Channel Error Suppression using Correlation of Sensing Infcmnation in Wrekss Sensor Networks

点击翻译按钮获取中文摘要

This research has aimed to achieve the performance improvement of the wireless sensor networks by using the correlation between the data observed by an individual sensor node.If the correlation is one, it can be thought as a diviersity reception as the case is the same as the reception of two stunk having same information, Thus, the influence of error on the wireless communication channel can be reduced when there is a correlation in the observational data.In this study, we consider joint channel decocting of Turbo code fur multiple correlated data that are observed by sensor nodes densely deployed in a sensor field. We focus on the correlation properties of observation data and try to reduce decocting arm by an iterative procedure. An approach to use practical channel codes for more than two correlated data is still not presented. A problem in the extension to cases of mom than two sensor nodes is how to use the information of correlation obtained from observation data. In this studs we propose an iterative channel decoding scheme that uses them with weighting. We show that when the number of sensor nodes is increased, decoding performance improvement cannot be achieved by simple weighting, and so a more appropriate weight is needed. We find the optimum weight that minimizes the bit error rate from the analytical formula for unaided BPSK and apply it to the case of Turbo code.Further, we show Extrinsic information transfer (EAT) of turbo based iterative joint decoding scheme f or two correlated binary sources. The convergence behavior of the proposed system is studied using EXIT charts.