hh.sePublications
Change search
Refine search result
1 - 12 of 12
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Belyaev, Evgeny
    et al.
    Tampere University of Technology, Tampere, Finland.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Surak, Adam
    Tampere University of Technology, Tampere, Finland.
    Gabbouj, Moncef
    Tampere University of Technology, Tampere, Finland.
    Jonsson, Magnus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Egiazarian, Karen
    Tampere University of Technology, Tampere, Finland.
    Robust vehicle-to-infrastructure video transmission for road surveillance applications2015In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 7, p. 2991-3003Article in journal (Refereed)
    Abstract [en]

    IEEE 802.11p vehicle-to-vehicle and vehicle-to-infrastructure communication technology is currently an emerging research topic in both industry and academia. Respective spectrum allocation of 10 MHz channels in the 5.9 GHz band for USA and Europe allows considering inter-vehicle transmission of a live video information as a basis, which enables a new class of safety and infotainment automotive applications such as road video surveillance. This paper is first of its kind where such a video transmission system is developed and experimentally validated. We propose a low-complexity unequal packet loss protection and rate control algorithms for a scalable video coding based on the three-dimensional discrete wavelet transform. We show that in comparison with a scalable extension of the H.264/AVC standard the new codec is less sensitive to packet losses, has less computational complexity and provides comparable performance in case of unequal packet loss protection. It is specially designed to cope with severe channel fading typical for dynamic vehicular environments and has a low complexity, making it a feasible solution for real-time automotive surveillance applications. Extensive measurements obtained in realistic city traffic scenarios demonstrate that good visual quality and continuous playback is possible when the moving vehicle is in the radius of 600 meters from the roadside unit. ©2014 IEEE

  • 2.
    Bocharova, Irina
    et al.
    Department of Information Systems, St. Petersburg University of Information Technologies, Mechanics and Optics, St.-Petersburg, Russia & Institute of Computer Science, University of Tartu, Estonia.
    Kudryashov, Boris
    Department of Information Systems, St. Petersburg University of Information Technologies, Mechanics and Optics, St.-Petersburg, Russia & Institute of Computer Science, University of Tartu, Estonia.
    Rabi, Maben
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lyamin, Nikita
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Dankers, Wouter
    Volvo GTT, Goteborg, Sweden.
    Frick, Erik
    AstaZero, Hällered, Sandhult, Sweden.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Department of Electrical Engineering, Western Norway University of Applied Sciences, Bergen, Norway.
    Characterizing Packet Losses in Vehicular Networks2019In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, no 9, p. 8347-8358Article in journal (Refereed)
    Abstract [en]

    To enable testing and performance evaluation of new connected and autonomous driving functions, it is important to characterize packet losses caused by degradation in vehicular (V2X) communication channels. In this paper we suggest an approach to constructing packet loss models based on the socalled Pseudo-Markov chains (PMC). The PMC based model needs only short training sequences, has low computational complexity, and yet provides more precise approximations than known techniques. We show how to learn PMC models from either empirical records of packet receptions, or from analytical models of fluctuations in the received signal strength. In particular, we validate our approach by applying it on (i) V2X packet reception data collected from an active safety test run, which used the LTE network of the AstaZero automotive testing site in Sweden, and (ii) variants of the Rician fading channel models corresponding to two models of correlations of packet losses. We also show that initializing the Baum-Welch algorithm with a second order PMC model leads to a high accuracy model. © 2019 IEEE.

  • 3.
    Campolo, Claudia
    et al.
    Dipartimento di Informatica, Matematica, Elettronica e Trasporti, University Mediterranea of Reggio Calabria.
    Molinaro, Antonella
    Dipartimento di Informatica, Matematica, Elettronica e Trasporti, University Mediterranea of Reggio Calabria.
    Vinel, Alexey
    Department of Communications Engineering, Tampere University of Technology.
    Zhang, Yan
    Simula Research Laboratory.
    Modeling Prioritized Broadcasting in Multichannel Vehicular Networks2012In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 61, no 2, p. 687-701Article in journal (Refereed)
    Abstract [en]

    Effective data broadcasting is essential in vehicular networks not only for road-safety message dissemination but also to aid routing and cooperative driving applications through periodic beaconing and to spread network initialization advertisements that are mandatory to support infotainment applications. Broadcast data are neither acknowledged nor retransmitted in case of failure, which raises the possibility of frame loss due to channel errors and collisions with multiple simultaneous broadcasts. This paper aims at modeling periodic broadcasting on the control channel of IEEE Std. 802.11p vehicular networks with multichannel architecture. Unlike previous related work, the proposed novel analytical approach accounts for mutual influence among nodes, frequent periodic updates of broadcasted data, standard network advertisement procedures, and 802.11p prioritized channel access with multichannel-related phenomena under various link quality conditions. © 2012 IEEE.

