Enhancement of Microstrip Patch Antenna Design and Performance for S-Band Applications Using Fuzzy Logic

Abstract: S-band (2-4 GHz) antennas play a critical role in modern wireless systems such as satellite communication, Wi-Fi, Bluetooth, and mobile networks. Microstrip Patch Antennas (MSPAs) are widely preferred for these applications due to their compact size, low profile, and ease of fabrication. However, conventional MSPA designs often exhibit narrow bandwidth, low gain, and reduced radiation efficiency because of strong nonlinear coupling among design parameters. This paper presents an Artificial Intelligence (AI) based optimization approach using Fuzzy Logic (FL) to enhance the performance of S-band MSPA. A Fuzzy Inference System (FIS) is developed to intelligently tune critical antenna parameters including patch dimensions and feed location. The paper proposes the design is implemented in MATLAB R2013a [8] and evaluated at a target frequency of 2.6 GHz. Simulation results demonstrate considerable improvement in antenna performance, achieving enhanced bandwidth, improved gain, and acceptable impedance matching. Comparative analysis confirms that the fuzzy logic optimized MSPA outperforms the conventionally designed antenna in terms of bandwidth, compactness, and radiation characteristics, making it suitable for modern S-band wireless communication applications in the current scenario.

Keywords: S-band, Microstrip Patch Antenna, Fuzzy Logic, Artificial Intelligence, Antenna Optimization, Bandwidth, Gain.