Performance Enhancement of Fuzzy Logic Based Transmission Power Control in Wireless Sensor Networks Using Markov Based RSSI Prediction
In this paper, the authors propose strategies for Transmission Power Control (TPC) in wireless sensor networks that guarantee reduction in the average power and average energy consumption. Two methods are proposed, Fuzzy logic based TPC (FTPC) and Markov based TPC (MTPC). FTPC utilizes the current value of Received Signal Strength Index (RSSI) and the source node's transmission Power (Ptsrc) for deciding the required transmission Power (Ptreq). In MTPC, the RSSI variations for successive transmissions are modeled as a Markov chain based on which a transition probability matrix is formulated. The Markov model utilizes the transition probability matrix to predict future RSSI variations and this information is effectively utilized by the Fuzzy logic for deciding the Ptreq value.