M
Mahmoud A. M. Albreem
Researcher at University of Sharjah
Publications - 80
Citations - 1298
Mahmoud A. M. Albreem is an academic researcher from University of Sharjah. The author has contributed to research in topics: MIMO & Detector. The author has an hindex of 10, co-authored 70 publications receiving 544 citations. Previous affiliations of Mahmoud A. M. Albreem include Universiti Malaysia Perlis & Universiti Sains Malaysia.
Papers
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Journal ArticleDOI
Massive MIMO Detection Techniques: A Survey
TL;DR: This paper discusses optimal and near-optimal detection principles specifically designed for the massive MIMO system such as detectors based on a local search, belief propagation and box detection, and presents recent advances of detection algorithms which are mostly based on machine learning or sparsity based algorithms.
Journal ArticleDOI
Sixth generation (6G)wireless networks: Vision, research activities, challenges and potential solutions
Mohammed H. Alsharif,Anabi Hilary Kelechi,Mahmoud A. M. Albreem,Shehzad Ashraf Chaudhry,M. Sultan Zia,Sunghwan Kim +5 more
TL;DR: This study highlights the most promising lines of research from the recent literature in common directions for the 6G project, exploring the critical issues and key potential features of 6G communications and contributing significantly to opening new horizons for future research directions.
Proceedings ArticleDOI
5G wireless communication systems: Vision and challenges
TL;DR: Why there is a need for 5G, advantages, and challenges, and a comprehensive study related to 5G has been presented.
Proceedings ArticleDOI
Green internet of things (IoT): An overview
Mahmoud A. M. Albreem,Ayman A. El-Saleh,Muzamir Isa,Wael A. Salah,Muzammil Jusoh,M. M. Azizan,Azuwa Ali +6 more
TL;DR: An overview regarding green IoT, which discusses the life cycle of green IoT which contains green design, green production, green utilization, and green recycling, and studies of IoT in 5G and IoT for smart cities are presented.
Journal ArticleDOI
Overview of Precoding Techniques for Massive MIMO
TL;DR: In this paper, the authors provide insights on linear precoding algorithms for massive MIMO systems and discuss the performance and energy efficiency of the precoders. And they also present potential future directions of linear precoder algorithms.