Advertisement

Wireless Networks

, Volume 21, Issue 4, pp 1227–1242 | Cite as

Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks

  • Nan Zhao
  • F. Richard YuEmail author
  • Hongjian Sun
  • Hongxi Yin
  • A. Nallanathan
  • Guan Wang
Article

Abstract

Interference alignment (IA) is a promising technique that can effectively eliminate the interferences in multiuser wireless networks. However, it requires highly accurate channel state information (CSI) of the whole network at all the transmitters and receivers. In practical wireless systems, it is difficult to obtain the perfect knowledge of a dynamic channel. Particularly, the CSI at transmitters used in IA is usually delayed through feedback, which will dramatically affect the performance of IA. In this paper, the performance of IA with delayed CSI is studied. The expressions of the average signal to interference plus noise ratio and sum rate of IA networks with delayed CSI are established. To alleviate the influence of delayed CSI, an IA scheme based on dynamic autoregressive (AR)-model channel prediction is proposed, in which the parameters of AR mode are updated frequently. The CSI of the next time instant is predicted using the present and past CSI in the proposed scheme to improve the performance of IA networks. Two key factors of the scheme, window length and refresh rate are analyzed in detail. Simulation results are presented to show that the proposed IA scheme based on channel prediction can significantly improve its performance with delayed CSI.

Keywords

Interference alignment Delayed channel state information Linear channel prediction Autoregressive model 

Notes

Acknowledgments

This research was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61201224 and 61372089, China Postdoctoral Science Foundation Special Funded Project under 2013T60282, and the Fundamental Research Funds for the Central Universities under DUT14QY44.

