Adaptive impedance matching using quantum genetic algorithm
来源期刊:中南大学学报(英文版)2013年第4期
论文作者:TAN Yang-hong(谭阳红) CHEN Sai-hua(陈赛华) ZHANG Gen-miao(张根苗) XIONG Zhi-ting(熊智挺)
文章页码:977 - 981
Key words:impedance matching; conventional genetic algorithm; quantum genetic algorithm
Abstract: An adaptive technique adopting quantum genetic algorithm (QGA) for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is also given, which shows that the QGA tuning algorithm is much faster. Moreover, the proposed method can be useful for software defined radio systems using a single antenna for multiple mobile and wireless bands.
TAN Yang-hong(谭阳红), CHEN Sai-hua(陈赛华), ZHANG Gen-miao(张根苗), XIONG Zhi-ting(熊智挺)
(College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)
Abstract:An adaptive technique adopting quantum genetic algorithm (QGA) for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is also given, which shows that the QGA tuning algorithm is much faster. Moreover, the proposed method can be useful for software defined radio systems using a single antenna for multiple mobile and wireless bands.
Key words:impedance matching; conventional genetic algorithm; quantum genetic algorithm