In the paper, we propose a fuzzy logic controller system to be implemented for smart mobility management in the 5G wireless communication network. Mobility management is considered as a main issue for all-IP mobile networks future generation. As a network-based mobility management protocol, Internet Engineering Task Force developed the Proxy Mobile IPv6 (PMIPv6) in order to support the mobility of IP devices, and many other results were presented to reduce latency handover and the amount of PMIPv6 signaling, but it is not enough for the application needs in realtime. The present paper describes an approach based on the IEEE 802.21 Media Independent Handover (MIH) standard and PMIPv6, so we present a new vertical handover algorithm for anticipating handover process efficiently. Our object is to propose a smart mobility management that contribute in 5G wireless communication system network operating functions. Two proposed dynamic thresholds were successfully made to guaranty process triggering, and a new primitive MIH is proposed for signaling a needed handover to be done. Simulation results demonstrate a significant reduction of the handover delay, packet loss, handover blocking probability and signaling overhead. Simulation results and tests are accomplished.
The antenna is a critical component of the communication system. The antenna is used in wireless communication for signal transmission and reception over long distances. There are numerous sorts of antennas, such as wire antennas, traveling wave antennas, reflector antennas, microstrip antennas, and so on. The application of antennas is determined by the antenna's attributes as well as the frequency range of operation. As a result, it is vital to understand the behavior of antennas over a wide range of operations and select the optimum antenna for the application. The performance parameters of the antenna determines its efficiency. VSWR, Return Loss, Directivity, Bandwidth, and more parameters are available. As a result, one of the primary areas of focus is antenna analysis. In this study, we simulate various antenna types and derive performance parameters such as return loss, directivity, and so on. MATLAB will be used to simulate the antenna at various frequencies. When all of the parameters are taken into account, the analysis becomes quite tough. In this case of ambiguity, we use fuzzy logic to calculate the antenna's performance index. A variety of antenna parameters will be fed into the fuzzy inference system, which will make a judgment based on a set of rules. The crisp numbers are turned into fuzzy values using the fuzzification process, then evaluated and defuzzied to obtain the antenna's performance index. The fuzzy inference system will be developed in MATLAB, and the overall system will be modeled in Simulink.
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