基于粒子群算法的自适应天线阵列性能优化

Aseel abdul-karim Qasim, A. Sallomi
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引用次数: 3

摘要

智能天线是第四代(4G)和其他未来蜂窝无线通信系统中有前途的技术之一,因为它能够通过使用分配的射频频谱提供高容量和覆盖范围。讨论了粒子群优化算法在线性天线阵自适应方向图合成中的应用潜力。通过考虑均匀和非均匀间隔线性阵列,验证了粒子群算法在区分期望信号和干扰信号方面的有效性。PSO用于优化阵列元素之间的间距,使其达到最大指向性。仿真结果表明,采用粒子群算法可以在指向性、旁瓣电平降低和HPBW等方面提高智能系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimisation of Adaptive Antenna Array Performance Using Particle Swarm Algorithm
Smart antenna represents one of the promising technology in the Fourth Generation (4G) and other future cellular wireless communication systems due to its capabilities to provide high capacity and coverage with the use of the allocated RF spectrum. This paper discusses, the potential of Particle Swarm Optimization (PSO) algorithm in adaptive pattern synthesis of the linear antenna array systems. The validity of the PSO algorithm in distinguishing between the desired signal and interferers is tested through considering uniform and non-uniform spaced linear array. The PSO is used to optimise the interspace between array elements at which maximum directivity is achieved. The simulations confirmed that smart system performance improvement in term of directivity, sidelobe level reduction and HPBW could be achieved through the use of PSO algorithm.
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