Distributed Subspace Projection in Wireless Sensor Networks Using Computational Codes

In this paper, we develop a new power-efficient algorithm for Wireless Sensor Networks (WSN) in order to obtain, in a distributed manner, the Projection of an observed sampled spatial field on a subspace of lower dimension. This is an important problem that is motivated in various applications where there are well defined subspaces of interest (e.g. spectral maps in cognitive radios). As opposed to traditional Gossip Algorithms used for subspace projection assuming separation of channel coding and computation, our algorithm combines Computational Coding and a modification of existing Gossip Algorithms, achieving important savings in convergence time and yielding an exponential decrease in energy consumption as the size of the network increases.