Faculty of Electrical Engineering

Czech Technical University in Prague

CTU in Prague

5Gmobile research lab

Department of Telecommunication Engineering
Technicka 2, 166 27, Prague
Tel.: +420 22435 5964
email: zdenek.becvar@fel.cvut.cz
http://5gmobile.eu/

Who we are

Zdenek Becvar
Associated profesor, team leader
Mobility management, Radio resource management, Network architecture

Pavel Mach
Postdoc researcher
Radio resource management, D2D, cognitive radio

Michal Vondra
Postdoc researcher
Mobility management, vehicular networks

Jan Plachy
PhD student
Big data in 5G networks

Alaa Almoustafa
PhD student
D2D communication in cellular networks

Tomas Dragoun
PhD student
Energy efficient mobile communication

More details about team at http://5gmobile.eu/team

Research description

5Gmobile (5GM)is a research center focusing on key aspects and challenges related to the future mobile networks and emerging wireless technologies. The aim of 5GM is to propose new approaches and provide innovative solutions enabling 5G mobile networks. The 5GM is oriented mainly on topics related to mobility and radio resource management. This includes design of control and management algorithms for handover, power control, interference management, load balancing, or energy efficient communications. The 5GM also addresses network architecture issues introduced by advanced 5G networks concept such as hybrid hierarchical architecture enabling joint management of radio and distributed computing resources. From 5G scenarios perspective, the 5GM research is oriented mainly towards scenarios encompassing device-to-device communication, merging mobile communication and distributed computation (fog/mist computing), vehicular ad-hoc networks, and intelligent transportation systems.

What is it good for

The research results of 5GM contribute to fulfilling the requirements for future generation mobile networks (5G). Our outputs contribute to especially efficient data transmission in mobile networks and seamless mobility. We also work on the convergence of mobile networks and cloud computing in terms of cloud distributed closer to the user, i.e., to the base stations. This brings new possibilities of cloud computing in mobile networks for real-time applications. The proposed solutions are not only theoretical models and simulations. Thanks to the cooperation with industrial partners, selected solutions are verified through emulations or demonstrators. Moreover due to the participation of the Department of Telecommunication Engineering in standardization bodies (especially ETSI / 3GPP), we have the opportunity to push our solutions to standards.

Research topics

Mobility Management

In area of mobility management, we focus on all stages of handover process, i.e., neighborhood scanning, handover decision, call admission control. For optimization, we exploit prediction and learning algorithms to estimate future characteristics and behavior of users and network.

  • Neighborhood scanning

    We design algorithms optimizing procedure of scanning of potential target cells if a user is moving. Our first approach is based on dynamic optimization of a set of scanned cells according to the SINR observed by a user equipment from its serving cell. Furthermore, we work on new scanning scheme maximizing utilization of the small cells and minimizing energy consumption due to scanning.

  • Handover decision

    For handover decision, we improve efficiency of handover decision process to avoid redundant handovers between neighboring cells. We targets mainly scenarios with densely deployed small cells as these are an integral part of 5G mobile networks. Our approaches include adaptive hysteresis or estimation of gain experienced by users if he/she performs handover to a target cell.

  • Fast Cell Selection

    We work also on coordinated communication of a user equipment with several neighboring cells by means of Fast Cell Selection in OFDMA networks with densely deployed femtocells for mobility management purposes. For each frame, the most suitable cell, which transmits/receives data to/from users is selected. This approach enables to minimize the number of hard handovers and, consequently, the interruption in user's communication due to handover is eliminated. We have designed also management of transmission coordination among neighboring cells.

  • Call Admission Control

    For call admission control, we define algorithms predicting signal quality received by the user just after handover based on knowledge of current signal levels observed from the serving and neighboring cells. Together with the prediction of user's mobility and handover, we can efficiency decide about admission of the users to a target cell and reduce the number of call drops.

Radio Resource Management

In area of radio resource management, we focus especially on power control mechanism, resource allocation schemes and spectrum sharing exploiting cognitive radio.
  • QoS-Guaranteed Power Control
  • The basic idea of our developed power control is to adapt the transmission power of femtocells according to current traffic load and signal quality between the user equipments and the femtocell in order to fully utilize radio resources allocated to the femtocell. The advantage of the proposed scheme is in provisioning of high quality of service level to the femtocell users, while interference to users attached to macro base station is minimized.

