Performance Analysis of Hybrid 5G-GNSS Localization

\ua9 2018 IEEE. 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

Novel Solution for Multi-connectivity 5G-mmW Positioning

\ua9 2018 IEEE. The forthcoming fifth generation (5G) systems with high beamforming gain antenna units, millimeter-wave (mmWave) frequency bands together with massive Multiple Input Multiple Output (MIMO) techniques are key components for accurate positioning methods. In this paper, we propose the positioning technique that is relying on the sparsity in the MIMO-OFDM channel in time and spatial domains, together with effective beamforming methods. We will study the proposed solution in a multi-connectivity context, which has been considered so far for the purpose of improving the user equipment (UE) communication data rate. We utilize the multi-connectivity for positioning, in order to improve robustness to measurement errors and increase positioning service continuity. In particular, we show that when a UE that has connectivity to more base stations, the total power and delay needed for positioning can be reduced

5G mmwave positioning for vehicular networks

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

Severe osteomyelitis caused by Myceliophthora thermophila after a pitchfork injury

BACKGROUND: Traumatic injuries occurring in agricultural settings are often associated with infections caused by unusual organisms. Such agents may be difficult to isolate, identify, and treat effectively. CASE REPORT: A 4-year-old boy developed an extensive infection of his knee and distal femur following a barnyard pitchfork injury. Ultimately the primary infecting agent was determined to be Myceliophthora thermophila, a thermophilic melanized hyphomycete, rarely associated with human infection, found in animal excreta. Because of resistance to standard antifungal agents including amphotericin B and caspofungin, therapy was instituted with a prolonged course of terbinafine and voriconazole. Voriconazole blood levels demonstrated that the patient required a drug dosage (13.4 mg/kg) several fold greater than that recommended for adults in order to attain therapeutic blood levels. CONCLUSION: Unusual pathogens should be sought following traumatic farm injuries. Pharmacokinetic studies may be of critical importance when utilizing antifungal therapy with agents for which little information exists regarding drug metabolism in children

Methodology for simulating 5G and GNSS high-accuracy positioning

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

Positioning in wireless networks:non-cooperative and cooperative algorithms

Abstract In the last few years, location-awareness has emerged as a key technology for the future development of mobile, ad hoc and sensor networks. Thanks to location information, several network optimization strategies as well as services can be developed. However, the problem of determining accurate location, i.e. positioning, is still a challenge and robust algorithms are yet to be developed. In this thesis, we focus on the development of distance-based non-cooperative and cooperative algorithms, which is derived based on a non-parametric non- Bayesian framework, specifically with a Weighted Least Square (WLS) optimization. From a theoretic perspective, we study the WLS problem and establish the optimality through the relationship with a Maximum Likelihood (ML) estimator. We investigate the fundamental limits and derive the consistency conditions by creating a connection between Euclidean geometry and inference theory. Furthermore, we derive the closed-form expression of a distance-model based Cramér-Rao Lower Bound (CRLB), as well as the formulas, that characterize information coupling in the Fisher information matrix. Non-cooperative positioning is addressed as follows. We propose a novel framework, namely the Distance Contraction, to develop robust non-cooperative positioning techniques. We prove that distance contraction can mitigate the global minimum problem and structured distance contraction yields nearly optimal performance in severe channel conditions. Based on these results, we show how classic algorithms such as the Weighted Centroid (WC) and the Non-Linear Least Square (NLS) can be modified to cope with biased ranging. For cooperative positioning, we derive a novel, low complexity and nearly optimal global optimization algorithm, namely the Range-Global Distance Continuation method, to use in centralized and distributed positioning schemes. We propose an effective weighting strategy to cope with biased measurements, which consists of a dispersion weight that captures the effect of noise while maximizing the diversity of the information, and a geometric-based penalty weight, that penalizes the assumption of bias-free measurements. Finally, we show the results of a positioning test where we employ the proposed algorithms and utilize commercial Ultra-Wideband (UWB) devices.Tiivistelmä Viime vuosina paikkatietoisuudesta on tullut eräs merkittävä avainteknologia mobiili- ja sensoriverkkojen tulevaisuuden kehitykselle. Paikkatieto mahdollistaa useiden verkko-optimointistrategioiden sekä palveluiden kehittämisen. Kuitenkin tarkan paikkatiedon määrittäminen, esimerkiksi kohteen koordinaattien, on edelleen vaativa tehtävä ja robustit algoritmit vaativat kehittämistä. Tässä väitöskirjassa keskitytään etäisyyspohjaisten, yhteistoiminnallisten sekä ei-yhteistoiminnallisten, algoritmien kehittämiseen. Algoritmit pohjautuvat parametrittömään ei-bayesilaiseen viitekehykseen, erityisesti painotetun pienimmän neliösumman (WLS) optimointimenetelmään. Väitöskirjassa tutkitaan WLS ongelmaa teoreettisesti ja osoitetaan sen optimaalisuus todeksi tarkastelemalla sen suhdetta suurimman todennäköisyyden (ML) estimaattoriin. Lisäksi tässä työssä tutkitaan perustavanlaatuisia raja-arvoja sekä johdetaan yhtäpitävyysehdot luomalla yhteys euklidisen geometrian ja inferenssiteorian välille. Väitöskirjassa myös johdetaan suljettu ilmaisu etäisyyspohjaiselle Cramér-Rao -alarajalle (CRLB) sekä esitetään yhtälöt, jotka karakterisoivat informaation liittämisen Fisherin informaatiomatriisiin. Väitöskirjassa ehdotetaan uutta viitekehystä, nimeltään etäisyyden supistaminen, robustin ei-yhteistoiminnallisen paikannustekniikan perustaksi. Tässä työssä todistetaan, että etäisyyden supistaminen pienentää globaali minimi -ongelmaa ja jäsennetty etäisyyden supistaminen johtaa lähes optimaaliseen suorituskykyyn vaikeissa radiokanavan olosuhteissa. Näiden tulosten pohjalta väitöskirjassa esitetään, kuinka klassiset algoritmit, kuten painotetun keskipisteen (WC) sekä epälineaarinen pienimmän neliösumman (NLS) menetelmät, voidaan muokata ottamaan huomioon etäisyysmittauksen harha. Yhteistoiminnalliseksi paikannusmenetelmäksi johdetaan uusi, lähes optimaalinen algoritmi, joka on kompleksisuudeltaan matala. Algoritmi on etäisyyspohjainen globaalin optimoinnin menetelmä ja sitä käytetään keskitetyissä ja hajautetuissa paikannusjärjestelmissä. Lisäksi tässä työssä ehdotetaan tehokasta painotusstrategiaa ottamaan huomioon mittausharha. Strategia pitää sisällään dispersiopainon, joka tallentaa häiriön aiheuttaman vaikutuksen maksimoiden samalla informaation hajonnan, sekä geometrisen sakkokertoimen, joka rankaisee harhattomuuden ennakko-oletuksesta. Lopuksi väitöskirjassa esitetään tulokset kokeellisista mittauksista, joissa ehdotettuja algoritmeja käytettiin kaupallisissa erittäin laajakaistaisissa (UWB) laitteissa

