Publications

Scientific publications

A. Anttonen, A. Mammela and T. Chen, “Hybrid User Association with Proactive Auxiliary Intervention for Multitier Cellular Networks,” 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia, 2019, pp. 1-6.

doi: 10.1109/VTCSpring.2019.8746686

Abstract: In this paper, we consider a hybrid user association (HUA) problem for load balancing of multitier cellular networks. The proposed hierarchical HUA approach builds on a combination of decentralized user association (DUA) and auxiliary intervention of a central control unit (CCU). A major challenge with the CCU intervention is the time interval determined by a selected CCU control cycle during which the DUA must accept all users that satisfy the prevailing association criterion while proactively mitigating potential resource depletions. Consequently, the primary focus of this work is on relating the control cycle of the CCU intervention with the incipient resource depletions, according to a maximum allowed resource depletion probability. By uniquely combining a set of mathematical tools from stochastic geometry and queueing theory, we present a novel HUA method which evaluates the association bias values of the DUA according to a CCU-optimized load vector and enables tier-based resource depletion probability provisioning over finite control cycles. The trade-offs between the proposed HUA method and the standard DUA approach are demonstrated via network simulations with flow-level spatiotemporal dynamics.

keywords: {cellular radio;frequency allocation;optimisation;probability;queueing theory;resource allocation;stochastic processes;telecommunication traffic;proactive auxiliary intervention;multitier cellular networks;hybrid user association problem;load balancing;hierarchical HUA approach;central control unit;CCU intervention;selected CCU control cycle;incipient resource depletions;maximum allowed resource depletion probability;novel HUA method;association bias values;CCU-optimized load vector;tier-based resource depletion probability;finite control cycles;standard DUA approach;network simulations;prevailing association criterion;potential resource depletions;stochastic geometry;queueing theory;Spatiotemporal phenomena;Load modeling;Interference;Queueing analysis;Signal to noise ratio;Cellular networks;Stochastic processes},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8746686&isnumber=8746285

Boualouache, A., Soua, R., and Engel, T. SDN-based Pseudonym-Changing Strategy for Privacy Preservation in Vehicular Networks. 15th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob’19). 2019.

Abstract: The pseudonym-changing approach is the de-factolocation privacy solution proposed by security standards toensure that drivers are not tracked during their journey. SeveralPseudonym Changing Strategies (PCSs) have been proposed tosynchronize Pseudonym Changing Processes (PCPs) between con-nected vehicles. However, most of the existing strategies are static,rigid and do not adapt to the vehicles’ context. In this paper, weexploit the Software Defined Network (SDN) paradigm to proposea context-aware pseudonym changing strategy (SDN-PCS) whereSDN controllers orchestrate the dynamic update of the securityparameters of the PCS. Simulation results demonstrate that SDN-PCS strategy outperforms typical static PCSs to perform efficientPCPs and protect the location privacy of vehicular network users.

Keywords: Vehicular networks ; location privacy ; pseudonym changing strategy ; SDN ; context-aware

URL: http://orbilu.uni.lu/handle/10993/40163 

Boualouache, A., Soua, R., and Engel, T. VPGA: an SDN-based Location Privacy Zones Placement Scheme for Vehicular Networks. 38th IEEE International Performance Computing and Communications Conference (IPCCC). 2019.

Abstract: Making personal data anonymous is crucial to ensure the adoption of connected vehicles. One of the privacy-sensitive information is location, which once revealed can be used by adversaries to track drivers during their journey. Vehicular Location Privacy Zones (VLPZs) is a promising approach to ensure unlinkability. These logical zones can be easily deployed over roadside infrastructures (RIs) such as gas station or electric charging stations. However, the placement optimization problem of VLPZs is NP-hard and thus an efficient allocation of VLPZs to these RIs is needed to avoid their overload and the degradation of the QoS provided within theses RIs. This work considers the optimal placement of the VLPZs and proposes a genetic-based algorithm in a software defined vehicular network to ensure minimized trajectory cost of involved vehicles and hence less consumption of their pseudonyms. The analytical evaluation shows that the proposed approach is cost-efficient and ensures a shorter response time.

