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Herein, we focus on convergent 6G communication, localization and sensing systems by identifying key technology enablers, discussing their underlying challenges, implementation issues, and recommending potential solutions. Moreover, we discuss exciting new opportunities for integrated localization and sensing applications, which will disrupt traditional design principles and revolutionize the way we live, interact with our environment, and do business. Regarding potential enabling technologies, 6G will continue to develop towards even higher frequency ranges, wider bandwidths, and massive antenna arrays. In turn, this will enable sensing solutions with very fine range, Doppler, and angular resolutions, as well as localization to cm-level degree of accuracy. Besides, new materials, device types, and reconfigurable surfaces will allow network operators to reshape and control the electromagnetic response of the environment. At the same time, machine learning and artificial intelligence will leverage the unprecedented availability of data and computing resources to tackle the biggest and hardest problems in wireless communication systems. As a result, 6G will be truly intelligent wireless systems that will provide not only ubiquitous communication but also empower high accuracy localization and high-resolution sensing services. They will become the catalyst for this revolution by bringing about a unique new set of features and service capabilities, where localization and sensing will coexist with communication, continuously sharing the available resources in time, frequency, and space. This work concludes by highlighting foundational research challenges, as well as implications and opportunities related to privacy, security, and trust.

Recently, localization for 5G millimeter-wave communication systems has been shown to provide high-accuracy performance, with error being in the order of tens of centimeters. However, most of the literature assumes a high level of synchronization, which is not always the case practically. To address this matter, we investigate a distributed two-way localization protocol (DLP) that relieves the need for tight timing synchronization. We derive the position and orientation bounds, when localization is initiated and carried out by the base station. Our simulation results show that the performance of DLP is identical to that of the synchronized one-way localization. We thus conclude that the considered 5G localization is limited by the estimation of the angles rather than the delay. The results also imply that orientation estimation is more challenging than position estimation.

Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. Despite their benefits for achieving high data rate communications, their potential advantages for tracking of the location and rotation angle of the user terminals are not well investigated. A joint heuristic beam selection and user position and orientation tracking approach is proposed. First, the user location is tracked in the uplink by joint beam selection together with time-of-arrival (TOA) and angle-of-arrival (AOA) tracking at the base station (BS). Then, the user rotation angle is obtained using the location information by joint beam selection and tracking at the mobile station (MS). The beam selection, TOA and AOA tracking, at the BS and MS are performed during the data transmission phase. Numerical results demonstrate that the proposed method performs close to the estimated position and rotation angle in the training phase with reduced complexity and reduced number of required pilots for the estimation.

Recently, millimeter-wave (mmWave) 5G localization has been shown to be toprovide centimeter-level accuracy, lending itself to many location-awareapplications, e.g., connected autonomous vehicles (CAVs). One assumptionusually made in the investigation of localization methods is that the userequipment (UE), i.e., a CAV, and the base station (BS) are {time} synchronized.In this paper, we remove this assumption and investigate two two-waylocalization protocols: (i) a round-trip localization protocol (RLP), wherebythe BS and UE exchange signals in two rounds of transmission and thenlocalization is achieved using the signal received in the second round; (ii) acollaborative localization protocol (CLP), whereby localization is achievedusing the signals received in the two rounds. We derive the position andorientation error bounds applying beamforming at both ends and compare them tothe traditional one-way localization. Our results show that mmWave localizationis mainly limited by the angular rather than the temporal estimation and thatCLP significantly outperforms RLP. Our simulations also show that it is morebeneficial to have more antennas at the BS than at the UE.

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.

We consider a novel positioning solution combining millimeter wave (mmW) 5G and Global Navigation Satellite System (GNSS) technologies. The study is carried out theoretically by deriving the Fisher Information Matrix (FIM) of a combined 5G-GNSS positioning system and, subsequently, the position, rotation and clock-bias error lower bounds. We pursue a two-step approach, namely, computing first the FIM for the channel parameters, and then transforming it into the FIM of the position, rotation and clock-bias. The analysis shows advantages of the hybrid positioning in terms of i) localization accuracy, ii) coverage, iii) precise rotation estimation and iv) clock-error estimation. In other words, we demonstrate that a tight coupling of the two technologies can provide mutual benefits.

This paper focuses on the exploitation of fifth generation (5G) centimetre-wave (cmWave) and millimetre-wave (mmWave) transmissions for high-accuracy positioning, in order to complement the availability of Global Navigation Satellite Systems (GNSS) in harsh environments, such as urban canyons. Our goal is to present a representative methodology to simulate and assess their hybrid positioning capabilities over outdoor urban, suburban and rural scenarios. A novel scenario definition is proposed to integrate the network density of 5G deployments with the visibility masks of GNSS satellites, which helps to generate correlated scenarios of both technologies. Then, a generic and representative modeling of the 5G and GNSS observables is presented for snapshot positioning, which is suitable for standard protocols. The simulations results indicate that GNSS drives the achievable accuracy of its hybridisation with 5G cmWave, because non-line-of-sight (NLoS) conditions can limit the cmWave localization accuracy to around 20 m. The 5G performance is significantly improved with the use of mmWave positioning with dominant line-of-sight (LoS) conditions, which can even achieve sub-meter localization with one or more base stations. Therefore, these results show that NLoS conditions need to be weighted in 5G localization, in order to complement and outperform GNSS positioning over urban environments.

Millimeter-wave (mm-wave) signals and large antenna arrays are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are well-known, their potential advantages for accurate positioning are largely undiscovered. We derive the Cramér-Rao bound (CRB) on position and rotation angle estimation uncertainty from mm-wave signals from a single transmitter, in the presence of scatterers. We also present a novel two-stage algorithm for position and rotation angle estimation that attains the CRB for average to high signal-to-noise ratio. The algorithm is based on multiple measurement vectors matching pursuit for coarse estimation, followed by a refinement stage based on the space-alternating generalized expectation maximization algorithm. We find that accurate position and rotation angle estimation is possible using signals from a single transmitter, in either line-of-sight, non-line-of-sight, or obstructed-line-of-sight conditions.

5G technologies present a new paradigm to provide connectivity to vehicles, in support of high data-rate services, complementing existing inter-vehicle communication standards based on IEEE 802.11p. As we argue, the specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning. Hence, 5G can work in synergy with existing on-vehicle positioning and mapping systems to provide redundancy for certain applications, in particular automated driving. This article provides an overview of the evolution of cellular positioning and discusses the key properties of 5G as they relate to vehicular positioning. Open research challenges are presented.