Autoencoder-Based Spatial Modulation for the Next Generation of Wireless Networks
Spatial Modulation (SM) has been proposed as a multiple-input-multiple-output (MIMO)-
based technique to overcome the inter-channel interference experienced in conventional …
based technique to overcome the inter-channel interference experienced in conventional …
Channel fading-robust pre-coders for low complexity few-mode IM/DD short reach fiber communications
In this letter, an autoencoder (AE) is used to optimize linear and nonlinear digital pre-coders
for short reach few-mode fiber transmission. Mach-Zehnder modulation is used to modulate …
for short reach few-mode fiber transmission. Mach-Zehnder modulation is used to modulate …
A MIMO Detector With Deep-Neural-Network for Faster-Than-Nyquist Optical Wireless Communications
M Cao, R Yao, Q Sun, Y Zhang, Q Yang… - IEEE Photonics …, 2024 - ieeexplore.ieee.org
Conventional multiple input multiple output (MIMO) detection algorithms face challenges
related to computational complexity and limited performance when handling high …
related to computational complexity and limited performance when handling high …
Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication
This paper presents a comprehensive study on the possible hybrid quantum-classical
autoencoder architectures for end-to-end radio communication against noisy channel …
autoencoder architectures for end-to-end radio communication against noisy channel …
Enhancing Physical Layer Security with Deep SIMO Auto-Encoder and RF Impairments Modeling
This paper presents a novel approach to achieving secure wireless communication by
leveraging the inherent characteristics of wireless channels through end-to-end learning …
leveraging the inherent characteristics of wireless channels through end-to-end learning …
Capacity and achievable rates of fading few-mode mimo im/dd optical fiber channels
The optical fiber multiple-input multiple-output (MIMO) channel with intensity modulation and
direct detection (IM/DD) per spatial path is treated. The spatial dimensions represent the …
direct detection (IM/DD) per spatial path is treated. The spatial dimensions represent the …
Machine learning for optimal resource allocation
M Pesavento, F Bahlke - Machine Learning for Future Wireless …, 2020 - Wiley Online Library
This chapter addresses decentralized approaches for minimizing network resource
consumption through both user allocation and range expansion. Machine Learning (ML) is …
consumption through both user allocation and range expansion. Machine Learning (ML) is …
[HTML][HTML] Dynamic adversarial jamming-based reinforcement learning for designing constellations
Y Xu, H Xie, N Ji, Y Chen, N Liu, X Xiang - Digital Communications and …, 2023 - Elsevier
To resist various types of jamming in wireless channels, appropriate constellation
modulation is used in wireless communication to ensure a low bit error rate. Due to the …
modulation is used in wireless communication to ensure a low bit error rate. Due to the …
Learning to modulate for non-coherent MIMO
Y Wang, T Koike-Akino - ICC 2020-2020 IEEE International …, 2020 - ieeexplore.ieee.org
The deep learning trend has recently impacted a variety of fields, including communication
systems, where various approaches have explored the application of neural networks in …
systems, where various approaches have explored the application of neural networks in …
Deep learning decoder for MIMO communications with impulsive noise
O Delgado, F Labeau - 2020 IEEE 17th Annual Consumer …, 2020 - ieeexplore.ieee.org
In this paper we consider signal detection in multiple-input-multiple-output (MIMO) systems
with an impulsive noise channel. The existing, near optimal, sphere decoder (SD) achieves …
with an impulsive noise channel. The existing, near optimal, sphere decoder (SD) achieves …