Designing a microstrip patch antenna at 3GHz frequency is very interesting task to the researchers due to wide applicability for IoT, body wearable antenna, WLAN, ISM communication etc. In this paper, a circular microstrip patch antenna with resonance at a frequency of 3GHz has been designed using FR4 substrate and inset feeding using CST studio. Initially, the antenna is manually tuned at the 3GHz operating frequency and obtain S11 is -38dB which is best compare to the existing works at this frequency. Next, the parametric influences have been observed by varying several antenna design parameters (i.e. patch radius and substrate height) and observing the respective variation in output like S11, bandwidth. In the next phase of this work, surface fitting technique has been used to model the 3GHz circular patch antenna that helps to predict the output S11, resonance frequency and bandwidth with satisfactory prediction accuracy. Surface-fitting model will help to reduce the effort and time required for redesigning and simulation of this type of circular patch antenna in future.  

The design of suitable compact antenna for 5G applications with superior return loss and bandwidth is still a fascinating task to the researchers. In this paper, the authors have designed a dual band microstrip patch antenna for 5G communications at 28 GHz and 46 GHz using CST studio. Rectangular patch antenna with double slots is considered to serve the purpose. The performance of the proposed patch antenna is very satisfactory in terms of return loss, VSWR, bandwidth and directivity. The values of S11 are well below -39dB and values of VSWR are very close to 1 for both resonance frequencies. The bandwidths for both cases are greater than 1.8 GHz which is an essential characteristic of 5G patch antennas for high speed connectivity and efficiency. Directivities are above 6 dB which are very suitable for the present problem. The simulation results are also compared with existing dual band 5G patch antennas and it has been observed that proposed antenna has outperformed the existing patch antennas that worked in 28GHz and 46GHz frequency range. The main advantage of this patch antenna is that it’s simple structure and good return loss, bandwidth and gain.

Linear antenna array pattern synthesis using computational method is an important task for the electronics engineers and researchers. Suitable optimization techniques are required for solving this kind of problem. In this work, Elephant Swarm Water Search Algorithm (ESWSA) has been used for efficient and accurate designing of linear antenna arrays that generate desired far field radiation pattern by optimizing amplitude, phase and distance of the antenna elements. ESWSA is inspired by water resource search procedure of elephants during drought. Two different fitness functions for two different benchmark problem of linear antenna array have been tested for validation of the proposed methodology. During optimization, three types of synthesis have been used namely: amplitude only, phase only and position only control for all cases antenna array. The results show that ESWSA is very efficient process for achieving desired radiation pattern while amplitude only control performed better compare to the others two controlling process for all benchmark problems.

Particle Swarm Optimization (PSO) is one of most widely used metaheuristics which is based on collective movement of swarm like birds or fishes. The inertia weight (w) of PSO is normally used for maintaining balance between exploration and exploitation capability. Many strategies for updating the inertia weight during iteration were already proposed by several researchers. In this paper, a Modified Particle Swarm Optimization (MPSO) algorithm based on self-adaptive acceleration constants along with Linear Decreasing Inertia Weight (LDIW) technique is proposed. Here, in spite of using fixed values of acceleration constants, the values are updated themselves during iteration depending on local and global best fitness value respectively. Six different benchmark functions and three others inertia weight strategies were used for validation and comparison with this proposed model. It was observed that proposed MPSO algorithm performed better than others three strategies for most of functions in term of accuracy and convergence although its execution time was larger than others techniques.