A fused Cuckoo Search Algorithm and African Vultures Optimization for optimising the patch of wearable microstrip patch antenna

Microstrip patch antennas (MPAs) are widely used in wireless body area networks (WBANs) due to their lightweight structure, low cost, and ease of integration with wearable systems. However, achieving optimal antenna performance in terms of impedance matching, bandwidth, and radiation efficiency requires precise geometric tuning, particularly for textile-based wearable applications. This work presents the design and optimization of a wearable textile microstrip patch antenna operating in the 2.3–2.45 GHz band. A hybrid AVCS-based optimization framework is employed to improve antenna performance by tuning key geometrical parameters, including patch dimensions, feed structure, ground plane size, and shape-defining elements. The optimization process is guided by a fitness function based on return loss and gain characteristics to ensure efficient impedance matching and stable radiation performance. The optimized antenna demonstrates significant improvement in electromagnetic characteristics, including enhanced return loss, increased bandwidth, and stable gain performance, while maintaining high radiation efficiency suitable for wearable biomedical applications. The results confirm that the proposed design methodology effectively enhances antenna performance and ensures reliable operation in the ISM band for WBAN communication systems.