Efficient communication strategies for distributed signal field estimation

Wireless sensor networks are a promising architecture for monitoring large spatial areas. While recent years have seen a surge of research activity in sensor networks, many significant challenges need to be overcome to realize the vision of sensor networks. The key challenges are tied to two vital operations in a sensor network: efficient information routing between sensor nodes to extract useful information from the data collected by the sensors; and efficient communication of this information from the network to a certain destination. This paper proposes a novel collaborative communication and estimation scheme for distributed signal field estimation that overcomes these challenges by exploiting the underlying smoothness of the field. In our approach, the signal field is uniformly partitioned into multiple regions and the nodes in each region coherently communicate their measurements via a dedicated noisy multiple access channel (MAC) to the destination where the estimate of each region is constructed to give an estimate of the entire field. Two salient features of our scheme are: it requires relatively little collaboration among sensing nodes; and is potentially far more power-efficient due to the power pooling gain afforded by coherent cooperation of the nodes in each region. In this paper, we analyze our new approach under the simple setting of estimating a piece-wise constant field and show that optimal mean-square distortion scaling can be achieved at the destination with constant network power (vanishing per node power).