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Ayman Uddin Mahin
Researcher at Ahsanullah University of Science and Technology
Publications - 9
Citations - 104
Ayman Uddin Mahin is an academic researcher from Ahsanullah University of Science and Technology. The author has contributed to research in topics: Smart grid & Transmission line. The author has an hindex of 3, co-authored 9 publications receiving 48 citations. Previous affiliations of Ayman Uddin Mahin include Bangladesh University of Engineering and Technology.
Papers
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Journal ArticleDOI
Recent research in cloud radio access network (C-RAN) for 5G cellular systems - A survey
Md. Farhad Hossain,Ayman Uddin Mahin,Topojit Debnath,Farjana Binte Mosharrof,Khondoker Ziaul Islam +4 more
TL;DR: This paper presents a comprehensive survey on the most recent advances in C-RAN research focusing on the analysis and enhancement of its various major aspects, including throughput enhancement, interference management, energy efficiency, latency, security and system cost reduction.
Proceedings ArticleDOI
Developing demand side management program for residential electricity consumers of Dhaka city
TL;DR: In this article, three demand side management tools: energy efficiency, direct load control and time of use have been applied and significant amount of electrical energy can be saved using energy efficiency.
Journal ArticleDOI
Measurement and monitoring of overhead transmission line sag in smart grid: A review
Journal ArticleDOI
Millimeter Wave Based Real-Time Sag Measurement and Monitoring System of Overhead Transmission Lines in a Smart Grid
TL;DR: The performance of the proposed sag measurement methods based on millimeter wave (mmWave) signals is analyzed and compared, and trade-offs between latency and sensitivity with bandwidth, and latency and percentage average error with number of samples are rigorously investigated.
Proceedings ArticleDOI
Millimeter Wave Based Sag Measurement Using Parabolic Approximation for Smart Grid Overhead Transmission Line Monitoring
TL;DR: The results show that the proposed mmWave based sag measurement technique incorporating parabolic approximation can achieve better accuracy even with smaller number of samples, though the accuracy degrades with error in angle of arrival.