期刊文献+

基于压缩感知重建去噪后的LDPC译码算法 被引量:1

LDPC decoding algorithm based on compressive sensing reconstruction for denoise
原文传递
导出
摘要 针对LDPC译码前的噪声问题,提出一种基于压缩感知重建去噪后的LDPC译码算法.首先,在接收端使用CS算法对系统的接收信号进行观测,恢复,消除信道传输过程中的噪声信息;然后,将恢复信号直接作为接收信号送入LDPC的译码器.仿真计算证明,这种改进的算法能有效减少噪声影响,降低LDPC的误码率,提高系统译码性能,在码长为512时,误码率可降低到10-5,并且受稀疏度,传输速率和CS重构算法影响.对比4种CS重构的贪婪算法,SP算法得到的效果较好. According to noise problems before LDPC decoding, we propose LDPC decoding algorithm, which based on compressive sensing reconstruction for denoise.First of all ,at the receiving end ,we use CS algorithm observing and recovering the received signal of system, to eliminate the noise in the process of information channel transmission, and then we use the restoring signal as a received signal directly into the LDPC decoder.The simulation calculation shows that the improved algorithm can effectively reduce the effects of noise, reduce the LDPC error rate and improve the decoding performance of the system,when the code length is 512,the error rate can be reduced to 10-5.And the error rate is influenced by the sparsity, the transmission rate and CS reconstruction algorithm.Comparing to four kinds of CS greedy algorithm reconstruetion.SP alzorithms get better.
出处 《云南大学学报(自然科学版)》 CAS CSCD 北大核心 2015年第5期680-686,共7页 Journal of Yunnan University(Natural Sciences Edition)
基金 吉林省教育厅"十二五"项目(120150047) 长春工程学院青年基金(320140001)
关键词 低密度奇偶校验(LDPC)码 压缩感知 译码 噪声 LDPC code ( Low Density Parity Check code) compressive sensing decoding noise
  • 相关文献

参考文献21

  • 1DONOHO D.Compressed sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306.
  • 2李树涛,魏丹.压缩传感综述[J].自动化学报,2009,35(11):1369-1377. 被引量:205
  • 3TSAIG Y,DONOHO D L.Extensions of compressed sensing[J].Signal Processing,2006,86(3):547-571.
  • 4ZHU B,HUANG D F,NORDHOLM S.Enhanced verification-based decoding for packet-based LDPC codes[J].IEEE Commun Lett,2008,12(2):136-138.
  • 5RYAN W E.An introduction to LDPC codes,in CRC handbook for coding and signal[M].CRC Press,2002.
  • 6HU X Y,ELEFTHERIOU E,ARNOLD D M.et al.Efficient implementations of the sum-product algorithm for decoding LDPC codes[J].GLOBECOM IEEE,2001.DoI:10.1109/GLOCOM.2001.965575.
  • 7MAO Y Y,BANIHASHEMI A H.Decoding low-density parity-check codes with probabilistic scheduling[J].IEEE Communications Letters,2001,5(10):414-416.
  • 8MORELOS-ZARAGOZA R H.纠错编码的艺术[M].张立军译.北京:北京交通大学出版社,2007.
  • 9ZARRINKHAT P,BANIHASHEMI A H.Hybrid hard-decision iterative decoding of regular low-density parity-check codes[J].IEEE Communications Letters,2004,8(4):250-252.
  • 10MACKAY D J C,NEAL R M.Near Shannon limit performance of low-density parity-check codes[J].Electron Lett Aug,1996,32:1645-1646.

二级参考文献77

  • 1Vinje W E, Gallant J L. Sparse coding and decorrelation in primary visual cortex during natural vision. Science, 2000, 287(5456): 1273-1276
  • 2Olshausen B A, Field D J. Emergency of simple-cell receptive field properties by learning a sparse coding for natural images. Nature, 1996, 381(6583): 607-609
  • 3Olshausen B A, Field D J. Sparse coding with an overcomplete basis set: a strategy employed by VI? Visual Research, 1997, 37(33): 3311-3325
  • 4Mallat S G, Zhang Z F. Matching pursuits with timefrequency dictionaries. IEEE Transactions on Signal Processing, 1993, 41(12): 3397-3415
  • 5Davis G M, Mallat S G, Zhang Z F. Adaptive time-frequency decompositions. SPIE Journal of Optical Engineering, 1994, 33(7): 2183-2191
  • 6Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit. SIAM Journal of Scientific Computing, 1999, 20(1): 33-61
  • 7Gorodnitsky I F, Rao B D. Sparse signal reconstruction from limited data using FOCUSS: are-weighted minimum norm algorithm. IEEE Transactions on Signal Processing, 1997, 45(3): 600-616
  • 8Figueiredo M A T, Nowak R D, Wright S J. Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(4): 586-598
  • 9Mancera L, Portilla J. Lo-norm-based sparse representation through alternate projections. In: Proceedings of IEEE International Conference on Image Processing. Washington D. C., USA: IEEE, 2006. 2089-2092
  • 10Bergeau F, Malt S. Match pursuit of images. In: Proceedings of the 1995 International Conference on Image Processing. Washington D. C., USA: IEEE, 1995. 53

共引文献240

同被引文献3

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部