息爆炸和万物
互联等新发展趋势所遇到的瓶颈问题. 首先介绍深度学习, 深度强化学习和联邦学习三类具有 …
互联等新发展趋势所遇到的瓶颈问题. 首先介绍深度学习, 深度强化学习和联邦学习三类具有 …