Publication

Abstract : Patch antenna is being used widely in wearable and implantable devices due to its lightweight characteristics. Multi-band patch antenna designs are possible by incorporating professional naturally inspired fractal pattern generating methodologies. Automated Frequency Characteristics Analyzer (AFCA), Artificial Neural Network based Fractal Pattern Generator (AFPG) and Nitinol based Pattern Selector (NPS) functional modules are proposed in this work to design a Dual band Reconfigurable Fractal Antenna for Wearable Devices (DRFA). Producing a miniature fractal patch antenna to support famed 2.4 GHz and 5.2 GHz frequency bands with lesser than 20db return loss is the objective of this work. Numerous fractal patterns are generated with the help of AFPG and their frequency responses are analyzed by Ansys HFSS (High Frequency Structure Simulator) through AFCA module. The results are provided to the AFPG part to train the neural network with proper biasing updates. The fitness function is set to the dimension restriction of 3000 square μm with less than 20 return loss at commonly used 2.4 GHz and 5.2 GHz. The feed type and length of the patches are also fine-tuned by the proposed AFPG module.