Abstract
The antenna is essential for anyone who wishes to communicate with others in remote regions. The antenna acts as a transducer that converts electromagnetic into electric power and vice versa. Based on the mode of application, different types of antennas are used. One of the most used antenna types is MIMO, which stands for multiple-input and multiple outputs. In wireless MIMO, multiple antenna elements are connected on both the receiver and transmitter sides. The reviewed antennas are printed on various substrates, and simulation is carried out in the HFSS tool. Optimized MIMO antenna algorithms are implemented in the MATLAB tool. Optimization algorithms such as the Hybrid Jaya-grey wolf optimization algorithm (J-GWO), Particle swarm optimization algorithm (PSO), Quasi-newton optimization algorithm (QNO), Salp swarm optimization algorithm (SSO), Moth-flame optimization algorithm (MFO), Ant colony optimization algorithm (ACO), Social spider optimization algorithm (SSO), Sealion optimization algorithm (SLO), Genetic algorithm optimization (GA) and hybrid Differential evolution based naked mole-rat optimization algorithm (HDN), Invasive weed optimization algorithm (IWO) and Teaching–learning optimization algorithm (TLBO) are reviewed from various literature. Many recent research works are analyzed to provide an efficient idea for the researchers to implement new optimization techniques in future.
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Manage, P.S., Naik, U. & Rayar, V. Optimization Algorithms for MIMO Antennas: A Systematic Review. Wireless Pers Commun 131, 105–139 (2023). https://doi.org/10.1007/s11277-023-10420-5
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DOI: https://doi.org/10.1007/s11277-023-10420-5