With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, ne...With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide larger bandwidth and at the same time small dimensions. Although the gain in bandwidth performances of an antenna are directly related to its dimensions in relation to the wavelength, the aim is to keep the overall size of the antenna constant and from there, find the geometry and structure that give the best performance. The design and bandwidth optimization of a Planar Inverted-F Antenna (PIFA) were introduced in order to achieve a larger bandwidth in the 2 GHz band, using two optimization techniques based upon genetic algorithms (GA), namely the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). During the optimization process, the different PIFA models were evaluated using the finite-difference time domain (FDTD) method-a technique belonging to the general class of differential time domain numerical modeling methods.展开更多
In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary...In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point crossoveroperation.Finally, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.展开更多
文摘With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide larger bandwidth and at the same time small dimensions. Although the gain in bandwidth performances of an antenna are directly related to its dimensions in relation to the wavelength, the aim is to keep the overall size of the antenna constant and from there, find the geometry and structure that give the best performance. The design and bandwidth optimization of a Planar Inverted-F Antenna (PIFA) were introduced in order to achieve a larger bandwidth in the 2 GHz band, using two optimization techniques based upon genetic algorithms (GA), namely the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). During the optimization process, the different PIFA models were evaluated using the finite-difference time domain (FDTD) method-a technique belonging to the general class of differential time domain numerical modeling methods.
文摘In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point crossoveroperation.Finally, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.
