Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation

Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands. In this article, we address the radio-based sensing and environment mapping prospect with specific emphasis on the user equipment (UE) side. We first describe an efficient l1-regularized least-squares (LS) approach to obtain sparse range--angle charts at individual measurement or sensing locations. For the subsequent environment mapping, we then introduce a novel state model for mapping diffuse and specular scattering, which allows efficient tracking of individual scatterers over time using interacting multiple model (IMM) extended Kalman filter and smoother. We provide extensive numerical indoor mapping results at the 28~GHz band deploying OFDM-based 5G NR uplink waveform with 400~MHz channel bandwidth, covering both accurate ray-tracing based as well as actual RF measurement results. The results illustrate the superiority of the dynamic tracking-based solutions, compared to static reference methods, while overall demonstrate the excellent prospects of radio-based mobile environment sensing and mapping in future mm-wave networks

Millimeter-wave Mobile Sensing and Environment Mapping : Models, Algorithms and Validation

Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands. In this article, we address the radio-based sensing and environment mapping prospect with specific emphasis on the user equipment (UE) side. We first describe an efficient ℓ1 -regularized least-squares (LS) approach to obtain sparse range--angle charts at individual measurement or sensing locations. For the subsequent environment mapping, we then introduce a novel state model for mapping diffuse and specular scattering, which allows efficient tracking of individual scatterers over time using interacting multiple model (IMM) extended Kalman filter and smoother. Also the related measurement selection and data association problems are addressed. We provide extensive numerical indoor mapping results at the 28~GHz band deploying OFDM-based 5G NR uplink waveform with 400~MHz channel bandwidth, covering both accurate ray-tracing based as well as actual RF measurement results. The results illustrate the superiority of the dynamic tracking-based solutions, compared to static reference methods, while overall demonstrate the excellent prospects of radio-based mobile environment sensing and mapping in future mm-wave networks.publishedVersionPeer reviewe

A multi-wavelength polarimetric study of the blazar CTA 102 during a Gamma-ray flare in 2012

We perform a multi-wavelength polarimetric study of the quasar CTA 102 during an extraordinarily bright $\gamma$-ray outburst detected by the {\it Fermi} Large Area Telescope in September-October 2012 when the source reached a flux of F$_{>100~\mathrm{MeV}} =5.2\pm0.4\times10^{-6}$ photons cm$^{-2}$ s$^{-1}$. At the same time the source displayed an unprecedented optical and NIR outburst. We study the evolution of the parsec scale jet with ultra-high angular resolution through a sequence of 80 total and polarized intensity Very Long Baseline Array images at 43 GHz, covering the observing period from June 2007 to June 2014. We find that the $\gamma$-ray outburst is coincident with flares at all the other frequencies and is related to the passage of a new superluminal knot through the radio core. The powerful $\gamma$-ray emission is associated with a change in direction of the jet, which became oriented more closely to our line of sight ($\theta\sim$1.2$^{\circ}$) during the ejection of the knot and the $\gamma$-ray outburst. During the flare, the optical polarized emission displays intra-day variability and a clear clockwise rotation of EVPAs, which we associate with the path followed by the knot as it moves along helical magnetic field lines, although a random walk of the EVPA caused by a turbulent magnetic field cannot be ruled out. We locate the $\gamma$-ray outburst a short distance downstream of the radio core, parsecs from the black hole. This suggests that synchrotron self-Compton scattering of near-infrared to ultraviolet photons is the probable mechanism for the $\gamma$-ray production.Comment: Accepted for publication in The Astrophysical Journa

Design Considerations of Dedicated and Aerial 5G Networks for Enhanced Positioning Services

Dedicated and aerial fifth generation (5G) networks, here called 5G overlay networks, are envisaged to enhance existing positioning services, when combined with global navigation satellite systems (GNSS) and other sensors. There is a need for accurate and timely positioning in safety-critical automotive and aerial applications, such as advanced warning systems or in urban air mobility (UAM). Today, these high-accuracy demands can partially be satisfied by GNSS, though not in dense urban conditions or under GNSS threats (e.g. interference, jamming or spoofing). Temporary and on-demand 5G network deployments using ground and flying base stations (BSs) are indeed a novel solution to exploit hybrid GNSS, 5G and sensor algorithms for the provision of accurate three-dimensional (3D) position and motion information, especially for challenging urban and suburban scenarios. Thus, this paper first analyzes the positioning technologies available, including signals, positioning methods, algorithms and architectures. Then, design considerations of 5G overlay networks are discussed, by including simulation results on the 5G signal bandwidth, antenna array and network deployment.Peer reviewe

