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PP.3

"Breaking the Gridlock of Spatial Correlation in GPS-aided IEEE 802.11p-based Cooperative Positioning"

Authors: Gia-Minh Hoang, Benoit Denis, Jerome Haerri, Dirk T.M. Slock

HIGHTS Partners: CEA-Leti, EURECOM

Published in: IEEE Transactions on Vehicular Technology ( Volume: 65, Issue: 12, Dec. 2016 )

Date of Publication: 10 August 2016

Page(s): 9554 - 9569

Abstract

Spatial correlations found in vehicular mobility are jeopardizing the precision level of cooperative positioning for future Cooperative Intelligent Transport System (C-ITS) applications. Bayesian filters traditionally assume independence of the measurement noise terms over space between different vehicles and over time at each vehicle, whereas they are actually correlated due to the local continuity of physical propagation phenomena (e.g., shadowing, multipath, etc.) under highly constrained vehicular mobility. In this paper, we break this gridlock by proposing an innovative data fusion framework capable of mitigating these effects to maintain the positioning precision level under severely correlated environments. We first illustrate the dramatic impact of correlated noise affecting both global positioning system and vehicle-to-vehicle (V2V) received power observations. Then, we propose a new generic data fusion framework based on a particle filter supporting three complementary methods to decorrelate measurement noises in a globally asynchronous context. Compared with conventional cooperative positioning, simulations performed in canonical vehicular scenarios (highway, urban canyon, tunnel) show that our proposed approach could provide up to 60% precision improvement in correlated environments, while matching by less than 15-20% deviation, an optimal cooperative positioning scheme considered under independent measurements.

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PP.5

"Coordination of Cooperative Autonomous Vehicles: Toward safer and more efficient road transportation"

Authors: Robert Hult, Gabriel R. Campos, Erik Steinmetz, Lars Hammarstrand, Paolo Falcone, Henk Wymeersch

HIGHTS Partners: Chalmers

Published in: IEEE Signal Processing Magazine ( Volume: 33, Issue: 6, Nov. 2016 )

Page(s): 74 - 84

Date of Publication: 04 November 2016

Abstract

While intelligent transportation systems come in many shapes and sizes, arguably the most transformational realization will be the autonomous vehicle. As such vehicles become commercially available in the coming years, first on dedicated roads and under specific conditions, and later on all public roads at all times, a phase transition will occur. Once a sufficient number of autonomous vehicles is deployed, the opportunity for explicit coordination appears. This article treats this challenging network control problem, which lies at the intersection of control theory, signal processing, and wireless communication. We provide an overview of the state of the art, while at the same time highlighting key research directions for the coming decades.

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PP.19

"Multipath Assisted Positioning with Simultaneous Localization and Mapping"

Authors: Christian Gentner, Thomas Jost, Wei Wang, Siwei Zhang, Armin Dammann, Uwe-Carsten Fiebig

HIGHTS Partners: DLR

Published in: IEEE Transactions on Wireless Communications ( Volume: 15, Issue: 9, Sept. 2016 )

Page(s): 6104 - 6117

Date of Publication: 08 June 2016

Abstract

This paper describes an algorithm that exploits multipath propagation for position estimation of mobile receivers. We apply a novel algorithm based on recursive Bayesian filtering, named Channel-SLAM. This approach treats multipath components as signals emitted from virtual transmitters, which are time synchronized to the physical transmitter and static in their positions. Contrary to other approaches, Channel-SLAM considers also paths occurring due to multiple numbers of reflections or scattering as well as the combination. Hence, each received multipath component increases the number of transmitters resulting in a more accurate position estimate or enabling positioning when the number of physical transmitters is insufficient. Channel-SLAM estimates the receiver position and the positions of the virtual transmitters simultaneously; hence, the approach does not require any prior information, such as a room-layout or a database for fingerprinting. The only prior knowledge needed is the physical transmitter position as well as the initial receiver position and moving direction. Based on simulations, the position precision of Channel-SLAM is evaluated by a comparison to simplified algorithms and to the posterior Cramér-Rao lower bound. Furthermore, this paper shows the performance of Channel-SLAM based on measurements in an indoor scenario with only a single physical transmitter.

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PP.21

"A Self-Organizing Frequency Approach to 802.11p Channel Estimation"

Authors: Razvan-Andrei Stoica, Stefano Severi, Giuseppe Thadeu Freitas de Abreu

HIGHTS Partners: Jacobs

Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: PP, Issue: 99 )

Page(s): 1 - 13

Date of Publication: 20 October 2016

Abstract

We consider in this paper the mobility challenges that emerge in the context of vehicular wireless communications. Specifically, we research the problem of estimating the mobile doubly selective channels for the IEEE 802.11p orthogonal frequency-division multiplexing-based communication. To mitigate some of the major challenges imposed by the time-varying vehicular environments and to solve this estimation problem a new standard-compliant channel estimator block is proposed. The estimator structure is an innovative construct stemming from the idea of subcarrier frequencies self-organization, which leverages intersubbands connections through decision directed feedback, spectral smoothing, and time tracking. Comparisons between the new method and existing alternatives already indicate that the proposed scheme outperforms the latter. Furthermore, the bit error rate (BER) and frame error rate (FER) performance of the new estimator is close to the one with perfect channel state information for low and medium SNRs.

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PP.26

"Secrecy Rate Analysis in Multi-Tier Heterogeneous Networks Over Generalized Fading Model"

Authors: Yohannes Jote Tolossa, Satyanarayana Vuppala, Giuseppe Abreu

HIGHTS Partners: Jacobs

Published in: IEEE Internet of Things Journal ( Volume: PP, Issue: 99 )

Page(s): 1 - 1

Date of Publication: 11 November 2016

Abstract

In this paper, the secrecy rate characteristics of multi-tier downlink heterogeneous networks under generalised fading model is investigated for two types of base-station (BS)- user(s) association scenarios. Each tier within the network has a single multi-antenna BS that intends to serve multiple single antenna mobile users. These users are assumed to be distributed according to homogeneous Poisson point process (PPP) with particular density parameter. Single antenna eavesdroppers which intend to wiretap the communication between the chosen BS and intended mobile user are also assumed to coexist within the network distributed as PPP with different intensity parameter. We have adopted the maximum received path gain, rather than distance, as a metric to describe the association scenario between a BS and typical user. Therefore, a typical user associates itself with (a) a BS that provides the user with the maximum path gain or (b) any potential BS that provides the k-th maximum path gain to the user. Using stochastic geometry as a tool, the received path gain distributions and the achievable average secrecy rate expressions from the perspective of association with the ‘best’ and the k-th ‘best’ BS are analysed analytically. Tractable numerical and simulation results are presented under various assumptions of fading scenario, path loss exponent, eavesdropper density and antenna figures to support the lemmas and propositions stated within the paper.

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