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A Variable Window Code-Aided Algorithm for Interference Suppression in DSSS Systems

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This study investigates a variable window code-aided (VWCA) algorithm for narrowband interference (NBI) suppression. The original code-aided technique, which simultaneously suppresses NBI and multiple access interference in direct-sequence code division multiple access networks, encounters either high computational complexity when the processing gain of the desired user is extremely high or performance deterioration when the processing gain is extremely low. By performing minimum mean square error detection on the assumed virtual symbol, the VWCA algorithm is derived and a robust blind adaptive implementation of the proposed VWCA algorithm is further developed. In contrast to the original code-aided technique, the proposed VWCA algorithm can flexibly meet different performance, complexity, and convergence speed demands for NBI suppression by adjusting the processing window length. Computer simulation results are presented to demonstrate the effectiveness of the VWCA algorithm .

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  1. 1.

    Goldsmith, A. (2005). Wireless communication. Cambridge: Cambridge University Press.

  2. 2.

    Wang, X., & Poor, H. V. (2004). Wireless communication systems: Advanced techniques for signal reception. Upper Saddle River, NJ: Prentice-Hall, 2004.

  3. 3.

    Milstein, L. B. (1988). Interference rejection techniques in spread spectrum communications. Proceedings of the IEEE, 76(6), 657–671.

  4. 4.

    Rusch, L. A., & Poor, H. V. (1994). Narrowband interference suppression in CDMA spread spectrum communications. IEEE Transactions on Communications, 42(234), 1969–1979.

  5. 5.

    Poor, H. V., & Wang, X. (1997). Code-aided interference suppression for DS/CDMA communications. Part I: Interference suppression capability. IEEE Transactions on Communications, 45, 1101–1111.

  6. 6.

    Poor, H. V., & Wang, X. (1997). Code-aided interference suppression for DS/CDMA communications. Part II: Parallel blind adaptive implementations. IEEE Transactions on Communications, 45, 1112–1122.

  7. 7.

    Buzzi, S., Lops, M., & Poor, H. V. (2002). Code-aided interference suppression for DS/CDMA overlay systems. Proceedings of the IEEE, 90(3), 394–435.

  8. 8.

    Wang, C., & Ma, M. (2010). Narrowband interference mitigation in DS-UWB systems. IEEE Signal Processing Letters, 17(5), 429–432.

  9. 9.

    Ho, K. C., Lu, X., & Mehta, V. (2007). Adaptive blind narrowband interference cancellation for multi-user detection. IEEE Transactions on Wireless Communications, 6(3), 1024–1033.

  10. 10.

    Chang, A. (2009). Subspace-based schemes for NBI and MAI suppression in DS-CDMA communications. Wireless personal communications, 50, 381–399.

  11. 11.

    Wang, F., & Tian, Z. (2008). Wideband receiver design in the presence of strong narrowband interference. IEEE Communications Letters, 12(7), 484–486.

  12. 12.

    Abedi, O., & Yagoub, M. C. E. (2013). Efficient narrowband interference cancellation in ultra-wide-band rake receivers. IET Communications, 7(1), 57–64.

  13. 13.

    Coon, J. (2008). Narrowband interference avoidance for ultra-wideband single-carrier block transmissions with frequency-domain equalization. IEEE Transactions on Wireless Communications, 7(10), 4032–4039.

  14. 14.

    Xu, Z., Nie, H., Chen, Z., Khani, H., & Yu, L. (2012). Nonlinear blind narrowband interference mitigation for energy detection based UWB receivers. IEEE Communications Letters, 16(10), 1596–1599.

  15. 15.

    Dahlman, E., Beming, P., Knutsson, J., Ovesjo, F., persson, M., & Roobol, C. (1998). WCDMA-the radio interface for future mobile multimedia communications. IEEE Transactions on Vehicular Technology, 47(4), 1105–1118.

  16. 16.

    Buzzi, S., & Poor, H. V. (2001). Channel estimation and multiuser detection in long-code DS/CDMA systems. IEEE Journal on Selected Areas in Communications, 19(8), 1476–1487.

  17. 17.

    Haykin, S. (2001). Adaptive filter theory (4th ed.). Englewood Cliffs, NJ: Prentice-Hall.

  18. 18.

    Zhao, H., Ma, S., Liu, F., & Tang, Y. (2014). A suboptimal multiuser pairing algorithm with low complexity for virtual MIMO systems. IEEE Transactions on Vehicular Technology, PP(99), 1–6.

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This work was supported by the National Natural Science Foundation of China (61531009, 61271164, 61471108, 61201266, 61501093), the National Major Projects (2014ZX03003001-002), the Ministry of Education and China Mobile Research Foundation (MCM20130111), and 863 Project (2014AA01A704, 2014AA01A706, 2015AA01A701).

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Correspondence to Fengwei Liu.

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Liu, F., Zhao, H. & Tang, Y. A Variable Window Code-Aided Algorithm for Interference Suppression in DSSS Systems. Wireless Pers Commun 88, 133–150 (2016).

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  • DSSS
  • Narrowband interference
  • Variable window code-aided