PAPR reduction of OFDM signals using radial basis function neural networks

被引：0
|
作者：
Sohn, Insoo [1 ]
Shin, Jaeho [1 ]
机构：
[1] Dongguk Univ, Dept Elect Engn, 3-26 Pil Dong, Seoul 100715, South Korea
来源：
2006 10TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY, VOLS 1 AND 2, PROCEEDINGS | 2006年
关键词：
OFDM; PAPR; RBF;
D O I：
暂无
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In this paper we investigate a novel peak-to-average power ratio (PAPR) reduction method based on radial basis function network (RBFN). The RBFN can be regarded as a method of adaptive curve-fitting interpolator and is used to generate optimum mapping pattern to reduce the PAPR in this paper. Our simulation results show that our proposed method has significant performance advantages with low computational complexity compared to the conventional methods.
引用
收藏
页码：1170 / +
页数：4
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