Interference Techniques Based on Deep Learning in Wireless Networks

S Arunprasath, A Suresh… - Resource Management in …, 2025 - Wiley Online Library
On small‐scale wireless networks, traditional architectures deliver fast execution and nearly
ideal performance, but when user density is high, the performance suffers significantly. The …

A Comprehensive Analysis of Deep Learning for Interference Suppression, Sample and Model Complexity in Wireless Systems

TR Oyedare - 2024 - vtechworks.lib.vt.edu
The wireless spectrum is limited and the demand for its use is increasing due to
technological advancements in wireless communication, resulting in persistent interference …

[PDF][PDF] Deep Learning for Wireless Interference Segmentation and Prediction

S Chinchali, S Tandon - Sandeep-Chinchali/3102622, 2012 - Citeseer
The proliferation of wireless devices ranging from smartphones to medical implants has led
to unprecedented levels of interference in shared, unlicensed spectrum. Modern devices …

Deep learning interference cancellation in wireless networks

Y Zhou, A Samiee, T Zhou, B Jalali - arXiv preprint arXiv:2009.05533, 2020 - arxiv.org
With the crowding of the electromagnetic spectrum and the shrinking cell size in wireless
networks, crosstalk between base stations and users is a major problem. Although hand …

Deep learning for experimental hybrid terrestrial and satellite interference management

P Henarejos, MÁ Vázquez… - 2019 IEEE 20th …, 2019 - ieeexplore.ieee.org
Interference Management is a vast topic present in many disciplines. The majority of
wireless standards suffer the drawback of interference intrusion and the network efficiency …

Interference estimation and mitigation in wireless networks

SA Mustafa - International Journal of Computing and Digital …, 2015 - journals.uob.edu.bh
To improve the resource utilization, the world of wireless communication network has seen
suggestion and developing of new frameworks targeting an improved model of resource …

Keep it simple: Cnn model complexity studies for interference classification tasks

T Oyedare, VK Shah, DJ Jakubisin… - IEEE INFOCOM 2023 …, 2023 - ieeexplore.ieee.org
The growing number of devices using the wireless spectrum makes it important to find ways
to minimize interference and optimize the use of the spectrum. Deep learning models, such …

[图书][B] Learning-based interference mitigation for wireless networks

CC Chen - 2009 - search.proquest.com
Wireless networks have raised great attention in the past decades because they provide
tether-free connectivity. Although much of the effort in wireless network research has been …

Interference suppression using deep learning: Current approaches and open challenges

T Oyedare, VK Shah, DJ Jakubisin, JH Reed - IEEE Access, 2022 - ieeexplore.ieee.org
In light of the finite nature of the wireless spectrum and the increasing demand for spectrum
use arising from recent technological breakthroughs in wireless communication, the problem …

Learning to optimize: Training deep neural networks for interference management

H Sun, X Chen, Q Shi, M Hong, X Fu… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Numerical optimization has played a central role in addressing key signal processing (SP)
problems. Highly effective methods have been developed for a large variety of SP …