High-Gain DGS-Based Patch Antenna Optimized Using Modified Leaf-in-Wind Optimization for Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), antenna design plays a vital role in reliable wireless communication between sensor nodes and the base station. Compared to other antennas, the microstrip patch antenna is widely preferred due to its compact structure and low profile. This work presents the development of a high-gain microstrip patch antenna specifically tailored for WSN applications. The proposed antenna incorporates a Defected Ground Structure (DGS) to enhance surface current distribution and to reduce mutual coupling. To further optimize antenna dimensions and electrical performance, a new metaheuristic optimization technique called Modified Leaf-in-Wind Optimization (MLiWO) is proposed. The algorithm enhances exploration and exploitation capabilities, enabling efficient searching of optimal geometric parameters. The antenna design is simulated and analyzed using an electromagnetic simulation tool. The results prove that the optimised antenna achieves a return loss of –38 dB at the target resonance frequency with excellent impedance matching. In addition, the antenna achieves a high peak gain of 8.51 dBi. The proposed method effectively combines DGS enhancements with intelligent optimization and provides a robust solution for next-generation WSN antenna design. The fabrication results show the exact match between measured and simulation results.