3D Positioning and Tracking in 5G Networks with Kalman Filtering

The emerging 5G mobile network will become a unique infrastructure that encompasses the cutting-edge technology with visionary applications. Unprecedented data rates, latency and capacity are going to be a game-changer for a wide range of industries. These new capabilities also promise to overturn everyday life routines of normal people: autonomous traffic and fully automated manufacturing/farming, tele-medicine and remote presence, extended sensor networks and augmented reality - all these novelties are going to turn the world into something only science fiction could imagine. The ground-breaking advances come at a cost. 5G is shifting the communications into the millimeter-wave (mmW) range which has never been used for this purpose before. MmW links must employ small cells and utilize highly directional antennas in order to counteract high path-loss at these frequencies. In addition to that, the dynamic scenarios imply that the 5G base stations (BSs) are going to serve users with fast and complex mobility, which is a challenge for a system with beamforming. The answers to these problem are multi-connectivity and location-aware communication. The 5G network requires embedded positioning system that can be used independently of other positioning techniques, create little overheads and ideally provide added-value positioning services to other players on the market. We propose a positioning method that uses network's own reference signals (RSs) to provide accurate positioning and tracking of the mobile users. Our method utilizes multi-connectivity and beamforming in order to estimate direction of departure (DoD) of the RSs from all connected BSs, and then converts the DoD angle estimates into positions. Moreover, most of the computational load is shifted from the user to the BSs and the core network, which helps to save user's battery. This stand-alone positioning method shows a potential to provide accuracy that covers needs for most mobile positioning applications envisioned for the 5G wireless networks

3D Positioning and Tracking in 5G Networks with Kalman Filtering

The emerging 5G mobile network will become a unique infrastructure that encompasses the cutting-edge technology with visionary applications. Unprecedented data rates, latency and capacity are going to be a game-changer for a wide range of industries. These new capabilities also promise to overturn everyday life routines of normal people: autonomous traffic and fully automated manufacturing/farming, tele-medicine and remote presence, extended sensor networks and augmented reality - all these novelties are going to turn the world into something only science fiction could imagine. The ground-breaking advances come at a cost. 5G is shifting the communications into the millimeter-wave (mmW) range which has never been used for this purpose before. MmW links must employ small cells and utilize highly directional antennas in order to counteract high path-loss at these frequencies. In addition to that, the dynamic scenarios imply that the 5G base stations (BSs) are going to serve users with fast and complex mobility, which is a challenge for a system with beamforming. The answers to these problem are multi-connectivity and location-aware communication. The 5G network requires embedded positioning system that can be used independently of other positioning techniques, create little overheads and ideally provide added-value positioning services to other players on the market. We propose a positioning method that uses network's own reference signals (RSs) to provide accurate positioning and tracking of the mobile users. Our method utilizes multi-connectivity and beamforming in order to estimate direction of departure (DoD) of the RSs from all connected BSs, and then converts the DoD angle estimates into positions. Moreover, most of the computational load is shifted from the user to the BSs and the core network, which helps to save user's battery. This stand-alone positioning method shows a potential to provide accuracy that covers needs for most mobile positioning applications envisioned for the 5G wireless networks

Channel Parameter Estimation and TX Positioning with Multi-Beam Fusion in 5G mmWave Networks

Since the beginning of the fifth generation (5G) standardization process, positioning has been considered as a key element in future cellular networks. In order to perform accurate positioning, solutions for estimating and processing location-related measurements such as direction of arrival (DoA) and time of arrival (ToA) for various use-cases need to be developed. In this paper, building on the existing 5G new radio (NR) specifications and millimeter wave frequencies, we propose a novel estimation and tracking solution of the DoA and ToA such that only analog/radio frequency (RF) beamforming-based observations are utilized. In addition to the proposed extended Kalman filter (EKF)-based estimation and tracking approach, we derive Cramér-Rao lower bounds (CRLBs) for the considered RF multi-beam system, and propose an information-based criterion for selecting the necessary beams for the estimation process in order to provide highly accurate performance with feasible computational complexity. The performance of the proposed method is evaluated using extensive ray-tracing simulations and numerical evaluations, and the results are compared with other estimation and beam-selection approaches. Based on the obtained results, beam-selection at the receiver can have a significant impact on the DoA and ToA estimation performance as well as on the subsequent positioning accuracy. Finally, we demonstrate the highly accurate performance of the methods when extended to joint multi-receiver-based device positioning and clock synchronization.publishedVersionPeer reviewe

