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Channel Impulse Response Analysis of the Indoor Propagation Based on Auto-Regressive Modeling

  • Jinpeng Liang
  • Wenjun Lu
  • Yang Liu
  • Qiong Wu
  • Baolong Li
  • Zhengquan Li
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 258)

Abstract

A novel statistical channel impulse response model at 2.6 GHz is proposed for the indoor stairs and corridor environment. The model is based on the frequency domain auto-regressive (AR) process. The samples of the complex frequency response can be described as the output of the AR transfer function driven by a Gaussian white-noise process. In this model, the number of poles of the AR transfer function is determined by the significant paths of radio propagation. The paths depend on the reflectors of different propagation environment. The accuracy of the AR modeling has been verified by utilizing the root-mean-square error and root-mean-square delay spread as metrics. The model is also compared with the conventional tapped delay line model. The proposed model can be useful for the development and design of future communication.

Keywords

Channel impulse response Stairs and corridor Auto-regressive process Radio propagation 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant No. 61701197 and 61571108, the Open Foundation of Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunication, Jiangsu Province, under Grant No. 2017WICOM01, the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, under Grant No. 2018D15, the Open Foundation of State Key Laboratory of Networking and Switching Technology, the Fundamental Research Funds for the Central Universities under Grant No. JUSRP11742 and JUSRP11738, the Postgraduate Research & Practice Innovation Program of Jiangsu Provence under Grant No. SJCX18_0646.

References

  1. 1.
    Huang, Y.M.: Signal processing for MIMO-NOMA: present and future challenges. IEEE Wirel. Commun. Mag. 25(2), 32–38 (2018)CrossRefGoogle Scholar
  2. 2.
    Zhu, J.Y., Wang, J.H., Huang, Y.M., He, S.W., You, X.H., Yang, L.X.: On optimal power allocation for downlink non-orthogonal multiple access systems. IEEE J. Sel. Areas Commun. 35(12), 2744–2757 (2017)Google Scholar
  3. 3.
    Xiao, M., Mumtaz, S., Huang, Y.M.: Millimeter wave communications for future mobile networks. IEEE J. Sel. Areas Commun. 35(9), 1909–1935 (2017)CrossRefGoogle Scholar
  4. 4.
    Xiang, W., Zheng, K., Shen, X.: 5G Mobile Communications. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-34208-5CrossRefGoogle Scholar
  5. 5.
    Geng, S., Vainikainen, P.: Millimeter-wave propagation in indoor corridors. IEEE Antennas Wirel. Propag. Lett. 8, 1242–1245 (2009)CrossRefGoogle Scholar
  6. 6.
    Rao, T.R., Murugesan, D., Ramesh, S., Labay, V.A.: Radio channel characteristics in an indoor corridor environment at 60 GHz for wireless networks. In: 5th International Conference on Advanced Networks and Telecommunication Systems, pp. 1–5. IEEE, Bangalore (2011)Google Scholar
  7. 7.
    Lim, S.Y., Yun, Z., Baker, J.M., Celik, N., Youn, H.S., Iskander, M.F.: Propagation modeling and measurement for a multifloor stairwell. IEEE Antennas Wirel. Propag. Lett. 8, 583–586 (2009)CrossRefGoogle Scholar
  8. 8.
    Zhao, X., Kivinen, J., Vainnikainen, P.: Tapped delay line channel models at 5.3 GHz in indoor environments. In: 52nd Vehicular Technology Conference, pp. 1–5. IEEE, Boston (2000)Google Scholar
  9. 9.
    Yu, Y., Liu, Y., Lu, W.J., Jin, S., Zhu, H.B.: Modeling and simulation of channel power delay profile under indoor stair environment. IET Commun. 11(1), 119–126 (2017)CrossRefGoogle Scholar
  10. 10.
    Suzuki, H.: A statistical model for urban radio propagation. IEEE Trans. Commun. 25(7), 673–680 (1977)CrossRefGoogle Scholar
  11. 11.
    Saleh, A.A.M., Valenzuela, R.: A statistical model for indoor multipath propagation. IEEE J. Sel. Areas Commun. 5(2), 128–137 (1987)CrossRefGoogle Scholar
  12. 12.
    Liu, Y., Yu, Y., Lu, W.J., Zhu, H.B.: Antenna-height-dependent path loss model and shadowing characteristics under indoor stair environment at 2.6 GHz. IEEJ Trans. Electr. Electron. Eng. 10(5), 498–502 (2015)CrossRefGoogle Scholar
  13. 13.
    Emanuel, P., Kunio, T., Genshiro, K.: Selected Papers of Hirotugu Akaike. Springer, New York (1998).  https://doi.org/10.1007/978-1-4612-1694-0CrossRefzbMATHGoogle Scholar
  14. 14.
    Morrison, G., Fattouche, M., Zaghloul, H.: Statistical analysis and autoregressive modeling of the indoor radio propagation channel. In: 1st International Conference on Universal Personal Communications, pp. 97–101. IEEE, Dallas (1992)Google Scholar
  15. 15.
    Yang, C.F., Wu, B.C.: A ray-tracing/PMM hybrid approach for determining wave propagation through periodic structures. IEEE Trans. Veh. Technol. 50(3), 791–795 (2001)CrossRefGoogle Scholar
  16. 16.
    Howard, S.J., Pahlavan, K.: Autoregressive modeling of wide-band indoor radio propagation. IEEE Trans. Commun. 40(9), 1540–1552 (1992)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Jinpeng Liang
    • 1
  • Wenjun Lu
    • 2
  • Yang Liu
    • 1
    • 2
  • Qiong Wu
    • 1
    • 3
  • Baolong Li
    • 1
    • 3
  • Zhengquan Li
    • 1
  1. 1.Key Laboratory of Advanced Process Control for Light IndustryJiangnan UniversityWuxiChina
  2. 2.Jiangsu Key Laboratory of Wireless CommunicationsNanjing University of Posts and TelecommunicationsNanjingChina
  3. 3.National Mobile Communications Research LaboratorySoutheast UniversityNanjingChina

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