References

  1. 1.
    Cadambe, V. R., & Jafar, S. A. (2008). Interference alignment and degrees of freedom of the K-user interference channel. IEEE Transactions on Information Theory, 54(8), 3425–3441.CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Maddah-Ali, M. A., Motahari, A. S., & Khandani, A. K. (2008). Communication over MIMO X channels: Interference alignment, decomposition, and performance analysis. IEEE Transactions on Information Theory, 54(8), 3457–3470.CrossRefMathSciNetGoogle Scholar
  3. 3.
    Jafar, S. A. (2010). Interference alignment—A new look at signal dimensions in a communication network. Foundations and Trends in Communications and Information Theory, 7(1), 1–130.CrossRefzbMATHMathSciNetGoogle Scholar
  4. 4.
    Gomadam, K., Cadambe, V. R., & Jafar, S. A. (2011). A distributed numerical approach to interference alignment and applications to wireless interference networks. IEEE Transactions on Information Theory, 57(6), 3309–3322.CrossRefMathSciNetGoogle Scholar
  5. 5.
    Yi, Y., Zhang, J., Zhang, Q., & Jiang, T. (2012). Exploring frequency diversity with interference alignment in cognitive radio networks. In Proceedings of the IEEE Globecom’12, Anaheim, CA.Google Scholar
  6. 6.
    Qu, T., Zhao, N., Yin, H., & Yu, F. (2012). Richard interference alignment for overlay cognitive radio based on game theory. In Proceedings of IEEE ICCT’12, Chengdu, China.Google Scholar
  7. 7.
    Guler, B., & Yener, A. (2011). Interference alignment for cooperative MIMO femtocell networks. In Proceedings of IEEE Globecom’11, Houston, TX.Google Scholar
  8. 8.
    Suh, C., Ho, M., & Tse, D. N. C. (2011). Downlink interference alignment. IEEE Transactions on Communication, 9(59), 2616–2626.CrossRefGoogle Scholar
  9. 9.
    Da, B., & Zhang, R. (2011). Exploiting interference alignment in multi-cell cooperative OFDMA resource allocation. In Proceedings of IEEE Globecom’11, Houston, TX.Google Scholar
  10. 10.
    Ayach, O. E., Peters, S. W., & Heath, R. W, Jr. (2013). The practical challenges of interference alignment. IEEE Wireless Communication, 20(1), 35–42.CrossRefGoogle Scholar
  11. 11.
    Santamaria, I., Gonzalez, O., Heath, R. W., Jr., & Peters, S. W. (2010). Maximum sum-rate interference alignment algorithms for MIMO channels. In Proceedings of IEEE Globecom’10, Miami, FL.Google Scholar
  12. 12.
    Wang, C., Papadopoulos, H. C., Pamprashad, S. A., & Caire, G. (2011). Improved blind interference alignment in a cellular environment using power allocation and cell-based clusters. InProceedings of IEEE ICC’11, Kyoto, Japan.Google Scholar
  13. 13.
    Zhao, N., Yu, F. R., Sun, H., Nallanathan, A., & Yin, H. (2013). A novel interference alignment scheme based on sequential antenna switching in wireless networks. IEEE Transactions on Wireless Communication, 12(10), 5008–5021.CrossRefGoogle Scholar
  14. 14.
    Shen, H., & Li, B. (2010). A novel iterative interference alignment scheme via convex optimization for the MIMO interference channel. In Proceedings of IEEE VTC’10F, (pp. 1–5), Ottawa, Canada.Google Scholar
  15. 15.
    Peters, S. W., & Heath, R. W, Jr. (2011). Cooperative algorithms for MIMO interference channels. IEEE Transactions on Vehicular Technology, 60(1), 206–218.CrossRefGoogle Scholar
  16. 16.
    Nosrat-Makouei, B., Andrews, J. G., & Heath, R. W, Jr. (2011). MIMO interference alignment over correlated channels with imperfect CSI. IEEE Transactions on Signal Processing, 59(6), 2783–2794.CrossRefMathSciNetGoogle Scholar
  17. 17.
    Krishnamachari, R. T., & Varanasi, M. K. (2010). Interference alignment under limited feedback for MIMO interference channels. In Proceedings of IEEE ISIT’10, Austin, TX.Google Scholar
  18. 18.
    Shin, W. Y., Kim, M., Yi, H., Kim, A., & Jung, B. C. (2011). Degrees-of-freedom based on interference alignment with imperfect channel knowledge. IEICE Transactions on Communications, E94B(12), 3579–3582.CrossRefGoogle Scholar
  19. 19.
    Huang, H., Lau, V. K. N., Du, Y., & Liu, S. (2011). Robust lattice alignment for K-user MIMO interference channels with imperfect channel knowledge. IEEE Transactions on Signal Processing, 59(7), 3315–3325.CrossRefMathSciNetGoogle Scholar
  20. 20.
    Ayach, O. E., & Heath, R. W, Jr. (2012). Interference alignment with analog channel state feedback. IEEE Transactions on Wireless Communications, 11(2), 626–636.CrossRefGoogle Scholar
  21. 21.
    Xie, B., Li, Y., Minn, H., & Nosratinia, A. (2013). Adaptive interference alignment with CSI uncertainty. IEEE Transactions on Communications, 61(2), 792–801.CrossRefGoogle Scholar
  22. 22.
    Jafar, S. (2012). Blind interference alignment. IEEE Journal of Selected Topics in Signal Processing, 6(3), 216–227.CrossRefMathSciNetGoogle Scholar
  23. 23.
    Taricco, G., & Biglieri, E. (2005). Space-time decoding with imperfect channel estimation. IEEE Transactions on Wireless Communication, 4(4), 1874–1888.CrossRefGoogle Scholar
  24. 24.
    Trivedi, Y. N., & Chaturvedi, A. K. (2011). Performance analysis of multiple input single output systems using transmit beamforming and antenna selection with delayed channel state information at transmitter. IET Communications, 5(6), 827–834.CrossRefzbMATHMathSciNetGoogle Scholar
  25. 25.
    Wen, S., & Yu, F. R. (2012). Predictive control for energy efficiency in wireless cellular networks. In Proceedings of IEEE VTC’12S, Yokohama, Japan.Google Scholar
  26. 26.
    Goldsmith, A., Effros, M., Koetter, R., Medard, M., Ozdaglar, A., & Zheng, L. (2011). Beyond Shannon: The quest for fundamental performance limits of wireless ad hoc networks. IEEE Communications Magazine, 49, 195–205.CrossRefGoogle Scholar
  27. 27.
    Vaze, C. S., & Varanasi, M. K. (2012). The degrees of freedom region and interference alignment for the MIMO interference channel with delayed CSIT. IEEE Transactions on Information Theory, 58(7), 4396–4417.CrossRefMathSciNetGoogle Scholar
  28. 28.
    Maddah-Ali, M. A., & Tse, D. (2012). Completely stale transmitter channel state information is still very useful. IEEE Transactions on Information Theory, 58(7), 4418–4431.CrossRefMathSciNetGoogle Scholar
  29. 29.
    Biglieri, E., Calderbank, R., Constantinides, A., Goldsmith, A., Paulraj, A., & Poor, H. V. (2007). MIMO wireless communications. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  30. 30.
    Boukerche, A. (2004). Performance evaluation of routing protocols for ad hoc wireless networks. Mobile Networks and Applications, 9(4), 333–342.CrossRefGoogle Scholar
  31. 31.
    Song, B., Cruz, R. L., & Rao, B. D. (2005). Network duality and its application to multi-user MIMO wireless networks with SINR constraints. In Proceedings of IEEE ICC’05 (pp. 2684–2689), Seoul.Google Scholar
  32. 32.
    Viswanathan, H. (1999). Capacity of Markov channels with receiver CSI and delayed feedback. IEEE Transactions on Information Theory, 45(2), 761–771.CrossRefzbMATHMathSciNetGoogle Scholar
  33. 33.
    Duel-Hallen, A. (2007). Fading channel prediction for mobile radio adaptive transmission systems. Proceedings of the IEEE, 95, 2299–2313.CrossRefGoogle Scholar
  34. 34.
    Boukerche, A. (2005). Handbook of algorithms for wireless networking and mobile computing. Boca Raton: CRC Press.CrossRefGoogle Scholar
  35. 35.
    Boukerche, A., Hong, S., & Jacob, T. (2002). A distributed algorithm for dynamic channel allocation. Mobile Networks and Applications, 7(2), 115–126.CrossRefGoogle Scholar
  36. 36.
    Haykin, S. (2002). Adaptive filter theory (4th Edition). Upper Saddle River: Prentice Hall.Google Scholar
  37. 37.
    Zhao, N., Yu, F. R., Sun, H., Yin, H., & Nallanathan, A. (2012). Interference alignment based on channel prediction with delayed channel state information. In Proceedings of the IEEE Globecom’12, Anaheim, CA.Google Scholar
  38. 38.
    Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communication. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  39. 39.
    Clarke, R. H. (1968). A statistical theory of mobile radio reception. Bell System Technical Journal, 47(6), 957–1000.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Nan Zhao
    • 1
  • F. Richard Yu
    • 2
    Email author
  • Hongjian Sun
    • 3
  • Hongxi Yin
    • 1
  • A. Nallanathan
    • 4
  • Guan Wang
    • 1
  1. 1.School of Information and Communication EngineeringDalian University of TechnologyDalianChina
  2. 2.Department of Systems and Computer EngineeringCarleton UniversityOttawaCanada
  3. 3.School of Engineering and Computer ScienceDurham UniversityDurhamUK
  4. 4.Institute of TelecommunicationsKing’s College LondonLondonUK

Personalised recommendations