Synthesization of M-type hexaferrite with composition Ba 0.5 Sr 0.5 Co x Ga x Fe 12-2x O 19 (x = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0) has been performed at temperature 1100 °C for 15 h by adopting conventional ceramic method. For analyzing the structure of synthesized material, the X-ray diffraction (XRD) method has been used. Besides that its properties are observed by using different characterization techniques like VSM (vibrating sample magnetometer), Fourier Transform Infrared (FTIR) spectra and VNA (Vector network analyzer), SEM (scanning Electron Microscopy), Energy-dispersive X-ray spectroscopy (EDAX). Microwave absorption property has been investigated using quarter wavelength and impedance matching mechanism in the X-Band range (8.2-12.4 GHz). From the results obtained, it was being observed that microwave absorption was best at doping concentration x = 0.4 i.e. −33.36 dB reflection loss at thickness 2.0 mm and frequency 9.62 GHz. The synthesized samples can be used for different possible applications in X-Band as narrowband & broadband absorbers and EMI shielding devices. The main applications are Electromagnetic Compatibility, microwave filters, network switches, Radar cross-section reduction (RCS) in the military, electronic enclosures and antenna applications.
In today’s scenario, mobile communication is facing a healthy competition due to different networks, interfaces, channels, and many more available in wireless heterogeneous environment. The problem arises when customers/users get the availability of many interfaces at the same time. At that time users need an intelligent or smart mechanism to connect them to the best services according to their requirements/preferences. Interface management manages available interfaces and connects the user with the best. In this paper, Interface management with Artificial Neural Network (ANN) allows the smart use of different radio accesses/interfaces. The selection is made with different parameters of different networks. This paper proposed a backpropagation neural network that is used for the switching in between different networks-3G, WLAN, 4G and 5G. The different parameters of a network are used as the selection parameters with assigning proper weights. Weights are initialized with fuzzy AHP and optimized with Back Propagation Neural Network (BPNN). The target value and the actual value is compared and their difference used as the adjusting value for the weights to get the optimum value. The backpropagation is used to train the network. The comparison among the projected algorithm and the existing algorithm shows the valuablity of the new method and the best connectivity of the network.
An experimental study of microstrip patch antenna designed and fabricated on FR4 epoxy substrate is presented. Further a performance comparison of designed antenna is made with proposed design using Gallium doped Ba-Sr hexagonal ferrite substrate. Microstrip feed line is used for inputting the signal to antenna. The whole simulation is done on HFSS simulator (version 13.0).The center frequency for proposed antenna is 10GHz and is optimized for significant performance parameters viz return loss, bandwidth, VSWR and gain. It was observed that the designed antenna provides better results with ferrite substrate as compared to FR4 epoxy substrate showing -10db broad bandwidth of 4.2GHz in the frequency region 8.2GHz to 12.4GHz. Although, the results of other parameters like return loss, VSWR and gain are found to be optimum with FR4 substrate as compared to mentioned ferrite substrate. The prototype of proposed antenna with FR4 epoxy substrate is fabricated and tested to attain the experimental results. The measured results are found to be better than simulated results. Thus the proposed antenna structure can be considered suitable for microwave communication application in X-band.
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