Yazar "Hussein, M.K." seçeneğine göre listele

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    A review software defined networking for Internet of things
    (Institute of Electrical and Electronics Engineers Inc., 2020) Mohammed, Alaa Hamid; Khaleefah, Raad M.; Hussein, M.K.; Abdulateef, Ihsan Amjad
    With the emergence of Internet of Things (IoT), there is now increasing interest in simplifying control of wireless networks. This is a very challenging task, which includes information acquisition, information analysis, decision-making and large-scale IoT networks implementing action. Resulting in research to explore the integration of Software Defined Networking (SDN) and IoT to make network control simpler, easier, and less strainy. SDN is a promising new paradigm shift capable of enabling a simplified and robust wireless programmable network to serve a range of physical objects and applications. This review article begins with SDN emerging. Recent significant developments in the wireless and optical domains are then highlighted with a view to integrating SDN and IoT. The SDN and IoT development issues are often explored from a security and scalability viewpoint. © 2020 IEEE.
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    The method of calibration compensation for fiber nonlinearity-A review
    (Institute of Electrical and Electronics Engineers Inc., 2020) Mohammed, Alaa Hamid; Khaleefah, Raad. M.; Hussein, M.K.; Almarzoogee, Ammar Hatem
    Digital signal processing for compensation for fibre nonlinearity Is a key enabler of ever-greater demand higher data rates for unified optical transmissions. A big challenge to the existing techniques that is the nonlinear coefficient of fiber Must be properly scale-up during compensation In order to attain the achieveable improvement in signal quality. In this paper, we have reviewed several papers in Fiber Nonlinear using several algorithms as well as processing the signal transmitting This problem is adaptively optimized using a low-complexity algorithm A soft-decision, bitwise demodulator based metric used for modern applications Decoders from the FEC. The study demonstrates an optimal scaling factor analysis with predictable accuracy. © 2020 IEEE.