Considerations about the Signal Level Measurement in Wireless Sensor Networks for Node Position Estimation

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSN) are crucial for monitoring systems, facing challenges in network autonomy, node localization, and data security.
• Node localization and distance estimation often rely on signal strength metrics like Received Signal Strength Indicator (RSSI).
• Understanding RSSI variations is key to improving WSN performance and reliability.

Purpose of the Study:

• To investigate the factors influencing Received Signal Strength Indicator (RSSI) measurements in Wireless Sensor Networks (WSN).
• To assess the impact of distance, geometrical orientation, and environment (indoor/outdoor) on RSSI values.
• To evaluate energy-aware data transmission algorithms and their relation to node power consumption.

Main Methods:

• Designed and implemented a system for Received Signal Strength Indicator (RSSI) acquisition.
• Conducted experiments in diverse indoor and outdoor environments to collect RSSI data.
• Measured node current consumption based on adjusted transmission power for energy-aware data transmission.

Main Results:

• RSSI measurements exhibit significant variations based on node distance, geometrical orientation, and environmental characteristics.
• Non-linearity in RSSI values necessitates intermediate processing for accurate distance and location estimation.
• Energy-aware transmission algorithms effectively adjust node power consumption relative to inter-node distances.

Conclusions:

• RSSI is a viable, yet complex, metric for WSN localization, requiring careful calibration and signal processing.
• Environmental factors and sensor orientation critically affect RSSI, impacting localization accuracy.
• Optimizing energy consumption in WSNs is achievable through distance-aware transmission power control.