ITM Web Conf.
Volume 7, 20163rd Annual International Conference on Information Technology and Applications (ITA 2016)
|Number of page(s)||5|
|Section||Session 1: Communication and Networking|
|Published online||21 November 2016|
The Irregularity Propagation Characteristics of Radio Signals For Wireless Sensor Network In Farmland
1 National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, PR China
2 Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, PR China
3 Key Laboratory for Information Technologies in Agriculture, Ministry of Agriculture, Beijing 100097, PR China
* Corresponding author: Hua-Rui Wu: firstname.lastname@example.org
This work aims to investigate the irregular propagation characteristics of wireless sensor network (WSN) at frequency of 433 MHz. Through the analysis of the received signal strength indicator (RSSI), it is found that the variance in received signal strength is largely random, along with a continuous change with incremental changes in direction. For the transceiver distance is 20 m, the packet loss rate (PLR) in all directions is relatively small except for the east direction, indicating that the signal is still strong in all directions. While for the transceiver distance is 40 m, it can be found that there is about 90% packet loss in the east direction. That is, the received signal strength in the east direction is lower than that in the other directions. Moreover, the communication range varies with the degree of receiver direction ranging from 0 to 359. Through the regression analysis in Matlab, we find that the optimal fitting models in different directions are different. The optimal fitting model in east and west direction is the modified exponential decay, and in south and north direction is the linear logarithmic model. The values of R2 vary from 0.935 to 0.961, and the values of RMSE range from 1.75 to 2.31.
© Owned by the authors, published by EDP Sciences, 2016
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