Analysis of network navigation with scheduling strategies

Network navigation is an emerging paradigm for enabling location-awareness in wireless networks. The limited wireless resource calls for scheduling algorithms to select node pairs for inter-node measurements. The design of efficient scheduling algorithms relies on an understanding of the underlying localization error evolution. This paper unifies the error evolution analysis in both the non-Bayesian and Bayesian cases. We first develop a unified recursive equation for the error evolution in the two cases. We then provide sufficient conditions for the boundedness of the error evolution. These conditions are more general than our previous results and can be used to derive error bounds for different scheduling algorithms. Furthermore, we show the the reduction of the error scaling with respect to the number of agents by increasing the multiplexing factor. These results provide insights for the efficient operation of wireless navigation networks.