Transmission and encoding research on life status data in WSN combined with OVTDM and CS

In view of the life status mass data collected, Wireless Sensor Networks(WSN) has a problem of limited sampling rate and low encoding efficiency, etc. Under the Nyquist sampling criterion, traditional data encoding way has reached Shannon limit performance, and spectrum efficiency has little room for improvement. So it becomes very urgent to compress the data and reduce communication expenditure. The authors plan to use the technology of Overlapped Time Division Multiplexing(OVTDM) and Compressive Sensing(CS) jointly to carry out further research on life status Data of WSN, which overthrows traditional Nyquist criterion respectively. Under the precondition of source encoding and channel encoding, the research idea is to use CS to reduce the amount of data procession sharply, and to combine OVTDM to improve the encoding efficiency and spectrum efficiency significantly. The specific approach is to build a typical data decoding system model of WSN, and to research bit error rate and signal to noise ratio of data encoding under different fading channel using the different procession methods, which aims at assessing the research effect of data encoding improvement in WSN. The project will not only break through the theory bottleneck of the existing technology, but also has important significance for clarifying the mechanism of transmission and encoding of life status data in WSN, revealing the research law of basic theory, and expanding the engineering application fields of this technology.