Keywords: Vehicular Networks ; Security ; Location privacy Zones ; Software Defined Networks ; Genetic Algorithm

URL: http://hdl.handle.net/10993/40220

Chochliouros I.P. et al. (2019) Enhanced Mobile Broadband as Enabler for 5G: Actions from the Framework of the 5G-DRIVE Project. In: MacIntyre J., Maglogiannis I., Iliadis L., Pimenidis E. (eds) Artificial Intelligence Applications and Innovations. AIAI 2019. IFIP Advances in Information and Communication Technology, vol 560. Springer, Cham

doi: https://doi.org/10.1007/978-3-030-19909-8_3

Abstract: In the new fascinating era of 5G, new communication requirements set diverse challenges upon existing networks, both in terms of technologies and business models. One among the essential categories of the innovative 5G mobile network services is the enhanced Mobile Broadband (eMBB), mainly aiming to fulfill users’ demand for an increasingly digital lifestyle and focusing upon facilities that implicate high requirements for bandwidth. In this paper we have discussed eMBB as the first commercial use of the 5G technology. Then, we have focused upon the original context of the 5G-DRIVE research project between the EU and China, and we have identified essential features of the respective eMBB trials, constituting one of the corresponding core activities. In addition, we have discussed proposed scenarios and KPIs for assessing the scheduled experimental work, based on similar findings from other research and/or standardization activities.

Chochliouros I.P. et al. (2019) Testbeds for the Implementation of 5G in the European Union: The Innovative Case of the 5G-DRIVE Project. In: MacIntyre J., Maglogiannis I., Iliadis L., Pimenidis E. (eds) Artificial Intelligence Applications and Innovations. AIAI 2019. IFIP Advances in Information and Communication Technology, vol 560. Springer, Cham

doi: https://doi.org/10.1007/978-3-030-19909-8_7

Abstract: An essential part of the actual EU policy towards promoting and validating 5G applications and of related solutions is via the establishment of an explicit plan and of a detailed roadmap for trials, tests and experimental activities though dedicated testbeds, in parallel with the current research and development activities coming from the 5G-PPP framework. The present paper discusses the fundamental role of the proposed trials’ initiatives within the broader European framework for the establishment and the promotion of 5G and also analyses the corresponding streams as indispensable parts of the 5G-PPP context, aiming to support innovation and growth. In addition, as part of the broader initiative for trial actions we identify the case of the 5G-DRIVE project that aims to realise 5G deployment scenarios (i.e., enhanced Mobile Broadband and Vehicle-to-Everything communications), between the EU and China, by discussing the fundamental features of the respective trials sites.

Chochliouros, I., et al. Use Cases for developing enhanced Mobile Broadband Services for the promotion of 5G. Proceedings of the EuCNC 2019, Special Session No.3.

A. Kostopoulos et al., “5G Trial Cooperation Between EU and China,” 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China, 2019, pp. 1-6.

doi: 10.1109/ICCW.2019.8756985

Abstract: The H2020 project 5G-DRIVE (5G HarmoniseD Research and TrIals for serVice Evolution between EU and China) cooperates with the Chinese twin project to trial and validate key functions of 5G networks operating at 3.5 GHz bands for enhanced Mobile Broadband (eMBB) and 3.5 GHz and 5.9 GHz bands for V2X scenarios. 5G-DRIVE will instil significant impact on the validation of standards and trigger the roll-out of real 5G networks and V2X innovative solutions driving new business opportunities and creating thereby new jobs and brand new business models. This paper presents the overall approach of 5G-DRIVE, the advances beyond the current state of the art for key 5G enabling technologies, as well as the considered use cases.

keywords: {5G mobile communication;broadband networks;cooperative communication;Chinese twin project;5G enabling technologies;5G trial cooperation;5G networks;V2X scenarios;5G harmonised research and trials for service evolution between EU and China;H2020 project 5G-DRIVE;enhanced Mobile Broadband;eMBB;frequency 3.5 GHz;frequency 5.9 GHz},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8756985&isnumber=8756635

S. Kukliński and L. Tomaszewski, “Key Performance Indicators for 5G network slicing,” 2019 IEEE Conference on Network Softwarization (NetSoft), Paris, France, 2019, pp. 464-471.

