| 摘要(英) |
Radio Frequency (RF) charging has a larger charging area than other wireless charging solutions, and it’s less susceptible to the shading of obstacles. The combination of transmitters (or chargers) and receivers (or harvesters) is utilized to perform RF charging. A transmitter, as the energy supplier, emits radio waves to charge a receiver Based on an antenna array, the beamforming technique adjust the amplitude and phase of every antenna in the array to form radio wave beams. The direction of beams can be adjusted, and the transmission distance can be extended so that the effective charging area can cover specific positions. Beamforming produces main lobes in the target direction, but produces side lobes in non-target directions, leading to energy waste. This study proposes an evolutionary algorithm, called Evolutionary Beamforming Optimization (EBO), to optimize the transmission amplitude of every antenna in an antenna array for trying to maximize the strength of the main lobe and to minimize the strength of the peak side lobe. EBO assumes an antenna array consisting of 12 omnidirectional antennas forming the uniform circular array (UCA) with a radius of λ. With the UCA, beamforming can produce nearly identical beam patterns for any target directions. This study also proposes EBO-Reseeding (EBO-R) to further improve EBO. The basic concept of EBO-R is reseeding, which randomly generates new individuals to replace the worst ones in the population in every generation. Reseeding does not increase the population size and endows EBO-R has better capability to explore possible individuals to achieve better results, convergence speeds, and stability than EBO. This study performs simulation experiments to compare EBO, EBO-R and one related evolutionary algorithm, namely PSOGSA-E. The simulation results show that EBO-R has the best performance, and EBO is worse than EBO-R and PSOGSA-E. However, EBO has the shortest execution time. |
| 參考文獻 |
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