AI Article Synopsis
- An automatic adaptive antenna impedance tuning algorithm called AQGA (Automatic Quantum Genetic Algorithm) is introduced, which uses quantum-inspired techniques for optimization.
- This algorithm specifically targets low-pass passive T-impedance matching LC-networks connecting RF transceivers to antennas, with results applicable from 1.4 to 5 GHz across various communication services.
- The AQGA exhibits significantly faster convergence times—averaging 75% to 49.2% faster than traditional genetic algorithms—making it suitable for real-time applications in RF systems.
Article Abstract
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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442656 | PMC |
| http://dx.doi.org/10.1038/s41598-020-71056-0 | DOI Listing |
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