ArticleSensors (Basel, Switzerland)2023
Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 41 citations in OpenAlex.
- Surrogate-Based EM Design of RF and Microwave Components: A Systematic Review of Workflow Roles, Inverse Design, Multifidelity, and Active Learning.Sensors (Basel, Switzerland) · 2026Review
- Implementation of a compact diplexer based on a modified T-shaped step-impedance resonator (MTSIR) for 5G networks.Scientific reports · 2025Article
- ANN-Assisted Beampattern Optimization of Semi-Coprime Array for Beam-Steering Applications.Sensors (Basel, Switzerland) · 2024Article
- Design of a miniaturized 90-degree quadrature hybrid coupler with harmonic suppression ability using π-shaped lumped elements.Scientific reports · 2024Article
- Reliability Evaluation Method for Array Antenna Considering Performance Changes.Sensors (Basel, Switzerland) · 2024Article
- Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2024Article
- A Four Element Stringray-Shaped MIMO Antenna System for UWB Applications.Micromachines · 2023Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 5 countries.
Funding
Abstract
This paper presents a novel approach to reducing undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two standard patch antenna cells with 0.07λ edge-to-edge distance were designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator was applied between the antennas to suppress their mutual coupling. For the first time, the optimum values of the resonator geometry parameters were obtained using the proposed inverse artificial neural network (ANN) model, constructed from the sampled EM-simulation data of the system, and trained using the particle swarm optimization (PSO) algorithm. The inverse ANN surrogate directly yields the optimum resonator dimensions based on the target values of its S-parameters being the input parameters of the model. The involvement of surrogate modeling also contributes to the acceleration of the design process, as the array does not need to undergo direct EM-driven optimization. The obtained results indicate a remarkable cancellation of the surface currents between two antennas at their operating frequency, which translates into isolation as high as -46.2 dB at 2.45 GHz, corresponding to over 37 dB improvement as compared to the conventional setup.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.