Localization algorithm design and performance analysis in probabilistic LOS/NLOS environment

© 2016 IEEE. Non-line-of-sight (NLOS) propagation, which widely exists in wireless systems, will degrade the performance of wireless positioning system if it is not taken into consideration in the localization algorithm design. The 3rd Generation Partnership Project (3GPP) suggests that the probabilities of line-of-sight (LOS) and NLOS are related to the distance between the receiver and the transmitter. In this paper, we propose a Maximum Likelihood Estimator (MLE) for localization, which incorporates the distance dependent LOS/NLOS probabilities. Then, the position error bound is derived using Cramer-Rao Lower Bound (CRLB). Through numerical analysis, the impact of NLOS propagation on the position error bound is evaluated. The performance of our proposed algorithm is verified by real world experimental data

Towards the Next Generation of Location-Aware Communications

This thesis is motivated by the expected implementation of the next generation mobile networks (5G) from 2020, which is being designed with a radical paradigm shift towards millimeter-wave technology (mmWave). Operating in 30--300 GHz frequency band (1--10 mm wavelengths), massive antenna arrays that provide a high angular resolution, while being packed on a small area will be used. Moreover, since the abundant mmWave spectrum is barely occupied, large bandwidth allocation is possible and will enable low-error time estimation. With this high spatiotemporal resolution, mmWave technology readily lends itself to extremely accurate localization that can be harnessed in the network design and optimization, as well as utilized in many modern applications. Localization in 5G is still in early stages, and very little is known about its performance and feasibility. In this thesis, we contribute to the understanding of 5G mmWave localization by focusing on challenges pertaining to this emerging technology. Towards that, we start by considering a conventional cellular system and propose a positioning method under outdoor LOS/NLOS conditions that, although approaches the Cram\'er-Rao lower bound (CRLB), provides accuracy in the order of meters. This shows that conventional systems have limited range of location-aware applications. Next, we focus on mmWave localization in three stages. Firstly, we tackle the initial access (IA) problem, whereby user equipment (UE) attempts to establish a link with a base station (BS). The challenge in this problem stems from the high directivity of mmWave. We investigate two beamforming schemes: directional and random. Subsequently, we address 3D localization beyond IA phase. Devices nowadays have higher computational capabilities and may perform localization in the downlink. However, beamforming on the UE side is sensitive to the device orientation. Thus, we study localization in both the uplink and downlink under multipath propagation and derive the position (PEB) and orientation error bounds (OEB). We also investigate the impact of the number of antennas and the number of beams on these bounds. Finally, the above components assume that the system is synchronized. However, synchronization in communication systems is not usually tight enough for localization. Therefore, we study two-way localization as a means to alleviate the synchronization requirement and investigate two protocols: distributed (DLP) and centralized (CLP). Our results show that random-phase beamforming is more appropriate IA approach in the studied scenarios. We also observe that the uplink and downlink are not equivalent, in that the error bounds scale differently with the number of antennas, and that uplink localization is sensitive to the UE orientation, while downlink is not. Furthermore, we find that NLOS paths generally boost localization. The investigation of the two-way protocols shows that CLP outperforms DLP by a significant margin. We also observe that mmWave localization is mainly limited by angular rather than temporal estimation. In conclusion, we show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error, which asserts that mmWave will play a central role in communication network optimization and unlock opportunities that were not available in the previous generation

Hybrid and Cooperative Positioning Solutions for Wireless Networks

In this thesis, some hybrid and cooperative solutions are proposed and analyzed to locate the user in challenged scenarios, with the aim to overcome the limits of positioning systems based on single technology. The proposed approaches add hybrid and cooperative features to some conventional position estimation techniques like Kalman filter and particle filter, and fuse information from different radio frequency technologies. The concept of cooperative positioning is enhanced with hybrid technologies, in order to further increase the positioning accuracy and availability. In particular, wireless sensor networks and radio frequency identification technology are used together to enhance the collected data with position information. Terrestrial ranging techniques (i.e., ultra-wide band technology) are employed to assist the satellite-based localization in urban canyons and indoors. Moreover, some advanced positioning algorithms, such as energy efficient, cognitive tracking and non-line-of-sight identification, are studied to satisfy the different positioning requirements in harsh indoor environments. The proposed hybrid and cooperative solutions are tested and verified by first Monte Carlo simulations then real experiments. The obtained results demonstrate that the proposed solutions can increase the robustness (positioning accuracy and availability) of the current localization system

Non-line-of-sight identification and mitigation for indoor localization using ultra-wideband sensor networks

Thesis (PhD (Computer Engineering))--University of Pretoria, 2020.With the advent of Industry 4.0, indoor localization is central to many applications across multiple domains. Although impulse-radio ultra-wideband (IR-UWB) enables high precision time-of-arrival (TOA) based ranging and localization for wireless sensor networks, there are several challenges, including multi-user interference and non-line-of-sight (NLOS) conditions. NLOS conditions occur when the communication path between receiver and transmitter is obstructed, and these conditions are frequent indoors due to walls and other obstructions. To maintain location accuracy and precision similar to line-of-sight (LOS) conditions, identification and mitigation of these NLOS conditions is crucial. For identification and mitigation methods to be implemented in sensor networks, they must be of low complexity to minimize their influence on localization requirements. This thesis investigates NLOS identification and mitigation for IEEE 802.15.4a IR-UWB sensor networks. The objective of this thesis is to improve location accuracy in NLOS conditions for IR-UWB sensor networks. A comprehensive review of the state-of-the-art in NLOS identification and mitigation is conducted, and limitations of these methods with regards to the use of multiple channels, dependence on training data, mobility and complexity (particularly for applications with time constraints) are highlighted. This thesis proposes identification and mitigation methods that address the limitations found in state-of-the-art methods. A distance residual-based method for NLOS identification is proposed. Compared to conventional NLOS identification which relies on knowledge of LOS and NLOS channel statistics, or analysis of the standard deviation of range measurements over time, this identification method does not rely on these parameters. A NLOS classification method that distinguishes between through-the-wall and around-the-corner conditions using channel statistics extracted from channel impulse responses is proposed. Unlike most methods in literature that focus on distinguishing between LOS and NLOS, this method classifies NLOS conditions into through-the-wall and around-the-corner, therefore providing more context to the location estimate, and consequently enabling mitigation methods to be used for specific types of NLOS conditions. A through-the-wall ranging error mitigation method that relies on floor plans is proposed. A novel model for through-the-wall TOA ranging is proposed and experimentally evaluated. The conventional throughthe- wall TOA ranging model in literature requires many parameters which cannot be calculated in realistic scenarios. Compared to through-the-wall TOA ranging models found in literature, the proposed model relies on information from floor plans to reduce the number of unknown parameters in the model. The results show that NLOS errors caused by through-the-wall propagation are significantly mitigated with the proposed method, resulting in location accuracy which approaches the LOS case. A NLOS mitigation method which corrects location estimates affected by random ranging errors is proposed. This method relies on geometric constraints based on the fact that biases introduced by NLOS conditions in TOA range measurements are positive. The method is evaluated for cases where NLOS ranges are identifiable and cases where they are not identifiable. For the latter case, the results show that the proposed method significantly outperforms state-of-the-art optimization-based mitigation methods in terms of execution time, while retaining similar performance in terms of location accuracy.Electrical, Electronic and Computer EngineeringPhD (Computer Engineering)UnrestrictedFaculty of Engineering, Built Environment and Information TechnologySDG-09: Industry, innovation and infrastructureSDG-11:Sustainable cities and communitie