Abstract

Antennas with multifunctional capabilities integrated into a single device that demonstrates a high performance are in demand, and microstrip antennas with quadband coverage are very useful for a wide range of mm-wave applications. Antennas and propagation at mm-wave frequencies, on the other hand, poses several challenges which can be overcome by applying performance enhancement techniques to meet design objectives. This article presents the use of a binary-coded genetic algorithm for developing an improved quadband mm-wave microstrip patch antenna. The patch shape was optimized by dividing a conducting surface into 6 × 6 tiny rectangular blocks. The algorithm generated the solution space by introducing conducting and nonconducting features for each radiating cell on the patch surface and then greedily searched for the best-fitted individual based on the cost function. With the combination of High-Frequency Structure Simulator (HFSS) and MATLAB, candidate antennas were iteratively modeled by applying the suggested algorithm. The optimized antenna resonated at four frequencies centered at 28.3 GHz, 38.1 GHz, 46.6 GHz, and 60.0 GHz. The antenna realized a peak broadside directivity of 7.8 dB, 8.8 dB, 7.3 dB, and 7.1 dB, respectively, with a total operating bandwidth of 11.5 GHz. The research findings were compared with related works presented in the literature and found that the optimized antenna outperformed them in terms of bandwidth, directivity, and efficiency.

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