Abstract
To suppress the mutual coupling between closely-spaced patches, we propose a two-step decoupling design approach for a microstrip antenna array with the dimensions of 44.9 × 30.495 mm2. The first step is designing a decoupling unit on the basis of waveguided complementary split-ring resonators (WCSRRs) to improve isolation. The second step is presenting an optimization method by using a fully connected neural network (FCNN) to enhance design efficiency. By inserting WCSRRs structure between two patches with the edge-to-edge distance of 0.24λ0 (port-to-port distance with 0.66λ0), where λ0 is the wavelength of free space at a resonant frequency of 9 GHz, the mutual coupling can be reduced to −29.38 dB, which is confirmed by the EM simulation. We use the simulation results of the array geometries and EM performances to train FCNN at first and then use the trained FCNN to predict the array geometric parameters for the optimal EM response when the edge-to-edge distance between patches is further reduced to 0.21λ0 and 0.18λ0 (port-to-port distance reduced to 0.60λ0 and 0.56λ0). The measured isolation of the predicted microstrip antenna array is increased to 41.05 dB and 52.33 dB, respectively. Compared to the EM simulation, our FCNN approach has a higher accuracy and lower computational complexity. Therefore, the proposed array predicted by FCNN has a better decoupling performance. All the simulated and predicted results are validated via the measurement to demonstrate the effectiveness of our design scheme. The advantages of our work include the good decoupling performance of the proposed WCSRRs and the convenient optimization of the FCNN from physical response to optimal antenna array geometry design.
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