Quantizer design for source localization in sensor networks

In this paper, we propose a quantizer design algorithm that is optimized for source localization in sensor networks. For these applications, the goal is to minimize the amount of information that the sensor nodes have to exchange in order to achieve a certain source localization accuracy. We show that to achieve this goal requires the use of "application-specific" quantizers. Our proposed quantizer design algorithm uses a cost function that takes into account the distance between the actual source position and the position estimated based on quantized data. We apply this algorithm to a system where an acoustic sensor model is employed for localization. For this case we introduce the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations show the improved performance of our quantizer over traditional quantizer designs. They also show that an optimized bit allocation leads to significant improvements in localization performance with respect to a bit allocation that uses the same number of bits for each node.