  • Dynamic Resource Allocation
  • In this work, we focus on mitigation of cross-tier and co-tier interference for dense deployment of the femtocells. The femtocells either utilize an overlapping allocation mode or a non-overlapping allocation mode. The allocation mode is dynamically selected by a control unit depending on the changing interference pattern among individual femtocells. In order to create interference matrix among the femtocells, Bron-Kerbosch algorithm is used.

  • Hybrid Spectrum Sharing for Interference Mitigation
  • In this topic, we address the problem of interference caused by femtocells to macrocells. The solution is based on cognitive femtocell concept where the femtocells can access the frequency spectrum of more than one cellular operator. To guarantee QoS to the femtocell user even at heavy load, and despite low transmitting power, the femtocells can opportunistically access frequency bands of other cellular operators.

Device-to-device communication in cellular networks (D2D)

We focuses on efficient data transmission in scenario with local communication between two users attached to the same femtocell. We have proposd a novel routing scheme managing data transmission within a femtocell based on D2D principle. The routing path between users is dynamically selected from two hops transmission to direct one whenever the system can profit from it. In addition, we have developed a management procedure in order to implement our routing scheme into LTE standard. We also address problems of interference and mobility management for D2D in cellular networks.

Small Cell Cloud / Mobile Edge Computing

Small cell cloud, also known as Mobile Edge Computing, is a solution enabling offloading heavy computation from smartphones to cloud distributed over base station. We participate on development of this concept in area of architecture, QoS guarantee for nomadic users, optimization of data delivery and mobility management.

  • Architecture of Small Cell Cloud
  • We participate on modification of mobile network architecture to enable management of computing and storage resources deployed over enhanced small cells. Together with other partners, we have proposed integration of Small cell Cloud Manager into existing mobile networks. Moreover, we have proposed implementation of the Small cell Cloud Manager is by means of virtual-hybrid control of computing resources where virtualized computing power at small cells is shared for computation of user application as well as for management of computing resources.

  • Path selection enabling mobility of users while computation is in progress
  • We work on algorithm optimizing delay and/or energy consumption of the user equipment for offloading of parallelized computing tasks to the cloud-enhanced small cells, which are selected for computation. Our proposed approach selects the most suitable path for each part of data, delivers data to intended cell through radio and/or backhaul and then selects the most suitable path for collecting results. This enables also mobility of users if the computation is in progress.

  • Guaranteeing QoS by power control
  • We have also design control algorithm, which purpose is to guarantee that the requests processed by the cloud are received by the UE within required delay. This is done by coarse and dynamic fine setting of the small cells' transmitting power level. The amount of undelivered requests from the small cell cloud can be significantly minimized when compared to competitive schemes. At the same time, QoS of non-cloud users is only slightly impaired when compared to the scheme giving solely preferences to non-cloud users. We also show that the overhead introduced by our power control mechanism is negligible.

Intelligent Transportation System

In area of intelligent transportation system, we work on integration of VANET to 4G+/5G mobile networks. We proposed algorithm that enables route selection based on maximum expected signal quality with respect to the drivers’ maximum tolerated prolongation of journey. The ultimate is to select the route that ensures sufficient signal quality for users on board by maximizing the usage of vehicular ad-hoc networks resources, through Route Side Units, while minimizing the usage of the costly LTE-A resources.

Mobility modeling

We have developed mobility model representing a part of Prague (Czech Republic). Within this area, base stations are deployed according to the real deployment of Vodafone mobile operator. The mobility model exploits graph theory approach for finding the shortest possible path between two points of interest. Once a user reaches its destination, she/he chooses another destination and starts moving again. The probability that a user visits a point of interest is derived from real behavior of the users in the area. Based on the observation, four types of users are classified: workers, residents, visitors, and roaming residents. All parameters of simulation environment or mobility model can be easily modified or enhanced.

More details about our activities at http://5gmobile.eu/activities

Financial support and contracts

  • FP7 TROPIC, FP7 project no. ICT-318784 funded by European Commission (09/2012 – 02/2015)
  • FP7 FREEDOM, FP7 project no. ICT-248891 funded by European Commission (01/2010 – 12/2011)
  • FP7 ROCKET, FP7 project no. ICT-215282 funded by European Commission (01/2009 – 12/2010)
  • Prediction Algorithms for Efficient Mobility Management in Wireless Networks, Research project no. P102/12/P613 funded by Czech Science Foundation (01/2011 - 12/2014)
  • New methods for capacity improvement of heterogeneous wireless networks based on hybrid cognitive approach and small cells, Research project no. P102/13/24931 funded by Czech Science Foundation (02/2013 - 12/2015)

