Browse > Article

An Accurate Radio Channel Model for Wireless Sensor Networks Simulation  

Alejandro Martfnez-Sala (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Jose-Maria Molina-Garcia-Pardo (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Esteban Egea-Lopez (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Javier Vales-Alonso (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Leandro Juan-Llacer (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Joan Garcia-Haro (Department of Information Technologies and Communications at the Polytechnic University of Cartagena(UPCT))
Publication Information
Abstract
Simulations are currently an essential tool to develop and test wireless sensor networks (WSNs) protocols and to analyze future WSNs applications performance. Researchers often simulate their proposals rather than deploying high-cost test-beds or develop complex mathematical analysis. However, simulation results rely on physical layer assumptions, which are not usually accurate enough to capture the real behavior of a WSN. Such an issue can lead to mistaken or questionable results. Besides, most of the envisioned applications for WSNs consider the nodes to be at the ground level. However, there is a lack of radio propagation characterization and validation by measurements with nodes at ground level for actual sensor hardware. In this paper, we propose to use a low-computational cost, two slope, log-normal path­loss near ground outdoor channel model at 868 MHz in WSN simulations. The model is validated by extensive real hardware measurements obtained in different scenarios. In addition, accurate model parameters are provided. This model is compared with the well-known one slope path-loss model. We demonstrate that the two slope log-normal model provides more accurate WSN simulations at almost the same computational cost as the single slope one. It is also shown that the radio propagation characterization heavily depends on the adjusted model parameters for a target deployment scenario: The model parameters have a considerable impact on the average number of neighbors and on the network connectivity.
Keywords
Channel modeling; near ground propagation; simulation;
Citations & Related Records

Times Cited By Web Of Science : 7  (Related Records In Web of Science)
Times Cited By SCOPUS : 19
연도 인용수 순위
1 J. Zhao and R. Govindan, 'Understanding packet delivery performance in dense wireless sensor networks,' in Proc. ACM SenSys 2003, Los Angeles, California (USA), Nov. 2003
2 Mica2 MOTES, http://www.xbow.com
3 H. L. Bertoni, Radio Propagation for Modern Wireless Systems, New Jersey, Prentice Hall, 2000
4 K. Sohrabi, B. Manriquez, and G. Pottie, 'Near-ground wideband channel measurements,' in Proc. IEEE VTC'99, New York, 1999, pp. 571-574
5 R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler, 'An analysis of a large scale habitat monitoring application,' in Proc. ACM SenSys 2004, Baltimore (USA), Nov. 2004
6 D. Ganesan, D. Estrin, A. Woo, and D. Culler, 'Complex behavior at scale: An experimental study of low-power wireless sensor networks,' Technical Report UCLA/CSD-TR02-0013, Center for Embedded Networked Sensing, University of California, Berkeley, Feb. 2002
7 Chipcon CC1000, http://www.chipcon.com
8 T. Rappaport, Principles of Communications Systems, Prentice Hall, 2nd ed
9 G. Zhou, T. He, S. Krishnamurthy, and J. A. Stankovic, 'Impact of radio irregularity on wireless sensor networks,' in Proc. MobySys 2004, Boston, MA, June 2004, pp. 125-138
10 The network simulator ns-2, http://www.isi.edu/nsnam/ns/
11 A. Woo, T. Tong, and D. Culler, 'Taming the underlying issues for reliable multihop routing in sensor networks,' in Proc. ACM SenSys 2003, Los Angeles, California (USA), Nov. 2003
12 N. Reijers, G. P. Halkes, and K. G. Langendoen, 'Link layer in sensor networks,' in Proc. IEEE Int. Conf. Mobile Ad-hoc and Sensor Systems 2004, Florida (USA), Oct. 2004
13 E. Egea-Lopez, J. Vales-Alonso, A. S. Martinez-Sala, P. Pavon-Marino, and J. Garcia-Haro, 'Simulation tools for wireless sensor networks,' in Proc. SPECTS 2005, Philadelphia, PA, July 2005, pp. 559-566
14 V. Naoumov and T. Gross, 'Simulation oflarge ad-hoc networks,' in Proc. ACM MSWiM 2003, San Diego, CA, 2003, pp. 50-57
15 H. Spath, One Dimensional Spline Interpolation Algorithms, Wellesley, A. K. Peters Ltd., 1995
16 L. F. Perrone, Y. Yuan, and M. Nicol, 'Modeling and simulation best practices for wireless ad hoc networks,' in Proc. 2003 Winter Simulation Conf., New Orleans, LA, 2003, pp. 685-693
17 D. Kotz, C. Newport, B. Gray, J. Liu, Y. Yuan, and C. Elliot, 'Experimental evaluation of wireless simulation assumptions,' in Proc. ACM/IEEE MSWiM 2004, Venice, Italy, Oct. 2004, pp. 78-82
18 M. Takai, R. Bagrodia, K. Tang, and M. Gerla, 'Efficient wireless network simulations with detailed propagation models,' Wireless Networks, vol. 7, no. 3, pp. 297-305, May 2001   DOI   ScienceOn