Metaheuristic (Ant Colony Optimization) Algorithm-Based Optimization of a Circular Shaped Patch Antenna for Medical Purposes

• Published in: SN computer science Vol. 5; no. 7; p. 918
• Main Authors: Mahesh, D. S., Naveen, K. B.
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.10.2024; Springer Nature B.V
• Subjects: Advances in Computational Approaches for Image Processing; Algorithms; Anechoic chambers; Ant colony optimization; Antenna design; Antenna radiation patterns; Antennas; Body temperature; Cloud Applications and Network Security; Coaxial cables; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Data Structures and Information Theory; Design optimization; Directivity; Flame retardants; Food; Heart rate; Heuristic; Heuristic methods; Information Systems and Communication Service; Microcontrollers; Modules; Network analysers; Optimization algorithms; Original Research; Parameters; Patch antennas; Pattern analysis; Pattern Recognition and Graphics; Pheromones; Reflectance; Sensors; Shape optimization; Software; Software Engineering/Programming and Operating Systems; Software upgrading; Substrates; Vision; Voltage standing wave ratios; Wave reflection; Wireless Networks; VSWR; Return loss; ACO algorithm
• ISSN: 2661-8907; 2662-995X; 2661-8907
• DOI: 10.1007/s42979-024-03273-7

This paper presents the design, simulation, optimization, fabrication and testing of a circular shape based antenna, ant colony optimization (ACO) algorithm was chosen for antenna optimization. The antenna considered here was fed by a 1.59 mm diameter coaxial cable, the location of feeding and the radius of circular shape was varied by ant colony optimization algorithm (ACO). Finding a set of settings that would enhance the antenna's performance was the optimization's goal. We have made use of MATLAB software to implement ACO algorithm. The Ansys HFSS software which was used to design antenna allows MATLAB to be interfaced with it for optimization purpose. The parameters considered were return loss (reflection coefficient S 11 ) and the voltage standing wave ratio (VSWR). The ACO yielded a design with return loss (S 11 ) of − 25.85 dB and VSWR of 1.24 at 2.48 GHz. The entire antenna dimensions will be approximately (5 cm × 5 cm). The substrate used is FR4 (flame retardant) epoxy. There was strong good agreement between the measurements from the antenna's (fabrication) manufacturing and simulation for the operational frequencies and desirable performance in gain, bandwidth and VSWR (voltage standing wave ratio) parameters. The VSWR achieved values was lower than 1.4 for the frequencies used. Additionally, the simulations portray a broad radiation pattern and shows good gain and directivity. The antenna which was fabricated was tested using Anechoic chamber and network analyser. This tested antenna was used in wearable health care application due to its small size. At the transmitter side we used temperature and pulse reading sensors to collect physiological information like body temperature and heart rate from the patient, these sensors were connected to Arduino microcontroller then to transmit this physiological information, NRF24L01 transreceiver module along with our fabricated ACO optimised antenna was used, which is connected to Arduino microcontroller. At the receiver side we received the physiological information using, NRF24L01 transreceiver module along with our fabricated ACO optimised antenna connected to Arduino microcontroller. The RLC equivalent model of the ACO optimized circular shape based antenna was simulated in advanced design system (ADS) software which allows simulation of RF components and provides return loss parameter (S 11 ) which was − 27.96 dB at 2.44 GHz.