A Fisher Information Analysis of Joint Localization and Synchronization in Near Field

In 5G communication, arrays are used for both positioning and communication. As the arrays become larger, the far-field assumption is increasingly being violated and curvature of the wavefront should be taken into account. We explicitly contrast near-field and far-field uplink localization performance in the presence of a clock bias from a Fisher information perspective and show how a simple algorithm can provide a coarse estimate of a user's location and clock bias.Comment: Submitted to IEEE ICC 2020 Workshop

Cooperative localization with angular measurements and posterior linearization

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage of the positioning. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty, and AoA measurements noise, is analyzed

Cooperative Localization with Angular Measurements and Posterior Linearization

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty and AoA measurements noise, is analyzed.Comment: Submitted for possible publication to an IEEE conferenc

A Fisher information analysis of joint localization and synchronization in near field

In 5G communication, arrays are used for both positioning and communication. As the arrays become larger, the far-field assumption is increasingly being violated and curvature of the wavefront should be taken into account. In this paper, we use a single large linear array and relative phase measurements to perform the localization and synchronization. We explicitly contrast near-field and far-field uplink localization performance in the presence of a clock bias from a Fisher information perspective and show how a simple algorithm can provide a coarse estimate of a user\u27s location and clock bias

An Improved Method of Moments Estimator for TOA Based Localization

Abstract-Estimation accuracy and computational complexity are two major areas of consideration for localization system design. For time-of-arrival based systems, the 1st-order method of moments (MOM) least-squares (LS) estimator is simple to implement, but its performance is much worse than that of some computationally more complex estimators such as the MOM weighted LS (WLS) and nonlinear weighted LS (NLLS-WLS) estimators. In this paper, we develop an improved 1st-order MOM estimator to efficiently utilize the variances of the range measurements and the target position that, as the NLLS estimator, has a performance also approaching the Crammér-Rao lower bound but is much simpler than MOM-WLS and NLLS-WLS estimators. Index Terms-Location estimation and method of moments

Performance of location and orientation estimation in 5G mmWave systems: Uplink vs downlink

The fifth generation of mobile communications (5G) is expected to exploit the concept of location-aware communication systems. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Contributing to this understanding, we consider single-anchor localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels, for both the uplink and downlink. It is found that uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, reflected and scattered paths generally improve localization. Finally, using detailed numerical simulations, we show that mmWave systems are in theory capable of localizing a UE with sub-meter position error, and sub-degree orientation error

Error Bounds for Uplink and Downlink 3D Localization in 5G mmWave Systems

Location-aware communication systems are expected to play a pivotal part in the next generation of mobile communication networks. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Towards that, we address the uplink and downlink localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels. We also carry out a detailed analysis of the dependence of the bounds of different systems parameters. Our key findings indicate that the uplink and downlink behave differently in two distinct ways. First of all, the error bounds have different scaling factors with respect to the number of antennas in the uplink and downlink. Secondly, uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, the non-line-of-sight paths generally improve localization when a line-of-sight path exists. Finally, our numerical results show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error.Comment: This manuscripts is updated following two rounds of reviews at IEEE Transactions on Wireless Communications. More discussion is included in different parts of the paper. Results are unchanged, and are still vali

Single-Anchor Two-Way Localization Bounds for 5G mmWave Systems

Recently, millimeter-wave (mmWave) 5G localization has been shown to be to provide centimeter-level accuracy, lending itself to many location-aware applications, e.g., connected autonomous vehicles (CAVs). One assumption usually made in the investigation of localization methods is that the user equipment (UE), i.e., a CAV, and the base station (BS) are {time} synchronized. In this paper, we remove this assumption and investigate two two-way localization protocols: (i) a round-trip localization protocol (RLP), whereby the BS and UE exchange signals in two rounds of transmission and then localization is achieved using the signal received in the second round; (ii) a collaborative localization protocol (CLP), whereby localization is achieved using the signals received in the two rounds. We derive the position and orientation error bounds applying beamforming at both ends and compare them to the traditional one-way localization. Our results show that mmWave localization is mainly limited by the angular rather than the temporal estimation and that CLP significantly outperforms RLP. Our simulations also show that it is more beneficial to have more antennas at the BS than at the UE.Comment: This version is accepted for publication as a paper in the IEEE Transactions on Vehicular Technolog

A Comparison of Parametric and Sample-Based Message Representation in Cooperative Localization

Location awareness is a key enabling feature and fundamental challenge in present and future wireless networks. Most existing localization methods rely on existing infrastructure and thus lack the flexibility and robustness necessary for large ad hoc networks. In this paper, we build upon SPAWN (sum-product algorithm over a wireless network), which determines node locations through iterative message passing, but does so at a high computational cost. We compare different message representations for SPAWN in terms of performance and complexity and investigate several types of cooperation based on censoring. Our results, based on experimental data with ultra-wideband (UWB) nodes, indicate that parametric message representation combined with simple censoring can give excellent performance at relatively low complexity