Compressive Sensing Implementation In a Wireless Sensor Network Environment

Anand, Abhishek (2017) Compressive Sensing Implementation In a Wireless Sensor Network Environment. Masters thesis, Indian Institute of Technology Hyderabad.

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Abstract

In the present world we are surrounded by various sensors providing us with all kinds of information. This led to emergence in the research of Wireless Sensor Netwo rk (WSN) and Internet Of Things (IOT). Efficient data gathering in these fields becomes an important objective as the power and battery life of most of these devices are limited. We move away from the usual method of sampling the data at Nyquist Rate to a techn ique called Compressive Sensing (CS). Compressive technique ut ilizes the sparse nature of natural signals allowing us to sample and recover the signals at much lower rate. The recovery algorithm implemented was Orthogonal Matching pursuit (OMP) which is a greedy recovery algorithm. A new method of Compressive Sensing called quantized Compressive Sensing was also studied and implemented. Quantized Compressive Sensing focuses on the quantization of the measured values. 1 bit CS which is an extreme case of the quantized Compressive Sensing was implemented. Binary Iterati ve Hard Thresholding (BIHT) was implemented to recover the signal. I have also shown the other miscellaneous stuffs which I did during my M.tech at IIT hyd. These include study of the Bluetooth technology and implementing it in Matlab and Simulink. I had a lso designed an IoT product which is ultra - low power wireless door sensor. The door sensor informs the user the status of doors and windows. This can be used for variety of applications ranging from reducing the power from Air Conditioner to security appli cations

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