A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives

Efficient localization plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would contribute to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities for enhancing localization of UAVs and UGVs. In this paper, we review the radio frequency (RF) based approaches for localization. We review the RF features that can be utilized for localization and investigate the current methods suitable for Unmanned vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localization for both UAVs and UGVs is examined, and the envisioned 5G NR for localization enhancement, and the future research direction are explored

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

Passive round-trip-time positioning in dense ieee 802.11 networks

The search for a unique and globally available location solution has attracted researchers for a long time. However, a solution for indoor scenarios, where high accuracy is needed, and Global Positioning System (GPS) is not available, has not been found yet. Despite the number of proposals in the literature, some require too long a calibration time for constructing the fingerprinting map, some rely on the periodic broadcast of positioning information that may downgrade the data communication channel, while others require specific hardware components that are not expected to be carried on commercial off-the-shelf (COTS) wireless devices. The scalability of the location solution is another key parameter for next-generation internet of things (IoT) and 5G scenarios. A passive solution for indoor positioning of WiFi devices is first introduced here, which merges a time-difference of arrival (TDOA) algorithm with the novel fine time measurements (FTM) introduced in IEEE 802.11mc. A proof of concept of the WiFi passive TDOA algorithm is detailed in this paper, together with a thorough discussion on the requirements of the proposed algorithmThis work was funded by the Spanish Government and European Regional Development Fund (ERDF) through Comisión Interministerial de Ciencia y Tecnología (CICYT) under Project PGC2018-099945-B-I00.Peer ReviewedPostprint (published version

A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications

The commercial availability of low-cost millimeter wave (mmWave) communication and radar devices is starting to improve the penetration of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedented accuracy, especially with respect to sub-6 GHz commercial-grade devices. This paper surveys the state of the art in device-based localization and device-free sensing using mmWave communication and radar devices, with a focus on indoor deployments. We first overview key concepts about mmWave signal propagation and system design. Then, we provide a detailed account of approaches and algorithms for localization and sensing enabled by mmWaves. We consider several dimensions in our analysis, including the main objectives, techniques, and performance of each work, whether each research reached some degree of implementation, and which hardware platforms were used for this purpose. We conclude by discussing that better algorithms for consumer-grade devices, data fusion methods for dense deployments, as well as an educated application of machine learning methods are promising, relevant and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys & Tutorials (IEEE COMST

Localization as a Key Enabler of 6G Wireless Systems: A Comprehensive Survey and an Outlook

peer reviewedWhen fully implemented, sixth generation (6G) wireless systems will constitute intelligent wireless networks that enable not only ubiquitous communication but also high-Accuracy localization services. They will be the driving force behind this transformation by introducing a new set of characteristics and service capabilities in which location will coexist with communication while sharing available resources. To that purpose, this survey investigates the envisioned applications and use cases of localization in future 6G wireless systems, while analyzing the impact of the major technology enablers. Afterwards, system models for millimeter wave, terahertz and visible light positioning that take into account both line-of-sight (LOS) and non-LOS channels are presented, while localization key performance indicators are revisited alongside mathematical definitions. Moreover, a detailed review of the state of the art conventional and learning-based localization techniques is conducted. Furthermore, the localization problem is formulated, the wireless system design is considered and the optimization of both is investigated. Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems

A Review of Radio Frequency Based Localisation for Aerial and Ground Robots with 5G Future Perspectives

Efficient localisation plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned Aerial Vehicles (UAVs), which contributes to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities to enhance the localisation of UAVs and UGVs. In this paper, we review radio frequency (RF)-based approaches to localisation. We review the RF features that can be utilized for localisation and investigate the current methods suitable for Unmanned Vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localisation for both UAVs and UGVs is examined, and the envisioned 5G NR for localisation enhancement, and the future research direction are explored

Role of Reconfigurable Intelligent Surfaces in 6G Radio Localization: Recent Developments, Opportunities, Challenges, and Applications

Reconfigurable intelligent surfaces (RISs) are seen as a key enabler low-cost and energy-efficient technology for 6G radio communication and localization. In this paper, we aim to provide a comprehensive overview of the current research progress on the RIS technology in radio localization for 6G. Particularly, we discuss the RIS-assisted radio localization taxonomy and review the studies of RIS-assisted radio localization for different network scenarios, bands of transmission, deployment environments, as well as near-field operations. Based on this review, we highlight the future research directions, associated technical challenges, real-world applications, and limitations of RIS-assisted radio localization