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Predistortion of quadrature amplitude modulation signals using Volterra series approximation

机译:使用Volterra级数逼近对正交幅度调制信号进行预失真

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摘要

Modern digital communication systems are being called upon to move ever increasing amounts of information over decreasingly available bandwidth. This requires that communication systems employ bandwidth-efficient modulation schemes to conserve bandwidth while moving the information at higher data rates. A major stumbling block to using higher order modulation schemes in long haul communication is the distortion caused by high power amplifiers. These high power amplifiers are required to amplify the signal power to a level that will allow distant receivers to correctly demodulate and decode the information. The distortion caused by the high power amplifiers can render a modulation scheme unusable due to the high symbol error rates which result from the extensive skewing of the modulation scheme's signal constellation. This thesis details a predistortion technique using Volterra series approximation techniques to model the inverse of the high power amplifier's distortion characteristics. A 64 Quadrature Amplitude Modulation (64-QAM) system incorporating a predistorter is used to demonstrate the ability to achieve acceptable bit error rates. The implementation of the inverse model and the communication system is performed in MATLAB. The results show the viability of predistortion of digital data to allow the higher order modulation schemes to be incorporated into communication schemes, increasing the overall data rate while conserving bandwidth.
机译:要求现代数字通信系统在越来越少的可用带宽上移动越来越多的信息。这要求通信系统采用带宽有效的调制方案来节省带宽,同时以更高的数据速率移动信息。在长距离通信中使用高阶调制方案的主要障碍是高功率放大器引起的失真。需要这些高功率放大器将信号功率放大到允许远处的接收器正确解调和解码信息的水平。由高功率放大器引起的失真会由于高符号错误率而导致调制方案无法使用,而高符号错误率是由于调制方案的信号星座图的大幅度倾斜而导致的。本文详细介绍了一种预失真技术,该技术使用Volterra级数逼近技术对高功率放大器的失真特性的反函数进行建模。结合了预失真器的64正交幅度调制(64-QAM)系统用于演示实现可接受的误码率的能力。逆模型和通信系统的实现是在MATLAB中执行的。结果显示了数字数据预失真的可行性,以允许将更高阶的调制方案并入通信方案,从而在节省带宽的同时提高了整体数据速率。

著录项

  • 作者

    Donovan Michael T.;

  • 作者单位
  • 年度 1996
  • 总页数
  • 原文格式 PDF
  • 正文语种 en_US
  • 中图分类

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