基于广义贝塞尔多项式的粒子群优化超宽带系统高斯脉冲设计

V. Chutchavong, T. Anuwongpinit, B. Purahong, T. Archevapanich, K. Janchitrapongvej
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摘要

超宽带系统以极短的脉冲和巨大的带宽运行,为数据传输提供高数据速率。在设计UWB脉冲时,考虑脉冲形状是非常必要的,所设计的脉冲的频谱发射掩模应满足FCC在3.1 GHz ~ 10.6 GHz频率范围内的频谱掩模要求。传统的超宽带脉冲设计是基于高斯导数的。然而,频谱不满足FCC频谱掩模要求。本文利用广义贝塞尔多项式的数学特性设计高斯脉冲。将高斯脉冲导数与权系数优化与粒子群优化相结合,可以提高脉冲的频谱效率。粒子群优化算法是一种受动物行为启发的基于群体的优化算法。将粒子群算法应用于广义贝塞尔多项式传递函数以获得最佳权系数,并对其权向量进行优化,设计出超过FCC频谱掩模的脉冲。在MATLAB软件中发现,广义贝塞尔多项式可以用组合方法和粒子群算法逼近所提出的脉冲。频谱效率提高到89.30%,频谱更接近FCC频谱掩模要求。与以往的工作相比,证实了光谱效率的提高。
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Optimized Gaussian Pulse Design for UWB System Using Particle Swarm Optimization Based-on Generalized Bessel Polynomials
The ultrawideband system operates a very short pulse with enormous bandwidth to provide high data rates for data transmission. To design the UWB pulse, considering the pulse shape is very necessary, and a spectral emission mask of the designed pulse should meet the FCC spectral mask requirement between frequency range 3.1 GHz to 10.6 GHz. The traditional UWB pulse design is based on the Gaussian derivative. However, the frequency spectrum is not satisfied the FCC spectral mask requirement. In this study, the Gaussian pulse can be designed from the mathematical characteristic of the generalized Bessel polynomial. The spectral efficiency of the proposed pulse can be improved by the combination of the derivative of Gaussian pulse with a weight coefficient optimization with particle swarm optimization (PSO). PSO is a population-based optimization algorithm inspired by animal behavior. PSO is applied with generalized Bessel polynomial transfer function to gain the best weight coefficient, we proposed to optimize its weight vector to design a pulse that exceeds to FCC spectral mask. The results were found in MATLAB software show that generalized Bessel polynomials can approximate the proposed pulse with combination method and PSO. The spectral efficiency is improved to 89.30% and the spectrum is greater close to the FCC spectral mask requirement. To confirm an improved spectral efficiency compared to the previous works.
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