Abstract
In this paper the fractal characteristics of the received multipath signals of impulse radio ultra-wideband communication system are analyzed and proved using over-value function. The scale-invariant interval can be determined by the over-value function. The over-value functions of the received multipath signals of IR-UWB are computed according to the simulated signals, measured signals and channel model based proof, respectively. The curves of the over-value functions of the above are of the same form. For the above function curves, the double logarithmic graphs are computed to find the linear segment with the opposite of the fractal dimension as its slope, where the scale-invariant interval can be determined. The signals with strong noise are not fractals and the scale-invariant interval cannot be found. The analysis above can be helpful to improve the signal receiving techniques in IR-UWB. The conclusion is that the IR-UWB signal displays fractal characteristics on its scale-invariant interval.
Similar content being viewed by others
References
Win, M. Z., & Scholtz, R. A. (1998). Impulse radio: How it works. IEEE Communications Letters, 2(2), 36–38.
Di Benedetto, M.-G., & Giancola, G. (2004). Understanding ultra wide band radio fundamentals. New Jersey: Pearson Education.
Bolotov, V. N., & Tkach, Y. V. (2007). UWB communication using fractal signals. In Proceedings of the 37th European microwave conference (pp. 1672–1675), Munich.
Evangelista, G. (2006) Fractal modulation effects. In Proceeding of the 9th international conference on digital audio effects (DAFx-06) (pp. 101–106), Montreal.
Zhang, K. H., Yang, X., & Zhang, L. (2009). Target detection in complex background based on fuzzy enhanced fractal feature. In International conference on information and automation (pp. 408–411), Zhuhai, Macau.
Lévy-Véhel, J., & Lutton, E. (Eds.). (2005). Fractals in engineering: New trends in theory and applications. London: Springer.
Leung, H., Shanmugam, S., et al. (2006). An ergodic approach for chaotic signal estimation at low SNR with application to ultra-wide-band communication. IEEE Transactions on Signal Processing, 54(3), 1091–1103.
Foerster, J. R., & Li, Q. (2003). Channel modeling sub-committee report final. In Technical Report P802.15-02/490r1, IEEE 802.15 SG3a.
Molisch, A. F., Foerster, J. R., & Pendergrass, M. (2003). Channel models for ultrawideband personal area networks. IEEE Wireless Communications Magazine, 10(6), 14–21.
UWB Database from http://ultra.usc.edu/uwb_database.
Korvin, G. (1992). Fractal models in the earth sciences. Amsterdam: Elsevier.
Crovella, M. E., & Bestavros, A. (1997). Self-similarity in world wide web traffic: evidence and possible causes. IEEE/ACM Transactions on Networking, 5(6), 835 - 846.
Chen, Y. F., Xiang, Z. T., et al. (2011). Multi-fractal characteristics of mobile node’s traffic in wireless mesh network with AODV and DSDV routing protocols. Wireless Personal Communication, 58, 741–757.
Ghassemzadeh, S. S., & Tarokh, V. (2003).UWB path loss characterization in residential environments. In IEEE radio frequency integrated circuits symposium (pp. 501–504).
Ross, S. M. (2010). Introduction to probability models (tenth ed.). Oxford: Elsevier.
Falconer, K. (1990). Fractal geometry: Mathematical foundations and applications (2nd ed.). England: Wiley.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Tian, C., Zhu, S. The Fractal Characteristics of Signals in IR-UWB Communication System. Wireless Pers Commun 77, 837–855 (2014). https://doi.org/10.1007/s11277-013-1539-4
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-013-1539-4