Abstract-There is a big trend nowadays toward indoor proximity report based positioning. A binary valued proximity report can be obtained opportunistically through event-triggering, leading to significantly reduced signaling overhead for wireless communications. In this paper, we aim to derive two types of fundamental lower bound, namely the Cramér-Rao bound and the Barankin bound, on the mean-square-error of any proximity report based position estimator. Using the maximum-likelihood estimator as a representative example, we show that the Barankin bound is potentially much tighter than the Cramér-Rao bound and conclude that the Barankin bound ought be better suited for benchmarking any proximity report based position estimator.
The performance metric to be optimized is selected to be the overall positioning root-mean-square-error (RMSE) represented in terms of the Cramér-Rao bound or Barankin bound REF .
Fundamental Bounds on Position Estimation Using Proximity Reports
2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)
2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)
Computer Science