Falcone Lanas, Francisco

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https://academica-e.unavarra.es/handle/2454/48998

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Falcone Lanas

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Francisco

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Ingeniería Eléctrica, Electrónica y de Comunicación

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ISC. Institute of Smart Cities

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0000-0002-4911-9753

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88622

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2774

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Author: Virdee, Bal S. × Subject: Algorithms ×

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    PublicationOpen Access
    Improved adaptive impedance matching for RF front-end systems of wireless transceivers
    (Nature Research, 2020) Alibakhshikenari, Mohammad; Virdee, Bal S.; Shukla, Panchamkumar; See, Chan H.; Falcone Lanas, Francisco; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
    In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a low-pass passive T-impedance matching LC-network inserted between an RF transceiver and its antenna. Results of the AQGA tuning method are presented for applications across 1.4 to 5 GHz (satellite services, LTE networks, radar systems, and WiFi bands). Compared to existing genetic algorithm-based tuning techniques the proposed algorithm converges much faster to provide a solution. At 1.4, 2.3, 3.4, 4.0, and 5.0 GHz bands the proposed AQGA is on average 75%, 49.2%, 64.9%, 54.7%, and 52.5% faster than conventional genetic algorithms, respectively. The results reveal the proposed AQGA is feasible for real-time application in RF-front-end systems.