[HTML][HTML] A survey on Zero touch network and Service Management (ZSM) for 5G and beyond networks
Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand
for new business-oriented services in the fifth-generation (5G) and beyond network, the …
for new business-oriented services in the fifth-generation (5G) and beyond network, the …
Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Overview of deep learning-based CSI feedback in massive MIMO systems
Many performance gains achieved by massive multiple-input and multiple-output depend on
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
Channel-aware adversarial attacks against deep learning-based wireless signal classifiers
This paper presents channel-aware adversarial attacks against deep learning-based
wireless signal classifiers. There is a transmitter that transmits signals with different …
wireless signal classifiers. There is a transmitter that transmits signals with different …
Deep learning-based CSI feedback for beamforming in single-and multi-cell massive MIMO systems
The potentials of massive multiple-input multiple-output (MIMO) are all based on the
available instantaneous channel state information (CSI) at the base station (BS). Therefore …
available instantaneous channel state information (CSI) at the base station (BS). Therefore …
Compressive sampled CSI feedback method based on deep learning for FDD massive MIMO systems
Accurate downlink channel state information (CSI) is required to be fed back to the base
station (BS) in frequency division duplexing (FDD) massive multiple-input multiple-output …
station (BS) in frequency division duplexing (FDD) massive multiple-input multiple-output …
[HTML][HTML] Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Lightweight convolutional neural networks for CSI feedback in massive MIMO
In frequency division duplex mode of massive multiple-input multiple-output systems, the
downlink channel state information (CSI) must be sent to the base station (BS) through a …
downlink channel state information (CSI) must be sent to the base station (BS) through a …
Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends
Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the
potential of challenging large-scale problems in conventional massive multiple-input …
potential of challenging large-scale problems in conventional massive multiple-input …
Artificial intelligence in open-radio access network
PH Masur, JH Reed, NK Tripathi - IEEE Aerospace and …, 2022 - ieeexplore.ieee.org
This article outlines the proposed open-radio access network (O-RAN) deployment for fifth-
generation (5G) wireless networks. O-RAN seeks to supplant hardware-specific radio …
generation (5G) wireless networks. O-RAN seeks to supplant hardware-specific radio …