    Download full text (pdf)
    fulltext
  • 4.
    Kaur, Kuljeet
    et al.
    Thapar University, Patiala, Punjab, India.
    Dua, Amit
    Thapar University, Patiala, Punjab, India.
    Jindal, Anish
    Thapar University, Patiala, Punjab, India.
    Kumar, Neeraj
    Thapar University, Patiala, Punjab, India.
    Singh, Mukesh
    Thapar University, Patiala, Punjab, India.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    A Novel Resource Reservation Scheme for Mobile PHEVs in V2G Environment using Game Theoretical Approach2015In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 12, p. 5653-5666Article in journal (Refereed)
    Abstract [en]

    With the widespread penetration of plug-in hybrid electric vehicles (PHEVs), the overall demand on micro-grids (MGs) may increase manifold in the near future. Unregulated power demands from PHEVs may increase the demand-supply gap at MG. Thus, in order to keep MGs stabilize, and cater the ever growing energy demands, there is a requirement of an intelligent solution to regulate, and manage PHEVs in vehicle-togrid (V2G) environment. Keeping in view the above issues, this paper proposes a novel scheme which aims to regulate PHEVs? charging, and discharging activities based on MGs? day-ahead load curves. These load curves are obtained by utilizing the existing load forecasting techniques such as-fuzzy logic (FL), and artificial neural networks (ANN). Efficient utilization of PHEVs according to these curves may play a vital role in flattening MG?s load profile. Thus, the proposed scheme works by reserving resources such as-time slots, and charging points for PHEVs during peak shaving, and valley filling. Different algorithms pertaining to resource reservation for PHEVs have also been designed. These algorithms employ the concepts of game theory, and 0/1 knapsack problem for supporting peak shaving, and valley filling respectively. Moreover, PHEVs are also utilized when there are transitions from valley filling to peak shaving areas in the load curves, and vice-versa. PHEVs involved in this process have both charging, and discharging capabilities, and are referred as dual-mode PHEVs. The proposed scheme has been tested with respect to various parameters, and its performance was found satisfactory. © 2015 IEEE

  • 5.
    Keskin, Musa Furkan
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Jiang, Fan
    Chalmers University of Technology, Gothenburg, Sweden.
    Munier, Florent
    Ericsson Research, Gothenburg, Sweden.
    Seco-Granados, Gonzalo
    Universitat Autonoma de Barcelona, Barcelona, Spain.
    Wymeersch, Henk
    Chalmers University of Technology, Gothenburg, Sweden.
    Optimal Spatial Signal Design for mmWave Positioning Under Imperfect Synchronization2022In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 71, no 5, p. 5558-5563Article in journal (Refereed)
    Abstract [en]

    We consider the problem of spatial signal design for multipath-assisted mmWave positioning under limited prior knowledge on the user's location and clock bias. We propose an optimal robust design and, based on the low-dimensional precoder structure under perfect prior knowledge, a codebook-based heuristic design with optimized beam power allocation. Through numerical results, we characterize different position-error-bound (PEB) regimes with respect to clock bias uncertainty and show that the proposed low-complexity codebook-based designs outperform the conventional directional beam codebook and achieve near-optimal PEB performance for both analog and digital architectures. © 1967-2012 IEEE

  • 6.
    Liang, Guojun
    et al.
    Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China.
    U, Kintak
    Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China.
    Ning, Xin
    Laboratory of Artificial Neural Networks and High Speed Circuits, Institute of Semiconductors, Chinese Academy of Sciences, China.
    Tiwari, Prayag
    Halmstad University, School of Information Technology.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology.
    Kumar, Neeraj
    School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India; Lebanese American University, Beirut, Lebanon; King Abdulaziz University, Jeddah, Saudi Arabia.
    Semantics-aware Dynamic Graph Convolutional Network for Traffic Flow Forecasting2023In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 72, no 6, p. 7796-7809Article in journal (Refereed)
    Abstract [en]

