# GPRS Sensor Node Battery Life Span Prediction Based on Received Signal Quality: Experimental Study
###### Abstract
The scenario which is happening is almost the same as in human being communication; when someone with whom you are communicating is far away, you will have to use a lot of energy for the communication to be effective and if you are near each other, low energy is used for communication. The amplification of the received signal does not require any extra battery power but, in the situation when the received signal is weak, the mobile phone will try to boost its transmitter power expecting that it will increase the quality of the signal from the base stationl [9]. Then the increase in transmitter power will drain the battery more than in a location with good signal quality. A GPRS sensor node is like a mobile phone, it will transmit data through its nearest BTS as it is shown in Figure 1. In this paper, we are trying to show that when our sensor node has poor signal quality it will try to increase its transmitter power for better reception; this will consume a lot of energy from the battery. In the end, we will demonstrate the relationship between the power consumption and the signal quality (RSSI) at a particular location and this relationship will bring us to mathematically estimate the battery life of a GPRS sensor in that region. In this paper, we have tried to record the current consumption of our GPRS sensor node for six different locations with different received signal strength information (RSSI) levels. For each location, we have recorded: a. Reference current which is the consumed current when the GSM/GPRS module is switched off. b. GSM current which is current when the module is switched ON and connected to the network. And, c. GPRS current which is current when the module is transmitting data to a remote server and the RSSI value. Each of the above parameters has been recorded for 24 h. The received strength signal indicator (RSSI) is an important parameter which shows the quality of the signal which is being received by a receiver; this parameter depends mainly on the power which has been transmitted, the distance between the transmitter and receiver, and the medium between the transmitter and receiver [10]. A lot of research has been conducted about the localization of the receiving sensor node using RSSI and some research demonstrated that there is an impact of RSSI on the drainage of the battery. In this paper, we are trying to find the mathematical model which shows the effect of the RSSI on the power consumption of a receiving GPRS based sensor node and from here we will also estimate the sensor node lifetime. In our paper, we did our experiment with an IoT application that we can call \"Remote temperature monitor (RTM)\" which is sending temperature from five different locations to a remote server and at a rate of 20 s; we then try to see how this application will consume current in different locations remembering that each location will be defined by its RSSI. Then we used results from our measurement to derive a mathematical model that links the received strength signal information and the sensor node lifetime. With this, it will be possible to quantitatively understand how poor signal quality will reduce the lifetime of a sensor node, especially a GSM-based node. Basically, we are considering our sensor node as a mobile phone with only one application of sending data to the cloud. This can be applied both indoor as well as outdoor. During our modeling, we are supposing that:  
* Our sensor node is not moving,
* The rate with which the sensor node is transmitting data is fixed,
* All sensors in the network are not moving, and
* The sensor node is dead if and only if the battery voltage drops to 70% of its full charged voltage [11; 12]. Our contribution is to develop a data-driven mathematical model that shows the impact of RSSI on the battery life of GPRS/GSM based sensor nodes in a particular location. The rest of this research work is organized as follows: Section 2 details some other works which are related to our paper.