doi: 10.1109/NETSOFT.2019.8806692

Abstract: Network slicing technology will influence the way in which new networking solutions will be designed and operated. So far, network slicing is often linked with 5G networks, but this approach can be used to deploy any communications network(s) over a common infrastructure. The concept is still a subject of intensive research and standardization. From the point of view of network or service operator, it is necessary to define fundamental quantitative indicators for performance evaluation of the network slicing. Such parameters are often called Key Performance Indicators (KPIs). Network slicing KPIs should deal with network slicing run-time and life-cycle management and orchestration. The paper proposes a set of KPIs for network slicing taking into account the 5G network specifics.

keywords: {5G mobile communication;quality of service;telecommunication network management;virtualisation;networking solutions;communications network;network slicing run-time;life-cycle management;key performance indicators;5G network slicing technology;Network slicing;5G mobile communication;3GPP;Monitoring;Key performance indicator;Network slicing;KPI;orchestration;management;5G},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8806692&isnumber=8806619

M. Kutila, P. Pyykonen, Q. Huang, W. Deng, W. Lei and E. Pollakis, “C-V2X Supported Automated Driving,” 2019 IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, China, 2019, pp. 1-5.

doi: 10.1109/ICCW.2019.8756871

Abstract: Automated driving is expected to improve road safety and traffic efficiency. Host vehicle onboard sensing systems typically sense the environment up to 250 m ahead of the vehicle. Today’s LiDARs can see approximately 120 m, and recognition of small objects, such as animals or dropped cargo, however, today reliably drop when range is more than 50m. Connected driving adds an electronic horizon to the onboard sensing system which could extend the sensing range and greatly improves the efficiency. Therefore, collaborative sensing in which the vehicle exchanges not only status messages but also real data has recently been intensively discussed. Current cellular 3G/4G networks have enhanced the downlink capacity for sharing large data blocks. However, uplink is limited and therefore vehicles are unable to share point clouds of what they see in front. This article investigates the opportunities of 5G-based cellular vehicle-to-everything (C-V2X) collaborative sensing based on the results of trials conducted at test sites in China and Finland. The results indicate that the round-trip is stable (<; 60 ms) even when exchanging 1 MB/s between vehicles. Finally, the automotive industry perspective is taken into account in identifying and prioritizing potential use case scenarios for utilizing 5G based connected driving applications.

keywords: {3G mobile communication;4G mobile communication;cellular radio;optical radar;road safety;road vehicles;vehicular ad hoc networks;traffic efficiency;host vehicle;LiDARs;animals;dropped cargo;electronic horizon;onboard sensing system;sensing range;collaborative sensing;current cellular 3G/4G networks;downlink capacity;data blocks;point clouds;5G-based cellular vehicle-to-everything;connected driving applications;V2X Supported Automated Driving;road safety;status messages;byte rate 1.0 MByte/s},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8756871&isnumber=8756635

S. Noor, P. Assimakopoulos and N. J. Gomes, “A Flexible Subcarrier Multiplexing System With Analog Transport and Digital Processing for 5G (and Beyond) Fronthaul,” in Journal of Lightwave Technology, vol. 37, no. 14, pp. 3689-3700, 15 July15, 2019.

doi: 10.1109/JLT.2019.2918215

Abstract: A flexible subcarrier multiplexing system combining analog transport with digital domain processing is presented. By making use of bandpass sampling and applying a systematic mapping of signals into available Nyquist zones, the multiplexing system is able to present multiple signals at the same intermediate frequency at the remote site. This simplifies the processing required for multiple antenna systems. We further propose the use of track-and-hold amplifiers at the remote site. These elements are used to extend the mapping to a mapping hierarchy, offering flexibility in frequency placement of signals and relaxation of analog-to-digital converter bandwidth and sampling rate constraints. The system allows the transport of different numerologies in a number of next generation radio access network scenarios. Experimental results for large signal multiplexes with both generic and 5th-generation mobile numerologies show error-vector magnitude performance well within specifications, validating the proposed system. Simulation results from a system model matched to these experimental results provide performance predictions for larger signal multiplexes and larger bandwidths.

