Reconstruction of Level Cross Sampled Signals using Sparse Signals & Backtracking Iterative Hard Thresholding

Abstract

Industry 4.0 applications involve more number of sensors or Internet of Things (IoT) devices to support automation in the industry. It involves more number of computations to analyze the sensor data collected from several critical parts of the processing units. Sparse signal processing is one which has numerous applications in area of communication and signal processing. This paper presents a novel approach to reduce the computations with the help of level cross sampling (LCS) and a backtracking based iterative hard thresholding (BIHT) algorithm for reconstruction. The process involves, an information signal is converted to a random sparse signal using non-uniform sampling at the transmitter side and then it can be reconstructed back using BIHT algorithm at receiver side. Simulation results exhibit the superior performance of the proposed BIHT reconstruction in comparison with the literature.