Ray Propagation Channel Modeling Using Geographic Information Systems for Wireless Sensor Network Deployment

In wireless sensor network (WSN) implementations, the potential loss of crucial measurement data is problematic. This happens when the sensor nodes and the base station have a wireless link that does not reach the required received signal strength indicator (RSSI) levels. To prevent data loss, a proactive approach involves the prediction RSSI values within the vicinity of the base station, and positioning sensor nodes in locations with sufficient RSSI levels. Predicting the RSSI level involves channel modelling of radio propagation mechanisms such as ray propagation. The integration of geographic information systems (GIS) into creating 3D environment models would enhance the accuracy of channel modelling, since prediction considers obstructions and reflections. The RSSI prediction was conducted by gathering GIS data to simulate the buildings of UP Diliman, then applying ray propagation models allowed the researcher to determine locations with sufficient RSSI from the proposed base stations. The results of this study will be useful in the instance that a wireless sensor network is implemented in UP Diliman.