More details about our project at http://5gmobile.eu/projects

International collaboration

  • Universitat Politècnica de Catalunya (UPC), Barcelona – university (SP)
  • Universita di Roma, La Sapienza, Rome – university (IT)
  • CEA-Leti, Grenoble – research-and-technology organization (FR)
  • CEA-List, Paris – research-and-technology organization (FR)
  • National Taiwan University of Science and Technology (NTUST), Taipei – university (TW)
  • University College Dublin (UCD), Dublin – university (IR)
  • ATOS, Barcelona, Madrid – IT service, international company (SP)
  • CINI, Rome – consortium of Italian IT universities (IT)
  • DUNE, Rome – SME (IT)
  • SEQUANS, Paris - SME (FR)

More details about our partners at http://5gmobile.eu/cooperation

Selected publications

  • M. Vondra, Z. Becvar, "Distance-based Neighborhood Scanning for Handover Purposes in Network with Small Cells," IEEE Transactions on Vehicular Technology, accepted for publication, February 2015.
  • P. Mach, Z. Becvar, "Enhancement of Hybrid Cognitive Approach for Femtocells," IEEE Vehicular Technology Conference (VTC-Spring 2015), Glasgow, Scotland, May 2015.
  • M.A. Puente, Z. Becvar, M. Rohlik, F. Lobillo, E. Calvanese Strinati, "A Seamless Integration of Computationally-Enhanced Base Stations into Mobile Networks Towards 5G," IEEE Vehicular Technology Conference (VTC-Spring 2015) workshop on 5G Architectures, Glasgow, Scotland, May 2015.
  • M. Vondra, S. Djahel, J. Murphy, "VANETs Signal Quality-based Route Selection inSmart Cities," IFIP Wireless Days (WD 2014), Rio de Janeiro, Brasil, November 2014.
  • Z. Becvar, P. Mach, E. Calvanese Strinati, "Q-Learning-based Prediction of Channel Quality after Handover in Mobile Networks," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2014), Washington, USA, September 2014.
  • Z. Becvar, J. Plachy, P. Mach, "Path Selection Using Handover in Mobile Networks with Cloud-enabled Small Cells," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2014), Washington, USA, September 2014.
  • P. Mach, Z. Becvar, "Centralized Dynamic Resource Allocation Scheme for Femtocells Exploiting Graph Theory Approach," IEEE Wireless Communications and Networking Conference (WCNC 2014), Istanbul, Turkey, April 2014.
  • M. Vondra, Z. Becvar, "Self-configured Neighbor Cell List of Macro Cells in Network with Small Cells," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2013), London, UK, September 2013.
  • Z. Becvar, M. Vondra, P. Mach, "Dynamic Optimization of Neighbor Cell List for Femtocells," IEEE Vehicular Technology Conference (VTC-Spring 2013), Dresden, Germany, June 2013.
  • Z. Becvar, P. Mach, M. Vondra, "Self-optimizing Neighbor Cell List with Dynamic Threshold for Handover Purposes in Networks with Small Cells," Wireless Communications and Mobile Computing, 2013.
  • Z. Becvar, P. Mach, "Mitigation of Redundant Handovers to Femtocells by Estimation of Throughput Gain," Mobile Information Systems, Vol. 9, No. 4, 2013.
  • P. Mach, Z. Becvar, R. Bestak, "Handover of Relay Stations for Load Balancing in IEEE 802.16," Wireless Communications and Mobile Computing, Vol. 13, No. 2, February 2013.
  • Z. Becvar, P. Roux, P. Mach, "Fast Cell Selection with Efficient Active Set Management in OFDMA Networks with Femtocells," EURASIP Journal on Wireless Communications and Networking 2012, 2012:292.
  • Z. Becvar, P. Mach, B. Simak, "Improvement of Handover Prediction in Mobile WiMAX by Using Two Thresholds," Computer Networks, Elsevier, Vol. 55, No. 16, November 2011.
  • P. Mach, Z. Becvar, "QoS-Guaranteed Power Control Mechanism Based on the Frame Utilization for Femtocells," EURASIP Journal on Wireless Communications and Networking, Vol. 2011, 16 pages, 2011.

Complete list of publications available at http://5gmobile.eu/publications


Responsible person: doc. Ing. Milan Polívka, Ph.D.