    Traffic flow forecasting is a challenging task due to its spatio-temporal nature and the stochastic features underlying complex traffic situations. Currently, Graph Convolutional Network (GCN) methods are among the most successful and promising approaches. However, most GCNs methods rely on a static graph structure, which is generally unable to extract the dynamic spatio-temporal relationships of traffic data and to interpret trip patterns or motivation behind traffic flows. In this paper, we propose a novel Semantics-aware Dynamic Graph Convolutional Network (SDGCN) for traffic flow forecasting. A sparse, state-sharing, hidden Markov model is applied to capture the patterns of traffic flows from sparse trajectory data; this way, latent states, as well as transition matrices that govern the observed trajectory, can be learned. Consequently, we can build dynamic Laplacian matrices adaptively by jointly considering the trip pattern and motivation of traffic flows. Moreover, high-order Laplacian matrices can be obtained by a newly designed forward algorithm of low time complexity. GCN is then employed to exploit spatial features, and Gated Recurrent Unit (GRU) is applied to exploit temporal features. We conduct extensive experiments on three real-world traffic datasets. Experimental results demonstrate that the prediction accuracy of SDGCN outperforms existing traffic flow forecasting methods. In addition, it provides better explanations of the generative Laplace matrices, making it suitable for traffic flow forecasting in large cities and providing insight into the causes of various phenomena such as traffic congestion. The code is publicly available at https://github.com/gorgen2020/SDGCN. © 2023 IEEE.

    Download full text (pdf)
    fulltext
  • 7.
    Lin, Jia-Chin
    et al.
    Department of Communication Engineering, National Central University, Taoyuan 32001, Taiwan.
    Mecklenbräuker, Christoph
    Institute of Telecommunications, Vienna University of Technology, 1040 Vienna, Austria.
    Vinel, Alexey
    Department of Communications Engineering, Tampere University of Technology, 33101 Tampere, Finland.
    Vassilaras, Spyridon
    Broadband Wireless and Sensor Networks Group, Athens Information Technology Center for Research and Education, 19002 Athens, Greece.
    Zhang, Tao
    Telcordia Technologies, Piscataway, NJ 08854, United States.
    Lo, Kuen-Rong
    Telecommunication Laboratories, Chunghwa Telecom Co., Ltd., Taoyuan 32601, Taiwan.
    Special Section on Telematics Advances for Vehicular Communication Networks2012In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 61, no 1, p. 1-2Article in journal (Refereed)
  • 8.
    Luan, Tom H.
    et al.
    Xi'an Jiaotong University, Xi'an, China.
    Chen, Cailian
    Shanghai Jiao Tong University, Shanghai, China & IEEE Globecom, Washington DC, USA.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Cai, Lin
    IEEE Globecom, Washington DC, USA & University of Victoria, Victoria, BC, Canada.
    Chen, Shanzhi
    Beijing University of Posts and Telecommunications, Beijing, China.
    Guest Editorial: Emerging Technology for 5G Enabled Vehicular Networks2016In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 10, p. 7827-7830, article id 7590151Article in journal (Refereed)
    Abstract [en]

    The papers in this special section focus on 5G mobile communication enabled vehicular networks. This section is designed to provide the academic and industrial communities an excellent venue to present the vision, research, and new solutions on the key technologies emerging for 5G enabled vehicular networks.

  • 9.
    Lyamin, Nikita
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Jonsson, Magnus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Bellalta, Boris
    Universitat Pompeu Fabra, Barcelona, Spain.
    Cooperative awareness in VANETs: On ETSI EN 302 637-2 performance2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 1, p. 17-28Article in journal (Refereed)
    Abstract [en]

    Cooperative Awareness on the road is aiming to support the road users with knowledge about the surroundings relying on the information exchange enabled by vehicular com- munications. To achieve this goal European Telecommunication Standard Institute (ETSI) delivered the standard EN 302 637-2 for Cooperative Awareness Messages (CAM). The CAM trig- gering conditions are based on the dynamics of the originating vehicle, which is checked periodically. In this paper, we show that standardized ETSI protocol may demonstrate a decrease in communication performance under several realistic mobility patterns. The potential influence of the discovered phenomena on two typical mobility scenarios is studied.

