Super-resolution channel estimation based deep learning in reconfigurable intelligent surface systems

QR Code

Super-resolution channel estimation based deep learning in reconfigurable intelligent surface systems

The propagation environment may be configured using a reconfigurable intelligent surface (RIS). The channel estimate is a critical problem in implementing the RIS-aided communication system. A cascaded channel with large dimensions and complex statistics is used in a RIS-aided multi-user multiple-in...

Full description

Bibliographic Details
Main Authors:	A . Rasid, Mohd Fadlee, Hussein, Wala’a, Ismail, Alyani, Audah, Kamil, Noordin, Nor K.
Format:	Article
Language:	English
Published:	Auricle Global Society of Education and Research 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/119485/ http://psasir.upm.edu.my/id/eprint/119485/1/119485.pdf

Similar Items

Cascaded and separate channel estimation based on CNN for RIS-MIMO systems
by: Hussein, Wala'a, et al.
Published: (2024)

Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN.
by: Audah, Kamil, et al.
Published: (2024)

Maximizing DRL-based energy efficiency in IRS-NOMA using a DDPG algorithm for the next generation of wireless communications
by: Audah, Kamil, et al.
Published: (2024)

Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
by: Ali, Wala'a Hussein
Published: (2018)

Super-resolution mapping
by: Muad, Anuar Mikdad
Published: (2011)

Super resolution for surveillance application
by: Anand Pakiam, Gerard
Published: (2007)

Improving super-resolution mapping through combining multiple super-resolution land-cover maps
by: Li, Xiaodong, et al.
Published: (2016)

Super resolution land cover mapping of hyperspectral images using the deep image prior-based approach
by: Ma, Xiaofeng, et al.
Published: (2020)

Motion-based super-resolution in the peripheral visual field
by: Patrick, Jonathan A., et al.
Published: (2017)

Multi-frame super-resolution: a survey
by: Khattab, Mahmoud, et al.
Published: (2019)

Super-FAN: integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
by: Bulat, Adrian, et al.
Published: (2018)

Optimizing hopfield neural network for super-resolution mapping
by: Anuar M. Muad,, et al.
Published: (2020)

High-resolution multipath channel parameter estimation using wavelet analysis
by: Aboaba, Olusegun Abiola
Published: (2014)

A family of reconfigurable neurocomputers for the "intelligent factory"
by: Erdogan, S. S., et al.
Published: (1992)

Finetuned Super-Resolution Generative Adversarial Network (Artificial Intelligence) Model for Calcium Deblooming in Coronary Computed Tomography Angiography
by: Sun, Zhonghua, et al.
Published: (2022)

Enhanced notes capture using super resolution technique on tecogan
by: Lee, Theresa Wen Yan
Published: (2023)

Multiuser Uplink MIMO Communications Assisted by Multiple Reconfigurable Intelligent Surfaces
by: Lv, Y., et al.
Published: (2021)

Design of a reconfigurable, modular and multi-channel bioimpedance spectroscopy system
by: Al-hashimi, Ahmad, et al.
Published: (2017)

Regularization-based multi-frame super-resolution: a systematic review
by: Khattab, Mahmoud, et al.
Published: (2020)

Comparison of super resolution methods in magnetic resonance images for small animals
by: Than, Joel Chia Ming, et al.
Published: (2019)

Super resolution imaging using modified lanr based on separable filtering
by: Somadina, Ike Chidiebere
Published: (2019)

Artificial Intelligence (Enhanced Super-Resolution Generative Adversarial Network) for Calcium Deblooming in Coronary Computed Tomography Angiography: A Feasibility Study
by: Sun, Zhonghua, et al.
Published: (2022)

Using super resolution microscopy to investigate the role of actin in adenosine receptor organisation
by: Garlick, Evelyn
Published: (2023)

Performance evaluation of reconfigurable intelligent surface against distributed antenna system at the cell edge
by: Kamaruddin, Nuraqila Alini, et al.
Published: (2022)

Integration of Luenberger estimator with control reconfiguration system for hypersonic aircraft
by: Zaludin, Zairil
Published: (2023)

End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels
by: Mfarej, Sumaya Dhari Awad
Published: (2021)

Analysis of joint channel estimation and joint data detection in TD-SCDMA systems
by: Marzook, Ali Kamil, et al.
Published: (2011)

A Super-Resolution Convolutional-Neural-Network-Based Approach for Subpixel Mapping of Hyperspectral Images
by: Ma, X., et al.
Published: (2019)

Reconfiguring Space
by: Thomas, Paul
Published: (2009)

Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
by: Ismail, Alyani, et al.
Published: (2013)

Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
by: Marzook, Ali Kamil, et al.
Published: (2013)

Single-Feed Polarization Reconfigurable Patch Antenna
by: Nurul Hazlina, Noordin, et al.
Published: (2012)

A Global Approach for Quantitative Super Resolution and Electron Microscopy on Cryo and Epoxy Sections Using Self-labeling Protein Tags
by: Müller, A., et al.
Published: (2017)

An Overview on Existential Threats Posed-by Human-like Super-intelligent Machines to Humanity
by: Jie, Xi
Published: (2021)

A New Super Wideband Fractal Monopole-Dielectric Resonator Antenna.
by: Ismail, Alyani, et al.
Published: (2013)

Reconfiguring material boundaries
by: Thomas, Paul
Published: (2010)

An efficient algorithm for improving precision of multi-cell channel estimation systems
by: Marzook, Ali Kamil, et al.
Published: (2012)

Speed estimation and target detection in forward scattering radar
by: Raja Abdullah, Raja Syamsul Azmir, et al.
Published: (2008)

Impact of land cover patch size on the accuracy of patch area representation in HNN-based super resolution mapping
by: Muad, Anuar M., et al.
Published: (2012)

Frequency reconfiguration mechanism of a PIN diode on a reconfigurable antenna for LTE and WLAN applications
by: Shah, S. M., et al.
Published: (2018)