Energy Efficient Signal Detection in Sensor Networks Using Ordered Transmissions

Signal detection is one application for which dedicated sensor networks have been proposed. Joint signal processing and communication design of such networks has been of great interest recently. We consider new approaches where transmissions can be ordered and halted when sufficient evidence is accumulated. We demonstrate that these approaches require, on average, fewer sensor transmissions and that the savings can be significant in cases of interest. We describe a highly efficient approach which saves transmissions over either the optimum unconstrained energy approach or censoring while achieving the same error probability as these approaches. The average number of transmissions saved (ANTS) is lower bounded by a quantity proportional to the number of sensors employed provided a well-behaved distance measure between the sensor distributions is sufficiently large. For such cases, the ANTS over the optimum unconstrained energy approach is shown to be larger than half the number of sensors employed. Numerical results for a mean-shift hypothesis testing problem with Gaussian noise show significant savings even for smaller values of the distance measure.