Parameter Estimation Over Noisy Communication Channels in Distributed Sensor Networks

Abstract

With the recent development of low-cost, low-power, multi-functional sensor nodes, sensor networks have become an attractive emerging technology in a wide variety of applications including, but not limited to, military surveillance, civilian, industrial and environmental monitoring [1]–[5]. In most of these new applications sensor nodes are capable not only of sensing but also of data processing, wireless communications and networking. It can be argued that it is their ability of ad hoc wireless networking that has attracted much interest to wireless sensor networks in recent years. A typical sensor network may consist of a large number of spatially distributed nodes to make a decision on a Parameter of Interest (PoI). This can be detection, estimation or tracking of a target or multiple targets. Once the network is deployed, the network resources, such as node power and communication bandwidth, are limited in many situations. This is due to the fact that reinstalling and recharging the batteries might be difficult, or even impossible, once the network is deployed. A common question arising in such networks is how to effectively combine the information from all the nodes in the network to arrive at a final decision while consuming the resources in an optimum way. In a distributed sensor network, the distributed nodes make observations of PoI and process them locally to make a summary of their observations. The final decision is usually made by combining these locally processed data. Once local decisions are made at each individual sensor node, the natural questions are how to combine the local decisions and where the final decision is made. When there is a possibility that the sensor network can have a central node (generally called as the fusion center) with relatively high processing power compared to distributed nodes, the summary of the local observations can be sent to the fusion center. The fusion center combines all local decisions in an optimum way to arrive at a final decision in what is known as the centralized architecture. The disadvantage of such a system is that if there is a failure in the fusion center, the whole network fails. On the other hand, in some applications, it might be of interest that nodes communicate with each other to reach at a final decision without O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg