模拟频谱再生和数据包大小的影响

P. Rudge, K. Gard, H. Gutierrez, M. Steer, R. Miles
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引用次数: 1

摘要

传统的非线性以双音互调失真为特征。然而,对于数字无线电来说,建立光谱再生模型更为重要。目前,人们对无线通信微波功率放大器的频谱再生建模非常感兴趣。预测频谱再生的能力,或者更具体地说,预测相邻通道功率比(ACPR)的能力,对实现可接受的线性性能的设计有直接影响。由于在线性度和效率之间存在权衡,因此回退量会显著影响功率放大器的效率,因此,例如,移动电话的通话时间。许多无线通信系统,如GSM,使用时域多址(TDMA)方案,以突发(或分组)方式发送信号。使用一个行为模型,该模型可以在给定输入信号统计估计的情况下预测ACPR,结果表明,ACPR高度依赖于输入信号统计,并依赖于数据包的长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling spectral regrowth and the effect of packet size
Traditionally nonlinearity has been characterized by two-tone intermodulation distortion. However, for digital radio, modelling spectral regrowth is much more important. There is currently much interest in modelling spectral regrowth in microwave power amplifiers for wireless communications. The ability to predict spectral regrowth or, more specifically, adjacent channel power ratio (ACPR), has a direct impact on design to achieve acceptable linearity performance. Since there is a trade-off between linearity and efficiency the amount of back-off can significantly affect power amplifier efficiency and thus, for example, talk-time for a mobile handset. Many wireless communications systems, such as GSM, use time domain multiple access (TDMA) schemes, sending signals in bursts (or packets). Using a behavioural model which can predict ACPR given an estimate of input signal statistics, it is shown that ACPR is highly dependent on the input signal statistics and it is dependent on the length of the packet.
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