User Positioning in mmW 5G Networks Using Beam-RSRP Measurements and Kalman Filtering

In this paper, we exploit the 3D-beamforming features of multiantenna equipment employed in fifth generation (5G) networks, operating in the millimeter wave (mmW) band, for accurate positioning and tracking of users. We consider sequential estimation of users' positions, and propose a two-stage extended Kalman filter (EKF) that is based on reference signal received power (RSRP) measurements. In particular, beamformed downlink (DL) reference signals (RSs) are transmitted by multiple base stations (BSs) and measured by user equipments (UEs) employing receive beamforming. The so-obtained beam-RSRP (BRSRP) measurements are reported to the BSs where the corresponding directions of departure (DoDs) are sequentially estimated by a novel EKF. Such angle estimates from multiple BSs are subsequently fused on a central entity into 3D position estimates of UEs by means of another (second-stage) EKF. The proposed positioning scheme is scalable since the computational burden is shared among different network entities, namely transmission/reception points (TRPs) and 5G-NR Node B (gNB), and may be accomplished with the signalling currently specified for 5G. We assess the performance of the proposed algorithm on a realistic outdoor 5G deployment with a detailed ray tracing propagation model based on the METIS Madrid map. Numerical results with a system operating at 39 GHz show that sub-meter 3D positioning accuracy is achievable in future mmW 5G networks.acceptedVersionPeer reviewe

Dynamic Beam Selection for Beam-RSRP Based Direction Finding in mmW 5G Networks

This paper considers direction-finding in millimeter wave (mmW) fifth generation (5G) networks by means of beam-based downlink (DL) reference signal received power (RSRP) measurements and subsequent reporting. In particular, we propose two methods that allow user equipments (UEs) to select, in an independent and dynamic manner, the most-relevant beam-RSRP (BRSRP) measurements as a trade-off between angle-related information and load of the feedback channel. A likelihood ratio (LR)-test is derived in which the hypothesis for “noise-only” BRSRP measurement is compared to that of “reference signal (RS)-plus-noise” observations, under a given significance level. A power threshold based method is also proposed in which the BRSRP measurements are compared to a threshold proportional to the noise power. Such a noise variance is estimated at each UE independently. The performance of the proposed beam selection schemes is assessed by means of an extended Kalman filter (EKF) tracking the direction of departure (DoD) of the line-of-sight (LoS) path between base stations (BSs) and a UE. Extensive numerical results are provided on a realistic mmW 5G outdoor deployment scenario operating at 39 GHz and with a ray-tracing propagation model based on the METIS Madrid grid.acceptedVersionPeer reviewe

Localization and Tracking in mmWave Radio Networks using Beam-Based DoD Measurements

3D-beamforming capabilities of multiantenna equipments in fifth generation (5G) networks, operating in the millimeter wave (mmW) band, allow for accurate positioning and tracking of users. In this paper, we propose a method for 3D positioning and tracking of moving user equipments (UEs) in 5G mmW networks based on downlink (DL) reference signals (RSs) and maximum ratio combining of subcarriers. In particular, we consider a system in which base stations (BSs) transmit beamformed DL RSs in a periodic manner and UEs exploit such RSs for estimating the BS-UE beam-pair gains by coherently combining all of the available subcarriers. This is achieved by a novel maximum likelihood (ML) estimator for the beam-pair gain. These beam-pair gain estimates are then reported back to the BSs, where they are used to estimate the direction of departure (DoD) of the DL RSs by a novel extended Kalman filter (EKF). The obtained DoD estimates from all available BSs are fused into a UE position estimate in a central unit of the considered network by a second stage EKF. Hence, the computational burden is distributed among different network entities. The proposed positioning algorithm may be implemented with minor modifications to the signalling scheme currently specified for the first phase (Rel. 15) of 3GPP 5G New Radio (NR) system. The performance of this positioning scheme is evaluated in a realistic ray-tracing based outdoor scenario resembling an automated truck platooning in a cargo port setting.acceptedVersionPeer reviewe