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Research on the Intelligent Signal Channel Sensing Based ICI Elimination Algorithm of the OFDM System

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Abstract

This paper investigated the channel estimation based inter-carrier interference (ICI) cancellation algorithm elimination of the orthogonal frequency division multiplexing (OFDM) system. Compared to the traditional technologies, this new algorithm would be processed as part of ICI as noise, and to reduce the effects of interference between the carrier frequency offset by simultaneous judgment and impulse channel frequency response (CFR). At the same time, the algorithm considered the CFR estimate of the frequency-offset effect, the closest to the actual frequency offset value, thereby reducing the ICI. To simplify the calculation, the frequency-offset hypothesis was determined utilizing a binary search method, and matrix interference was simplified. Simulation results demonstrated the effectiveness and superiority of the algorithm.

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References

  1. Sun XD, Yu Q, Yuan HT (2003) Key technology of OFDM implementation [J]. Comput Electron 25(1):65–68

    Google Scholar 

  2. Armstrong J (1999) Analysis of new and existing methods of reducing intercarrier intercarrier interference due to carrier frequency offset in OFDM[J]. IEEE Trans Commun 47(3):365–369

    Article  Google Scholar 

  3. Russell M, Stuber GL (1995) Interchannel interference analysis of OFDM in a mobileenvironment[J]. IEEE Vehic Techn Conf 15(2):820–824

    Google Scholar 

  4. Cheng LB (2008) An improved LMMSE channel estimation method and its performance analysis [J]. Acta Electron Sin 36(9):1782–1785

    Google Scholar 

  5. Krishnan KV, Sajith RM, Khara S (2015) Dynamic resource allocation in OFDM based cognitive radio system considering primary user QoS and secondary user proportional constraints [J]. J Commun Technol Electron 60(11):1269–1275

    Article  Google Scholar 

  6. Azhar AH, Tran T, O’Brien D (2013) A gigabit/s indoor wireless transmission using MIMO-OFDM visible-light communications [J]. IEEE Photon Soc 25(2):171–174

    Article  Google Scholar 

  7. Li Y, Stuber G (2006) Orthogonal frequency division multi –plexing for wireless communications [M]. Springer Press, New York

    Book  Google Scholar 

  8. Ingle, VK, Proakis, JG. (2016) Digital signal processing using MATLAB [M]. Cengage Learning

  9. Gupta V, Mohapatra D, Raghunathan A, Roy K (2013) Low-power digital signal processing using approximate adders [J]. IEEE Counc Electron Des Autom 32(1):124–137

    Google Scholar 

  10. Rabiner, LR, Gold, B. (1975) Theory and application of digital signal processing [M].Englewood Cliffs

  11. Ahmed, N, Rao, KR. (2012) Orthogonal transforms for digital signal processing [M]. Springer Science & Business Media

  12. Rabha WI (2015) Upper bound of partial sums determined by matrix theory [J]. Turkish J Anal Number Theory 3(6):149–153

    Google Scholar 

  13. Xu Z, Hu C, Mei L (2016) Video structured description technology based intelligence analysis of surveillance videos for public security applications. Multimedia Tools Appl 75(19):12155–12172

    Article  Google Scholar 

  14. Xu Z, Mei L, Hu C, Liu Y (2016) The big data analytics and applications of the surveillance system using video structured description technology. Clust Comput 19(3):1283–1292

    Article  Google Scholar 

  15. Xu Z, Wei X, Liu Y, Mei L, Hu C, Choo KR, Zhu Y, Sugumaran V (2016) Building the search pattern of web users using conceptual semantic space model. Int J Web Grid Serv (IJWGS) 12(3):328–347

    Article  Google Scholar 

  16. Zhou Q (2016) Research on heterogeneous data integration model of group enterprise based on cluster computing. Clust Comput 19(3):1275–1282

    Article  Google Scholar 

  17. Xu Z, Zhang H, Hu C, Mei L, Xuan J, Choo KR, Sugumaran V, Zhu Y (2016) Building knowledge base of urban emergency events based on crowdsourcing of social media. Concurr Comput: Pract Experience 28(15):4038–4052

    Article  Google Scholar 

  18. Xu Z, Zhang H, Sugumaran V, Choo KR, Mei L, Zhu Y (2016) Participatory sensing-based semantic and spatial analysis of urban emergency events using mobile social media. EURASIP J Wireless Comm Netw 2016:44

    Article  Google Scholar 

  19. Zhou Q, Luo J (2015) Artificial neural network based grid computing of E-government scheduling for emergency management. Comput Syst Sci Eng 30(5):327–335

    Google Scholar 

  20. Nakamura J (2016) Image sensors and signal processing for digital still cameras [M]. CRC press

  21. Xi XP, Zhang C (2009) Study on ICI cancellation algorithms for mobile OFDM systems [J]. J Electron Inf Technol 31(3):25–28

    MathSciNet  Google Scholar 

  22. Shen J (2006) On inter-cell interference mitigation for OFDM systems [J]. Telecommun Sci 7(1):10–13

    Google Scholar 

Download references

Acknowledgements

This work was supported in part by Jiangsu Policy Guidance (Industry University Research) Project (Grant no. BY2016030-16), Major horizontal project (Grant no. KYH15052), Talent Introduction Project (Grant no. KYY15016) and Jiangsu Planned Projects for Postdoctoral Research Funds (Grant no. 1601138B).

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Correspondence to Enxing Zheng.

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Liu, R., Zheng, E. Research on the Intelligent Signal Channel Sensing Based ICI Elimination Algorithm of the OFDM System. Mobile Netw Appl 22, 255–266 (2017). https://doi.org/10.1007/s11036-016-0792-7

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  • DOI: https://doi.org/10.1007/s11036-016-0792-7

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