Iterative ToA-based terminal positioning in emerging cellular systems

Abstract

Abstract-Emerging cellular networks integrate the user terminal geo-localization function besides the communication function. The conventional positioning approach is to estimate the terminal location in two-steps: first the distance to all connected base stations is assessed based on signal time-of-flight measurements, then the location is deduced from the distances by multilateration. The two-step approach incurs a performance degradation because information is lost from the received signal when the multi-lateration is performed. In this paper, we propose to iterate between the two conventional steps to progressively refine the distance estimates based on the knowledge of the position estimate obtained from the previous iterations. The information exchanged between the two-steps not only consists in the mean of the estimates (distance or position) but also of their variance that convey information about the reliability of the estimates. Simulation results show that the achievable performance after a few iterations is close to the performance of the optimal approach that directly estimates the position based on the observation of the received signal.

ToA-based Iterative Localization in Rich Multipath Channels

“…The principle of the iterative localization system is very similar to [10]. The algorithm relies on the Bayes framework [11] to take into account prior knowledge from the previous iteration.…”

“…The mean and variance of the posterior distribution (10) respectively provide the Minimum Mean Square Error (MMSE) delay estimate [11] together with an indication of its reliability. Delay mean and variance are then converted into a distance information by scaling them by the speed of light:…”

“…The position estimation step is very similar to the one developed in [10]. One instance of the position estimation block is implemented per base station at the fusion center.…”

“…While DPE turns out to be the optimal localization solution, it suffers from a significant complexity increase and requires the full knowledge of the received signal at the central fusion center. We recently demonstrated that the performance of DPE can be approached by iterating between the two conventional steps [10]. This iterative approach allows to reduce the computational burden and the communication overhead compared to DPE but is up to now only designed for ideal line-of-sight propagation conditions.…”

“…This iterative approach allows to reduce the computational burden and the communication overhead compared to DPE but is up to now only designed for ideal line-of-sight propagation conditions. In this paper, we therefore propose to extend the iterative localization method of [10] to be able to operate in a rich multipath environment, typical of dense urban and indoor environments. We resort to the approach developed in [6], [7] to estimate the propagation delay of the signal using some prior knowledge of the channel PDP.…”