N
Nor Shahida Mohd Shah
Researcher at Universiti Tun Hussein Onn Malaysia
Publications - 95
Citations - 904
Nor Shahida Mohd Shah is an academic researcher from Universiti Tun Hussein Onn Malaysia. The author has contributed to research in topics: MIMO & Signal. The author has an hindex of 12, co-authored 92 publications receiving 577 citations. Previous affiliations of Nor Shahida Mohd Shah include Osaka University & University of Malaya.
Papers
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Journal ArticleDOI
A Review of Partial Transmit Sequence for PAPR Reduction in the OFDM Systems
Yasir Amer Jawhar,Lukman Audah,Montadar Abas Taher,Khairun Nidzam Ramli,Nor Shahida Mohd Shah,Mustafa Musa,Mustafa Sami Ahmed +6 more
TL;DR: The simulation and the numerical calculations results show that the rows exchange-interleaving PTS scheme is the best method for reducing the PAPR value with low complexly in the frequency domain, and the cooperative PTS method is thebest among the modulation stage methods, while the cyclic shift sequence PTS method achieves the superior performance in PAPr reduction and computational complexity for the time domain methods.
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A Novel Self-Tuning Fuzzy Logic Controller Based Induction Motor Drive System: An Experimental Approach
Nabil Farah,Md. Hairul Nizam Talib,Nor Shahida Mohd Shah,Qazwan Abdullah,Zulkifilie Ibrahim,J. M. Lazi,Auzani Jidin +6 more
TL;DR: The purpose of this paper is to design and implement a simple self-tuning fuzzy logic controller (ST-FLC) for IM drives application that is able to adjust the output scaling factor of the main FLC speed controller by improving the accuracy of the crisp output.
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A Survey on Deep Learning for Ultra-Reliable and Low-Latency Communications Challenges on 6G Wireless Systems
Adeeb Salh,Lukman Audah,Nor Shahida Mohd Shah,Abdulraqeb Alhammadi,Qazwan Abdullah,Yun Hee Kim,Samir A. Al-Gailani,Shipun Anuar Hamzah,B. A. F. Esmail,Akram A. Almohammedi +9 more
TL;DR: In this paper, an improvement to the multi-level architecture by enabling artificial intelligence (AI) in URLLC is presented, which is done through the application of learning, predicting, and decision-making to manage the stream of individuals trained by big data.
Journal ArticleDOI
Energy-efficient power allocation and joint user association in multiuser-downlink massive MIMO system
Adeeb Salh,Nor Shahida Mohd Shah,Lukman Audah,Qazwan Abdullah,Waheb A. Jabbar,Mahathir Mohamad +5 more
TL;DR: The study aims to maximize the non-convex EE in a downlink (DL) massive MIMO system using a proposed energy-efficient low-complexity algorithm (EELCA) that guarantees optimal power allocation solution based on Newton's methods and joint user's association based on the Lagrange’s decomposition method.
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Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks
TL;DR: It is concluded that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas.