针对DTMB-A系统的自适应峰均比降低算法
发布时间：2018-08-21 20:17
【摘要】：针对地面数字多媒体广播演进方案(DTMB-A)中由于采用了较大FFT长度而带来的高峰均比问题,提出一种基于动态星座图扩展的自适应峰均比降低算法。首先介绍了针对APSK调制方式的动态星座图扩展算法,明确了星座点可扩展区域的选择方式;随后基于峰值抵消信号推导了动态星座图扩展算法的最优时域系数;最后针对现有动态星座图扩展算法对初始限幅门限值敏感的问题,提出一种在迭代中自适应调整限幅门限值的方法。仿真结果表明:所提算法的降峰均比性能优于现有动态星座图扩展算法,同时在初始限幅门限值设置不理想的情况下具有较好的鲁棒性。
[Abstract]:An adaptive peak-to-average ratio (PAPR) reduction algorithm based on dynamic constellation expansion is proposed to solve the problem of peak-to-average ratio (PAPR) caused by large FFT length in terrestrial digital multimedia broadcasting evolution scheme (DTMB-A). Firstly, the dynamic constellation expansion algorithm for APSK modulation is introduced, and the selection method of the scalable region of constellation points is defined, then the optimal time-domain coefficients of the expansion algorithm are derived based on the peak cancellation signal. Finally, aiming at the sensitivity of the existing dynamic constellation expansion algorithms to the initial limiting threshold, an adaptive method for adjusting the limiting threshold in iteration is proposed. The simulation results show that the proposed algorithm is superior to the existing dynamic constellation expansion algorithm in peak-to-average ratio (PAPR) performance, and has good robustness when the initial limit threshold is not well set.
【作者单位】： 清华大学电子工程系 清华信息科学与技术国家实验室;数字电视国家工程实验室(北京);
【基金】：国家自然科学基金创新研究群体项目(61021001) 国家“八六三”高技术项目(2012AA011704)
【分类号】：TN941
本文编号：2196235
[Abstract]:An adaptive peak-to-average ratio (PAPR) reduction algorithm based on dynamic constellation expansion is proposed to solve the problem of peak-to-average ratio (PAPR) caused by large FFT length in terrestrial digital multimedia broadcasting evolution scheme (DTMB-A). Firstly, the dynamic constellation expansion algorithm for APSK modulation is introduced, and the selection method of the scalable region of constellation points is defined, then the optimal time-domain coefficients of the expansion algorithm are derived based on the peak cancellation signal. Finally, aiming at the sensitivity of the existing dynamic constellation expansion algorithms to the initial limiting threshold, an adaptive method for adjusting the limiting threshold in iteration is proposed. The simulation results show that the proposed algorithm is superior to the existing dynamic constellation expansion algorithm in peak-to-average ratio (PAPR) performance, and has good robustness when the initial limit threshold is not well set.
【作者单位】： 清华大学电子工程系 清华信息科学与技术国家实验室;数字电视国家工程实验室(北京);
【基金】：国家自然科学基金创新研究群体项目(61021001) 国家“八六三”高技术项目(2012AA011704)
【分类号】：TN941
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1 梁林峰;王军;宋健;;针对DTMB-A系统的自适应峰均比降低算法[J];清华大学学报(自然科学版);2014年04期
，本文编号：2196235
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