Machine Learning in Short-Reach Optical Systems: A Comprehensive Survey
C Shao, SM Billah, E Giacoumidis, S Li, J Li… - arXiv preprint arXiv …, 2024 - arxiv.org
In recent years, extensive research has been conducted to explore the utilization of machine
learning algorithms in various direct-detected and self-coherent short-reach communication …
learning algorithms in various direct-detected and self-coherent short-reach communication …
[HTML][HTML] Generalized Hybrid LiFi-WiFi UniPHY Learning Framework Towards Intelligent UAV-based Indoor Networks
Advancements in unmanned aerial vehicle (UAV) technology, along with indoor hybrid LiFi-
WiFi networks (HLWN), promise the development of cost-effective, energy-efficient …
WiFi networks (HLWN), promise the development of cost-effective, energy-efficient …
The Use of Deep Learning Techniques in OFDM Receivers for 5G NR: A Survey
Abstract The Fifth Generation (5G) New Radio (NR) wireless system is the most promising
next-generation solution to meet the needs of the increasing demands of mobile market …
next-generation solution to meet the needs of the increasing demands of mobile market …
[HTML][HTML] Analyzing the Influence of Diverse Background Noises on Voice Transmission: A Deep Learning Approach to Noise Suppression
A Nogales, J Caracuel-Cayuela, ÁJ García-Tejedor - Applied Sciences, 2024 - mdpi.com
Featured Application A deep learning application to improve speech clarity in digital audio
affected by environmental noises, showing potential for enhancing real-time streaming …
affected by environmental noises, showing potential for enhancing real-time streaming …
Learning-to-Learn the Wave Angle Estimation
A precise incident wave angle estimation in aerial communication is a key enabler in sixth-
generation wireless communication network. With this goal, a generic 3-dimensional (3D) …
generation wireless communication network. With this goal, a generic 3-dimensional (3D) …
Deep learning-based receiver design for generalized frequency division multiplexing (GFDM)
SMJA Tabatabaee, A Maroosi - Physical Communication, 2024 - Elsevier
Generalized frequency division multiplexing (GFDM) is a new efficient multi-carrier system in
highly dispersive channels. In a conventional GFDM receiver, if the length of a GFDM block …
highly dispersive channels. In a conventional GFDM receiver, if the length of a GFDM block …
A Hardware Accelerated Autoencoder for RF Communication Using Short-Time-Fourier-Transform Assisted Convolutional Neural Network
K Jung, J Woo, S Mukhopadhyay - 2024 Design, Automation & …, 2024 - ieeexplore.ieee.org
This paper presents a hardware-accelerated autoencoder (AE) for wireless communication
using a Short-Time-Fourier-Transform Assisted Convolutional Neural Network (STFT-CNN …
using a Short-Time-Fourier-Transform Assisted Convolutional Neural Network (STFT-CNN …
End-to-End Autoencoder for Drill String Acoustic Communications
I Lezhenin, A Sidnev, V Tsygan, I Malyshev - arXiv preprint arXiv …, 2024 - arxiv.org
Drill string communications are important for drilling efficiency and safety. The design of a
low latency drill string communication system with high throughput and reliability remains an …
low latency drill string communication system with high throughput and reliability remains an …
CNN-AE 在超奈奎斯特无线光通信端到端系统中的性能.
曹明华， 王瑞， 张悦， 张星宇… - Journal of Chongqing …, 2024 - search.ebscohost.com
符号间干扰的存在使超奈奎斯特(faster-than-NyquistꎬFTN) 速率无线光通信系统的性能受到
严重影响ꎬ 针对此问题ꎬ 提出了一种基于卷积神经网络自编码器的端到端通信系统来消除符号 …
严重影响ꎬ 针对此问题ꎬ 提出了一种基于卷积神经网络自编码器的端到端通信系统来消除符号 …
CNN-Based End-to-End Deeper Autoencoders for Physical Layer of Wireless Communication System
In this paper, a deeper autoencoder is proposed, which is composed of systematic and
strategic convolutional neural network (CNN) layers. The proposed autoencoder can …
strategic convolutional neural network (CNN) layers. The proposed autoencoder can …