Title :
Spatial Correlation-Based Distributed Compressed Sensing in Wireless Sensor Networks
Author :
Hu, Haifeng ; Yang, Zhen
Author_Institution :
Coll. of Telecommun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Abstract :
In this paper, Spatial Correlation-based Distributed Compressed Sensing (SCDCS) model and algorithm are presented in Wireless Sensor Networks (WSN), where spatial correlation and joint sparse models between the sensor nodes can be exploited in order to compress and reconstruct sensor observations in an energy efficient manner based on coding/decoding algorithm of SCDCS. Finally, the analysis of relationship between reconstruction error and compression ratio in SCDCS is carried out in simulation. Simulation results show that SCDCS can achieve acceptable estimation accuracy in an energy efficient way.
Keywords :
correlation methods; decoding; encoding; wireless sensor networks; coding-decoding algorithm; compression ratio; joint sparse models; reconstruction error; spatial correlation-based distributed compressed sensing; wireless sensor networks; Algorithm design and analysis; Clustering algorithms; Compressed sensing; Correlation; Energy consumption; Measurement uncertainty; Wireless sensor networks;
Conference_Titel :
Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3708-5
Electronic_ISBN :
978-1-4244-3709-2
DOI :
10.1109/WICOM.2010.5601158
