Indoor Wireless Optical CDMA System for LANs and Healthcare Monitoring - Alyan, Emad Ahmed
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Unlimited customer demands such as the need for higher data rates, higher security, and increased cost effectiveness, have led to the rapid development of optical wireless communication (OWC) systems over RF communication systems due to the former's high transmission bandwidth. However, OWC systems suffer from multipath dispersion, background noise, and multiple access interference and phase-induced intensity noise when the system has to accommodate multiple users simultaneously. This book investigates the use of optical code division multiple access (OCDMA) technology and optimized divergence…mehr

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Produktbeschreibung
Unlimited customer demands such as the need for higher data rates, higher security, and increased cost effectiveness, have led to the rapid development of optical wireless communication (OWC) systems over RF communication systems due to the former's high transmission bandwidth. However, OWC systems suffer from multipath dispersion, background noise, and multiple access interference and phase-induced intensity noise when the system has to accommodate multiple users simultaneously. This book investigates the use of optical code division multiple access (OCDMA) technology and optimized divergence angle of the transmitter, to reduce the impairments that exist in the system. It also investigates the use of infrared technology in an indoor mobile healthcare monitoring system to ensure the quality of transmission between the coupled transmitter with the medical nodes, which might be attached to the patient's body, and the established base station on the ceiling of the hospital room. This is because existing technology is generally based on RF systems, which might suffer from electromagnetic interference.
Autorenporträt
Emad Ahmed Alyan is a PhD candidate in biomedical engineering at Universiti Teknologi Petronas (UTP), Malaysia. Some of his research work has been published in refereed journals and conferences. His current research revolves around medical signal processing, computational neuroscience, with an emphasis on machine learning and statistical analysis.