Energy Efficient Distributed Detection via Multi-Hop Transmission in Sensor Networks

Abstract

Most existing works on distributed detection have assumed that a bank of independent dedicated channels or a multiaccess channel is used for transmitting local decisions to the fusion center. Such a transmission scheme could result in significant energy expenditure when sensors are far from the fusion center. The natural solution to energy-efficient distributed detection is to use multi-hop transmission with information fusion at intermediate nodes. In this paper, we investigate three options for multi-hop fusion schemes: Multihop Forwarding (MF), Multihop Histogram Fusion (HF) and Multihop LLR Fusion (LF). For the simplest MF scheme, the quantized observations are sent to the fusion center along the shortest path tree without further processing at relaying nodes. For HF, each sensor transmits the histogram of the observations of its descendants and itself, which achieves further energy reduction relative to MF when the number of quantization bits is small. For LF, the normalized loglikelihood ratio (LLR) values for subsets of nodes are computed and propagated along the minimum spanning tree, such that the fusion center acquires an estimate of the normalized LLR of all sensors' observations, which is used to decide the hypothesis. We show that LF exhibits the most favorable energy scaling laws with the network size among these schemes. Simulation results suggest that multihop fusion schemes significantly reduces the transmission energy compared with direct transmission, with LF requiring the least energy to achieve the same detection performance.