An algorithm for green communication signal reconstruction in wireless sensor network. Case study Kenya prisons telecommunication

Abstract

Environmental consideration provides news trends in wireless communication network known as green communication. The main object of green communication is to save as much as possible the energy consumption of the communication system. In this research study, We have investigated the green distributed nonlinear state estimation problem in wireless sensor networks (WSNs).which will be seamlessly integrated with the forthcoming 5G communication system’s distributed signal reconstruction algorithm is developed by employing compressive sensing and consensus filter to solve sparse signal reconstruction issue in WSNs with energy efficiate considered. In particular, the pseudo-measurement (PM) technology is introduced into the Kalman filter(CKF),and a sparsity constraint is imposed on the nonlinear estimation CKF.inorder to develop a distributed reconstruction algorithm to fuse the random linear measurement from the nodes in WSNs,the PM embedded CKF is formulated into the information form, and then the derived information filter is combined with consensus filter, while the square-root version is further developed to improve the performance and strengthen power saving capability. The simulation result demonstrate that the signal can be reconstructed with much fewer nodes in decentralized manner and all the nodes can reach a consensus, while providing some attractive benefits to the green 5G communication system