The application of aggressive space mapping algorithm in microstrip patch antennna design

Chen, Feng; Shi, Zhiwei; Deng, Xi; Song, Jingping; Liu, Yunlin

doi:10.1109/icmmt.2010.5525089

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Our methodology is based on the classical Broyden‐based input space mapping (SM) algorithm to efficiently optimize the return loss of the PIFA handset antenna under these considerations, exploiting a coarse model that is not only a structurally simplified version of the fine model but also fully neglects the operational environment. Unlike other antenna design optimization approaches based on SM , here the EM couplings of the antenna with the battery, handset case, and human head are considered in the fine model. The approach is in principle applicable to other environmental objects, such as the human hand, cell‐phone display, speaker, and so forth.…”

Section: Introductionmentioning

confidence: 93%

Space mapping optimization of handset antennas considering EM effects of mobile phone components and human body

Cervantes-González

Rayas‐Sánchez

López

et al. 2015

Int J RF and Microwave Comp Aid Eng

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To meet antenna design specifications under realistic conditions, electromagnetic coupling effects between the antenna and its environment must be considered. In this work, an efficient antenna design optimization methodology that considers the influence of the human head and main mobile handset components on the antenna performance is presented. The computational optimization time is dramatically reduced by exploiting a Broyden-based input space mapping (SM) algorithm. Both coarse and fine models required for the SM algorithm are based on the finite-element method and are implemented in the same simulator; simplifying the modeling process. However, our coarse model does not consider any object of the actual operational environment. In spite of that and other simplifications applied to the coarse model, the proposed optimization scheme is able to find a solution that meets the specifications in a realistic environment by performing an extremely small number of expensive fine model simulations. Our practical illustration opens up the feasibility of using this CAD methodology to optimize other RF devices that operate in close proximity to objects that affect its desired response, as it is the case for many wearable devices.

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Section: Introductionmentioning

confidence: 93%