On the trade-off between positioning and data rate for mm-Wave communication

Abstract Millimeter wave (mmW) communication systems have the potential to increase data rates with low-latency, highly directional communication links. Due to the geometric nature of the propagation, mmW signals can also be used for accurate positioning. This paper explores the trade-off between communication rate and positioning quality in mmW systems. We show how rate and positioning quality interact as a function of bandwidth, number of antennas, and receiver location

On the utilization of MIMO-OFDM channel sparsity for accurate positioning

Abstract Recent results have revealed that MIMO channels at high carrier frequencies exhibit sparsity structure, i.e., a few dominant propagation paths. Also channel parameters, namely angular information and propagation delay can be modelled with the physical location of the transmitter, receiver and scatters. In this paper, we leverage these features into the development of a single base-station localization algorithm, and show that the location of an unknown device can be estimated with an accuracy below a meter based on pilot signalling with a OFDM transmission. The method relies on the utilization of the “Adaptive-LASSO” optimization method, in which an ℓ1-based minimization problem is solved by adapting the sparsifying matrix (dictionary) and the sparse vector jointly. Then the location of the device is estimated from the parameters of the sparsifying matrix. Finally, the positioning method is evaluated in different channel setting utilizing a ray-tracing channel model at 28GHz

Multihop versus message-passing: a complexity and accuracy comparison for distributed localization

In this paper we present the multihop-approach as a complexity and energy-efficient alternative to the classical message-passing scheme in distributed localization for wireless sensor networks (WSNs). While it is the approach currently most often considered for cooperative localization, message-passing localization algorithms (MPLAs) rely on the “diffusion” of the known location of a few nodes (anchors) to the entire network via a typically large number of message exchanges amongst neighbors, resulting in high communications costs, low robustness to mobility, little location privacy to end users and slow convergence. In contrast, in multihop localization algorithms (MHLAs) each node is localized based on the multihop distances between itself and anchors, such that substantially lower communication costs, intrinsic privacy and faster location-acquisition are inherently achieved. Based on the fact that the Cramer-Rao lower bounds (CRLBs) of MHLAs and MPLAs are comparable in most cases of interest, we demonstrated via simulations that from a complexity and energy-efficiency point of view, MHLAs with higher signalto- noise ratio (SNR) but “near-zero” communication costs are a valid alternative to MPLAs