Binarized aggregated network with quantization: Flexible deep learning deployment for CSI feedback in massive MIMO systems
Massive multiple-input multiple-output (MIMO) is one of the key techniques to achieve better
spectrum and energy efficiency in 5G system. The channel state information (CSI) needs to …
spectrum and energy efficiency in 5G system. The channel state information (CSI) needs to …
Phyfinatt: An undetectable attack framework against phy layer fingerprint-based wifi authentication
WiFi connection has been suffering from MAC forgery attacks due to the loose authentication
mechanism between access points (APs) and clients. To address this problem, the physical …
mechanism between access points (APs) and clients. To address this problem, the physical …
CAnet: Uplink-aided downlink channel acquisition in FDD massive MIMO using deep learning
In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
[HTML][HTML] Security concerns on machine learning solutions for 6G networks in mmWave beam prediction
Abstract 6G–sixth generation–is the latest cellular technology currently under development
for wireless communication systems. In recent years, machine learning (ML) algorithms have …
for wireless communication systems. In recent years, machine learning (ML) algorithms have …
AI enabled wireless communications with real channel measurements: Channel feedback
Artificial intelligence (AI) has shown great potential in wireless communications. AI-
empowered communication algorithms have beaten many traditional algorithms through …
empowered communication algorithms have beaten many traditional algorithms through …
Defending adversarial attacks on deep learning-based power allocation in massive MIMO using denoising autoencoders
Recent work has advocated for the use of deep learning to perform power allocation in the
downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are …
downlink of massive MIMO (maMIMO) networks. Yet, such deep learning models are …
Privacy and security in distributed learning: A review of challenges, solutions, and open research issues
In recent years, the way that machine learning is used has undergone a paradigm shift
driven by distributed and collaborative learning. Several approaches have emerged to …
driven by distributed and collaborative learning. Several approaches have emerged to …
Leakage prediction in machine learning models when using data from sports wearable sensors
Q Dong - Computational Intelligence and Neuroscience, 2022 - Wiley Online Library
One of the major problems in machine learning is data leakage, which can be directly
related to adversarial type attacks, raising serious concerns about the validity and reliability …
related to adversarial type attacks, raising serious concerns about the validity and reliability …
On Assessing Vulnerabilities of the 5G Networks to Adversarial Examples
M Zolotukhin, P Miraghaei, D Zhang… - IEEE Access, 2022 - ieeexplore.ieee.org
The use of artificial intelligence and machine learning is recognized as the key enabler for
5G mobile networks which would allow service providers to tackle the network complexity …
5G mobile networks which would allow service providers to tackle the network complexity …
[PDF][PDF] Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems.
MH Abidi, H Alkhalefah… - CMES-Computer Modeling …, 2024 - researchgate.net
The healthcare data requires accurate disease detection analysis, real-time monitoring, and
advancements to ensure proper treatment for patients. Consequently, Machine Learning …
advancements to ensure proper treatment for patients. Consequently, Machine Learning …