RETRACTED ARTICLE: Design and Optimization of Wearable Microstrip Patch Antenna using Hybrid Fuzzy Flamingo Swarm Optimization Algorithm for RF Energy Harvesting

Abstract

The wearable antenna design is popular in the modern world due to communication and surveillance. When designing these antennas, different constraints need to be taken into account such as flexibility, bandwidth, cost, frequency band, and data transmission rate. This paper presents a hybrid fuzzy flamingo swarm optimization (HFFSO) algorithm to optimize the n-shaped textile-based microstrip patch antenna (MPA) to operate in multiband frequencies. The antenna optimization problem is solved in this paper using an HFFSO algorithm to improve the bandwidth of LTE and 5G applications. The flamingo swarm optimization (FSO) algorithm is integrated with the fuzzy decision-making strategy to enhance the exploration phase and prevent the local optima trapping. The personal computer-aided antenna design (PCAAD) simulation software is used to create the antenna developed by the HFFSO algorithm. The HFFSO algorithm generates three optimal frequency bands (790–860 MHz, 1.6–2.3 GHz, and 3.3–3.8 GHz) for supporting modern telecommunication standards. Polyimide ultra-thin copper laminates are utilized in fabrication to provide greater flexibility while lowering dielectric losses. The high-frequency structure simulator (HFSS) software is used to design the various types of substrate materials used in the antenna. The polyethylene substrate used in this paper is said to be effective and maintains an operation frequency of 2.4 GHz. The performance of the HFFSO algorithm is evaluated via four CEC 2005 benchmark functions, reflection coefficient, gain, optimal fitness value in terms of a different frequency band, rectifier efficiency, and bandwidth. The experimental results achieved show that the proposed antenna is suitable for high-speed 5G applications.