Signal Radiation Characteristics of Piezoelectric Antennas in Wireless Communications

This paper proposes an antenna parameter adjustment algorithm based on adaptive chaotic particle swarm optimization. The algorithm cleverly uses chaotic mapping to initialize particle positions, so that particles can be more evenly distributed in the search space, greatly enhancing the global search capability; by dynamically and adaptively adjusting the inertia weight and learning factor based on factors such as iteration process and particle fitness, the convergence speed and accuracy of the algorithm are effectively improved. The study carefully built an experimental model using professional simulation software, and set up a variety of simulation scenarios such as free space, indoor multipath, and outdoor complex terrain for comprehensive verification. The experimental results show that compared with traditional antennas, piezoelectric antennas have significant advantages in signal radiation patterns, with the main lobe width reduced by about 15% and the side lobe level reduced by about 8dB. In terms of radiation efficiency, after algorithm optimization, at a frequency of 2.4GHz, the radiation efficiency is greatly increased from the initial 60% to 85%, an increase of 41.7%. At the same time, the signal strength stability at the receiving end is significantly enhanced, and the signal fluctuation range is reduced by 30% in a multipath environment. This study has laid a solid theoretical and experimental foundation for the widespread application of piezoelectric antennas in the field of wireless communications.