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Al-Rabayah, Mohammad
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Electrical & Electronics Engineering

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Two-way differential strategy for wireless sensor networks Alabed, Samer; Alsaraira, Amer; Mostafa, Nour; Al-Rabayah, Mohammad; Shdefat, Ahmed; Zaki, Chamseddine; A. Saraereh, Omar; Al-Arnaout, Zakwan
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6121

Abstract

In this paper, a novel optimal two-way amplify and forward (AF) differential beamforming method for wireless sensor network is proposed. The proposed method is an advanced signal processing technique used to enhance the performance and reliability of the communication link by exploiting the diversity provided by multiple antennas. Unlike current state-of-the-art methods which require the knowledge of channel state information (CSI) at both transmitting and receiving antennas or at least at the receiving antennas, the suggested method does not need CSI at any transmitting or receiving antenna. Moreover, the proposed method enjoys high error performance with high diversity and coding gain and has a very low encoding and decoding complexity. Through our simulations, the proposed method is proved to outperform the best known non-coherent multi-antenna methods.
Sinusoidal modelling for efficient source coding of phonocardiogram signals in cardiac monitoring devices Alabed, Samer; Al-Rabayah, Mohammad; Al-Sheikh, Bahaa; Farah, Lama Bou
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9806

Abstract

This study focuses on developing an efficient and cost-effective approach for compressing Phonocardiogram (PCG) signals without compromising their quality. The method utilizes two data compression techniques, capturing heart sounds and transforming them into the frequency domain to extract essential features such as frequency, phase, and amplitude peaks. The compressed signals are subsequently reconstructed to faithfully replicate the original heart sounds. The findings contribute to advancements in biomedical signal processing and compression methodologies, with potential applications in telemedicine and remote sustainable healthcare systems. Compressed PCG signals enable real-time remote consultations and continuous cardiac health monitoring, particularly in underserved regions with limited medical resources. This research holds significant potential for improving access to cardiovascular healthcare and promoting overall health and well-being.
Co-Authors A. Saraereh, Omar Al-Arnaout, Zakwan Al-Sheikh, Bahaa Alabed, Samer Alsaraira, Amer Farah, Lama Bou Mostafa, Nour Shdefat, Ahmed Zaki, Chamseddine