Fundamental Bounds on Position Estimation Using Proximity Reports
2016 (English)Conference paper (Refereed)
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 Cram´er-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 Cram´er-Rao bound and conclude that the Barankin bound ought be better suited for benchmarking any proximity report based position estimator.
Place, publisher, year, edition, pages
Barankin bound, Cramér-Rao bound, mean-square-error, position estimation, proximity report.
IdentifiersURN: urn:nbn:se:liu:diva-129760OAI: oai:DiVA.org:liu-129760DiVA: diva2:943184
IEEE 83rd Vehicular Technology Conference: VTC2016-Spring 15–18 May 2016, Nanjing, China