...
首页> 外文期刊>International journal of RF and microwave computer-aided engineering >An Adaptive Predistorter Using Modified Neural Networks Combined with a Fuzzy Controller for Nonlinear Power Amplifiers
【24h】

An Adaptive Predistorter Using Modified Neural Networks Combined with a Fuzzy Controller for Nonlinear Power Amplifiers

机译:改进的神经网络与模糊控制器相结合的自适应预失真器用于非线性功率放大器

获取原文
获取原文并翻译 | 示例
           

摘要

In digital radio systems, high data transmission rates require the use of spectrally efficient linear modulation techniques: however, these techniques are generally sensitive to nonlinearity caused by the high-power amplifier (HPA) employed in transmitter systems. The nonlinearity of HPA is potentially responsible for spectral spreading, adjacent channel interference (ACI), and degradation of bit-error rates (BERs). This article proposes an adaptive predistortion scheme to compensate for the HPA's nonlinearity by combining adaptive structure-varying neural networks and a fuzzy controller. Simulations show that this predistortion scheme can very effectively prevent the warping of the signal constellations, thus reducing the system's BER and learning time.
机译:在数字无线电系统中,高数据传输速率要求使用频谱有效的线性调制技术:但是,这些技术通常对发射机系统中使用的高功率放大器(HPA)引起的非线性敏感。 HPA的非线性可能导致频谱扩展,相邻信道干扰(ACI)和误码率(BER)下降。本文提出了一种自适应预失真方案,通过结合自适应结构变化神经网络和模糊控制器来补偿HPA的非线性。仿真表明,这种预失真方案可以非常有效地防止信号星座变形,从而减少了系统的BER和学习时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号