M
M. Naufal M. Saad
Researcher at Universiti Teknologi Petronas
Publications - 12
Citations - 63
M. Naufal M. Saad is an academic researcher from Universiti Teknologi Petronas. The author has contributed to research in topics: MIMO & Multi-agent system. The author has an hindex of 4, co-authored 11 publications receiving 45 citations. Previous affiliations of M. Naufal M. Saad include Petronas.
Papers
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Journal ArticleDOI
Modulation classification for MIMO systems: State of the art and research directions
Mohammad Rida Bahloul,Mohd Zuki Yusoff,Abdel-Haleem Abdel-Aty,M. Naufal M. Saad,Marwan Al-Jemeli +4 more
TL;DR: The modulation classification for MIMO systems is discussed and a comprehensive and critical literature review of the existing MC algorithms for M IMO systems are presented; where possible, gaps in the knowledge base are identified and future directions for the research work are suggested.
Journal ArticleDOI
An Efficient Likelihood-Based Modulation Classification Algorithm for MIMO Systems.
TL;DR: A new algorithm to overcome the problems associated with the existing likelihood-based MC algorithms is developed and shows that the proposed algorithm works well under various operating conditions, and performs close to the performance upper bound with reasonable complexity.
Journal ArticleDOI
An efficient likelihood-based modulation classification algorithm for multiple-input multiple-output systems
TL;DR: In this article, the authors formulated the modulation classification problem as maximizing a global likelihood function formed by combining the likelihood functions for the estimated transmitted signals, where minimum mean square error (MMSE) filtering is employed to separate the MIMO channel into several sub-channels.
Journal ArticleDOI
Efficient and Low Complexity Modulation Classification Algorithm for MIMO Systems
TL;DR: The results show that the proposed algorithm is capable of classifying the considered modulation schemes with good classification accuracy and can achieve performance comparable to that of the HLRT approach while having a significantly lower computational complexity.
Proceedings ArticleDOI
Motorcyclists safety system to avoid rear end collisions based on acoustic signatures
TL;DR: An acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications and it is believed that this method can help to reduce a significant number of motorcycle accidents.