  • 10.
    Shao, Caixing
    et al.
    University of Electronic Science and Technology of China, Chengdu, China & College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, China.
    Leng, Supeng
    University of Electronic Science and Technology of China, Chengdu, China.
    Zhang, Yan
    Simula Research Laboratory, Lysaker, Norway & University of Oslo, Oslo, Norway.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Jonsson, Magnus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Performance Analysis of Connectivity Probability and Connectivity-aware MAC Protocol Design for Platoon-based VANETs2015In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 12, p. 5596-5609Article in journal (Refereed)
    Abstract [en]

    Vehicular Ad Hoc Networks (VANETs) can provide safety and non-safety applications to improve the passenger safety and comfort. Grouping vehicles into platoons in VANETs can improve road safety and reduce fuel consumption. It is critical to design an efficient Medium Access Control (MAC) protocol for Platoon-based VANETs. Moreover, because of the space and time dynamics of moving vehicles, network connectivity is an important performance metric to indicate the quality of the network communications and the satisfaction of users. Unfortunately, network connectivity is often ignored in the design of existing MAC protocols for VANETs. In this paper, we study the connectivity characteristics and present a connectivity-aware MAC protocol for platoon-based VANETs. The connectivity probabilities are analyzed for the Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication scenarios in oneway and two-way VANETs, respectively. A multi-priority Markov model is presented to derive the relationship between the connectivity probability and the system throughput. Based on variable traffic status and network connectivity, a multi-channel reservation scheme is adopted to dynamically adjust the length of the Control CHannel (CCH) interval and the Service CHannel (SCH) interval for the improvement of the system throughput. Analysis and simulation results show that the throughput increases with the connectivity probability. However, with further increase of the connectivity probability, the throughput will decrease due to numerous channel contention. © Copyright 2015 IEEE

  • 11.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology.
    Thunberg, Johan
    Halmstad University, School of Information Technology.
    Sjöberg, Katrin
    Volvo Autonomous Solutions, Göteborg, Sweden.
    Fedorov, Aleksei
    Lund University, Lund, Sweden.
    Vinel, Alexey
    Safety of Automatic Emergency Braking in Platooning2022In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 71, no 3, p. 2319-2332Article in journal (Refereed)
    Abstract [en]

    A platoon comprises a string of consecutive highly automated vehicles traveling together. Platooning allows for increased road utilization and reduced fuel consumption due to short inter-vehicular distances. Safety in terms of guaranteeing no rear-end collisions is of utmost importance for platooning systems to be deployed in practice. We compare how safely emergency braking can be handled by emerging V2V communications on the one hand and by radar-based measurements of existing AEBS on the other. We show that even under conservative assumptions on the V2V communications, such an approach significantly outperforms AEBS with an ideal radar sensor in terms of allowed inter-vehicle distances and response times. Furthermore, we design two emergency braking strategies for platooning based on V2V communications. The first braking strategy assumes centralized coordination by the leading vehicle and exploits necessary optimal conditions of a constrained optimization problem, whereas the second -- the more conservative solution -- assumes only local information and is distributed in nature. Both strategies are also compared with the AEBS.

  • 12.
    Vinel, Alexey
    et al.
    Tampere University of Technology, Department of Communications Engineering.
    Belyaev, Evgeny
    Tampere University of Technology, Department of Signal Processing.
    Egiazarian, Karen
    Tampere University of Technology, Department of Signal Processing.
    Koucheryavy, Yevgeni
    Tampere University of Technology, Department of Communications Engineering.
    An Overtaking Assistance System Based on Joint Beaconing and Real-Time Video Transmission2012In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 61, no 5, p. 2319-2329Article in journal (Refereed)
    Abstract [en]

    Overtaking on rural roads often becomes dangerous when oncoming traffic is detected by the driver too late or its speed is underestimated. Recently proposed cooperative overtaking assistance systems, which are based on Vehicular Ad hoc NETworks (VANETs), rely on either real-time video transmission or the exchange of status messages (beacons). In the first case, a video stream captured by a camera installed at the windshield of a vehicle is compressed and broadcast to any vehicles driving behind it, where it is displayed to the driver. In the second case, beacons that include position, speed, and direction are frequently broadcast by all the vehicles to ensure detection of oncoming traffic as early as possible and to issue a warning to the driver whenever needed. In this paper, we demonstrate that the performance of a video-based overtaking assistant can be significantly improved if codec channel adaptation is undertaken by exploiting information from the beacons about any forthcoming increase in the load of the multiple access channel used. The theoretical framework presented describes the basic patterns of such a coupled overtaking assistant and can serve as a useful guideline for the future practical implementation of the system. The benefits of our approach are demonstrated in relation to the practical scenario of H.264/AVC video coding and IEEE 802.11p/Wireless Access in Vehicular Environments (WAVE) intervehicle communication standards. © 2012 IEEE.

    Download full text (pdf)
    fulltext
1 - 12 of 12
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf