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  • 标题:Joint Channel Estimation and Nonlinear Distortion Recovery Based on Compressed Sensing for OFDM Systems
  • 本地全文:下载
  • 作者:Li-Jun Ge ; Yi-Tai Cheng ; Bing-Rui Xiao
  • 期刊名称:Journal of Communications
  • 印刷版ISSN:1796-2021
  • 出版年度:2016
  • 卷号:11
  • 期号:1
  • 页码:15-22
  • DOI:10.12720/jcm.11.1.15-22
  • 语种:English
  • 出版社:ACADEMY PUBLISHER
  • 摘要:In order to solve the problems of high PAPR and channel estimation in OFDM systems, a new algorithm of joint channel estimation and Nonlinear Distortion (NLD) recovery based on compressed sensing is proposed for nonli nearly distorted OFDM systems, using the dual sparsity of channel and NLD. In quasi-static channel, the channel is estimated by adopting Golay complementary sequences to against NLD, and the NLD is estimated by using compressed sensing based on pectinate pilots. In time-varying channel, a scheme of pilot grouping and cascaded clipping is proposed. The pilots are divided into two groups. The first group, which is protected from NLD influence, is adopted to estimate the channel by compressed sensing, and the second group is used to estimate the NLD by compressed sensing as well, based on the estimated channel information. Simulation results show a good performance of the proposed algorithm without any priori information. And also advantages are brought for the system without any PAPR reduction algorithms or iterative operations.
  • 关键词:OFDM ; compressed sensing ; channel estimation ; nonlinear distortion
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