keywords: {5G mobile communication;analogue-digital conversion;radio access networks;radio-over-fibre;signal sampling;subcarrier multiplexing;digital domain processing;bandpass sampling;systematic mapping;available Nyquist zones;remote site;multiple antenna systems;mapping hierarchy;analog-to-digital converter bandwidth;sampling rate constraints;system model;digital processing;5G fronthaul;analog transport;flexible subcarrier multiplexing system;error-vector magnitude;next generation radio access network scenarios;signal multiplexes;track-and-hold amplifiers;Multiplexing;Bandwidth;5G mobile communication;Frequency-domain analysis;Amplitude modulation;MIMO communication;Next generation networking;Digital signal processing;massive-MIMO (mMIMO);millimeter wave (mmW);mobile fronthaul;radio-over-fiber;subcarrier multiplexing (SCM)},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8720052&isnumber=8744414

S. Xue, Y. Ma, A. Li, N. Yi and R. Tafazolli, “On Unsupervised Deep Learning Solutions for Coherent MU-SIMO Detection in Fading Channels,” ICC 2019 – 2019 IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-6.

doi: 10.1109/ICC.2019.8761999

Abstract: In this paper, unsupervised deep learning solutions for multiuser single-input multiple-output (MU-SIMO) coherent detection are extensively investigated. According to the ways of utilizing the channel state information at the receiver side (CSIR), deep learning solutions are divided into two groups. One group is called equalization and learning, which utilizes the CSIR for channel equalization and then employ deep learning for multiuser detection (MUD). The other is called direct learning, which directly feeds the CSIR, together with the received signal, into deep neural networks (DNN) to conduct the MUD. It is found that the direct learning solutions outperform the equalization-and-learning solutions due to their better exploitation of the sequence detection gain. On the other hand, the direct learning solutions are not scalable to the size of SIMO networks, as current DNN architectures cannot efficiently handle many co-channel interferences. Motivated by this observation, we propose a novel direct learning approach, which can combine the merits of feedforward DNN and parallel interference cancellation. It is shown that the proposed approach trades off the complexity for the learning scalability, and the complexity can be managed due to the parallel network architecture.

keywords: {fading channels;interference suppression;multiuser channels;neural nets;SIMO communication;supervised learning;coherent MU-SIMO detection;fading channels;unsupervised deep learning solutions;multiuser single-input multiple-output coherent detection;channel state information;CSIR;channel equalization;multiuser detection;deep neural networks;direct learning solutions;sequence detection gain;direct learning approach;learning scalability;equalization-and-learning solutions;Deep learning;Fading channels;Receivers;MIMO communication;Training data;Complexity theory},

URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8761999&isnumber=8761046

Xue, Songyan & Li, A. & Wang, J. & Yi, N. & Ma, Y. & Tafazolli, Rahim & Dodgson, T.. (2019). To Learn or Not to Learn: Deep Learning Assisted Wireless Modem Design.

Abstract: Deep learning is driving a radical paradigm shift in wireless communications, all the way from the application layer down to the physical layer. Despite this, there is an ongoing debate as to what additional values artificial intelligence (or machine learning) could bring to us, particularly on the physical layer design; and what penalties there may have? These questions motivate a fundamental rethinking of the wireless modem design in the artificial intelligence era. Through several physical-layer case studies, we argue for a significant role that machine learning could play, for instance in parallel error-control coding and decoding, channel equalization, interference cancellation, as well as multiuser and multiantenna detection. In addition, we will also discuss the fundamental bottlenecks of machine learning as well as their potential solutions in this paper.

URL: https://arxiv.org/abs/1909.07791 

Other publications and articles

Author: Latif Ladid (University of Luxembourg, IPv6 Forum President)

Publication & Date: InterComms: International Communications Project (Issue 31 – 2019), 2019.

Abstract: This publication presents a thorough overview of the 5G-DRIVE project, including the objectives, project concept, trial sites, and expected impact.

LinkWeb

Author: 5G-DRIVE consortium

Publication & Date: European 5G Annual Journal (2019)

Link: Coming soon.