Compressed Sensing for Efficient Random Routing in Multi-Hop Wireless Sensor Networks

Date Added: Aug 2010
Format: PDF

Compressed Sensing (CS) is a novel theory based on the fact that certain signals can be recovered from a relatively small number of non-adaptive linear projections, when the original signals and the compression matrix own certain properties. In virtue of these advantages, compressed sensing, as a promising technique to deal with large amount of data, is attracting ever-increasing interests in the areas of wireless sensor networks where most of the sensing data are the same besides a few deviant ones. However, the applications of traditional CS in such settings are limited by the huge transport cost caused by dense measurement.