A novel metamaterial-based circular patch multi-input multi-output (MIMO) antenna is designed with a 'C'-shaped defected ground structure for high isolation. A 4 × 4 mm 2 unit cell for a ring resonator has been designed and exhibited double negative material (DNG) properties from 1.0 to 2.92 GHz and 13.68 to 17.67 GHz and Mu negative material (MNG) from 4.70 to 13.67 GHz. The proposed antenna structure is designed by embedding the ring resonator-based meta-structure to a circular patch antenna and fabricated with dimensions 0.245λ 0 × 0.409λ 0 (15 × 25 mm 2 ). The proposed antenna operating at 8.50 to 14.23 GHz for X and lower Ku bands is used in the Unmanned Arial Vehicle (UAV's) applications. The spacing between elements is 0.088λ 0 (5.4 mm) on an FR4 epoxy substrate, and the 'C'-shaped structure on the back of the antenna improves the isolation of more than 24 dB in the operating band. Distance between the antenna elements plays a crucial role, and parameters affected by this are optimized by introducing machine learning. For future predictions, a linear regression model was created to optimize the parameters' linear dependencies like isolation and return loss on the distance between the antenna elements. The radiation efficiency and gain of the antenna are enhanced by 92% and 6.02 dB at 13.22 GHz, respectively. The MIMO antenna's simulated results of diversity and other parameters are in the acceptable range with the measured results used for X-band radar applications. The proposed decoupling technique is simple to understand and implement.
A new circular patch antenna with a novel metamaterial structure that achieves high bandwidth and positive gain across the operating band. The proposed antenna was Designed by incorporating three split ring resonators into the patch and fabricating it with 15 ×10 ×1.6 mm3. The use of a metamaterial structure with negative permittivity and permeability reduced mutual coupling in a wideband antenna. The designed antenna shows the isotropic nature at 9.71 GHz in the operating band from 8.80 to 12.89 GHz for X band applications specifically for detecting objects using radars. The optimetrics technique analyzed impedance matching with a good return loss of -30 dB. In comparison to previous works, miniaturization achieved up to 81.94%. The efficiency of 95.6% and isotropic pattern were also achieved at 9.71 GHz using HFSS020R2.
Radars are at the core of numerous real-world applications in healthcare monitoring and autonomous driving due to the rapid expansion of the communication system. MIMO (Multiple-Input Multiple-Output) antennas are an essential component of radar systems. The effect of mutual coupling degraded the performance of these antennas. This article comprehensively reviewed the metamaterial-based decoupling technique for antenna design and provided a comparison with other decoupling techniques. The occurrence and variety of current information, the sophistication of processing, and the low cost of data storage all contribute to the increased interest in using machine learning to find optimal solutions in a variety of fields. This article introduces and investigates machine learning applications in antenna design. This paper discusses implementing different machine learning models to optimize primary antenna performance, reduce mutual coupling, and increase the bandwidth. Various numerical results from synthetically generated and experimental datasets and about two specific applications are presented as a conclusion. These allow readers to evaluate the effectiveness of particular methods and compare them in terms of precision and computational effort.
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