Design and Optimization of a Circular Loop Antenna Using Genetics Algorithm for Terrestrial Communication

This paper is about the optimization of a small circular loop antenna using a Genetic Algorithm (GA) to significantly enhance its radiation efficiency for operation at 38.22MHz. Traditional small loop antennas are known for their poor radiation characteristics due to extremely low radiation resistance and high conductor losses, rendering them unsuitable for practical RF communication without a complex matching network. This research applies a Genetic Algorithm implemented in MATLAB to optimize two critical design parameters: the loop radius and the wire radius (thickness). An analytical electromagnetic model was developed to compute radiation resistance, conductor loss resistance (accounting for skin effect and radiation efficiency. The objective function was designed to maximize efficiency by minimizing its negative value. Results from the GA were analysed using convergence plots and two-dimensional contour maps, revealing the efficiency distribution across the design space. The optimized antenna achieved a loop radius of 0.02458m and a wire radius of 0.0099m, leading to a dramatic improvement in radiation efficiency from 0.02% (traditional design) to 99.4%. Additionally, gain and bandwidth performance were significantly improved, making the antenna suitable for terrestrial RF applications. The study demonstrates that evolutionary optimization techniques like GA can overcome the inherent limitations of traditional small loop antennas, by intelligently navigating the design space, the Genetic Algorithm identified configurations that would be difficult to obtain through manual tuning. These findings highlight the practical potential of computational intelligence in modern antenna design particularly for compact efficient and broadband systems in wireless and communication technologies.