K
Khaled M. Rabie
Researcher at Manchester Metropolitan University
Publications - 198
Citations - 3628
Khaled M. Rabie is an academic researcher from Manchester Metropolitan University. The author has contributed to research in topics: Computer science & Fading. The author has an hindex of 25, co-authored 156 publications receiving 2262 citations. Previous affiliations of Khaled M. Rabie include University of Manchester & Nazarbayev University.
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White Paper on Broadband Connectivity in 6G
Nandana Rajatheva,Italo Atzeni,Emil Björnson,Andre Bourdoux,Stefano Buzzi,Jean-Baptiste Dore,Serhat Erkucuk,Manuel Fuentes,Ke Guan,Yuzhou Hu,Xiaojing Huang,Jari Hulkkonen,Josep Miquel Jornet,Marcos Katz,Rickard Nilsson,Erdal Panayirci,Khaled M. Rabie,Nuwanthika Rajapaksha,Mohammad Javad Salehi,Hadi Sarieddeen,Shahriar Shahabuddin,Tommy Svensson,Oskari Tervo,Antti Tolli,Qingqing Wu,Wen Xu +25 more
TL;DR: This white paper explores the road to implementing broadband connectivity in future 6G wireless systems, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h.
Journal ArticleDOI
Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review
Augustine Ikpehai,Bamidele Adebisi,Khaled M. Rabie,Kelvin Anoh,Ruth Ande,Mohammad Hammoudeh,Haris Gacanin,Uche M. Mbanaso +7 more
TL;DR: The results indicate that operating an IoT device in a temperature of −20 °C can shorten its life by about half, and with a 10% improvement in receiver sensitivity, NB-IoT 882 MHz and LoRaWAN can increase coverage by up to 398% and 142%, respectively, without adverse effects on the energy requirements.
Proceedings ArticleDOI
A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study
Halgurd S. Maghded,Kayhan Zrar Ghafoor,Ali Safaa Sadiq,Kevin Curran,Danda B. Rawat,Khaled M. Rabie +5 more
TL;DR: In this article, a new framework is proposed to detect COVID-19 using built-in smartphone sensors, which provides a low-cost solution, since most of radiologists have already held smartphones for different daily-purposes.
Journal ArticleDOI
Detection of advanced persistent threat using machine-learning correlation analysis
Ibrahim Ghafir,Ibrahim Ghafir,Mohammad Hammoudeh,Vaclav Prenosil,Liangxiu Han,Robert Hegarty,Khaled M. Rabie,Francisco J. Aparicio-Navarro +7 more
TL;DR: The presented system is able to predict APT in its early steps with a prediction accuracy of 84.8% and is a significant contribution to the current body of research.
Posted Content
A Novel AI-enabled Framework to Diagnose Coronavirus COVID 19 using Smartphone Embedded Sensors: Design Study
Halgurd S. Maghdid,Kayhan Zrar Ghafoor,Ali Safaa Sadiq,Kevin Curran,Danda B. Rawat,Khaled M. Rabie +5 more
TL;DR: A new framework is proposed to detect COVID-19 using built-in smartphone sensors and reads the smartphone sensors’ signal measurements to predict the grade of severity of the pneumonia as well as predicting the result of the disease.