Clustered Compressive Sensing for M2M Communications

• Main Authors: Lo, Chung-Wei, 羅仲煒
• Other Authors: Huang, Ching-Yao
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/73642599365530511157

碩士 === 國立交通大學 === 電子工程學系 電子研究所 === 102 === Compressive sensing (CS) is an emerging technique for signal processing or image processing. The advantage of compressive sensing is that we can sample a signal of interest below the Nyquist rate and perfectly reconstruct from norm minimization. In this thesis, we apply compressive sensing into wireless sensor network for M2M communications in complex environments. Our proposed methodology is named clustered compressive sensing. Our goal is to recover the signal of unreceived sensor nodes from the signal of received sensor nodes, and furthermore, reduce the reconstruction error by clustering those sensors into clusters according to their data distribution and positions. Next, each clusters use principal component analysis (PCA) to obtain the linear projection matrices which transform the original signal into a sparse representation. Then, choosing active nodes randomly to transmit its data. And finally, recovering the original by norm minimization.