Conference 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},


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


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


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


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


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},


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},


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},


I.P. Chochliouros, A.S. Spiliopoulou, P. Lazaridis, A. Dardamanis, Z. Zaharis and A. Kostopoulos . (2020). Dynamic Network Slicing: Challenges and Opportunities. 5G-PINE 2020 Workshop at 16th Int. Conference on Artificial Intelligence Applications and Innovations

Xianfu Chen, Zhifeng Zhao, Celimuge Wu, Tao Chen, Honggang Zhang, Mehdi Bennis. (2020). Secrecy Preserving in Stochastic Resource Orchestration for Multi-Tenancy Network Slicing. IEEE Goblecom 2019

Abstract: Network slicing is a proposing technology to support diverse services from mobile users (MUs) over a common physical network infrastructure. In this paper, we consider radio access network (RAN)-only slicing, where the physical RAN is tailored to accommodate both computation and communication functionalities. Multiple service providers (SPs, i.e., multiple tenants) compete with each other to bid for a limited number of channels across the scheduling slots, aiming to provide their subscribed MUs the opportunities to access the RAN slices. An eavesdropper overhears data transmissions from the MUs. We model the interactions among the non-cooperative SPs as a stochastic game, in which the objective of a SP is to optimize its own expected long-term payoff performance. To approximate the Nash equilibrium solutions, we first construct an abstract stochastic game using the channel auction outcomes. Then we linearly decompose the per-SP Markov decision process to simplify the decision-makings and derive a deep reinforcement learning based scheme to approach the optimal abstract control policies. TensorFlow-based experiments verify that the proposed scheme outperforms the three baselines and yields the best performance in average utility per MU per scheduling slot.


Xianfu Chen, Celimuge Wu, Tao Chen, Nan Wu, Honggang Zhang, Yusheng Ji. (2019). Age of Information-aware Multi-tenant Resource Orchestration in Network Slicing. IEEE CBDCom 2019 (Best paper award)

Abstract: To satisfy diverse services from mobile users (MUs) over a common network infrastructure, network slicing is envisioned as a promising technology. This paper considers radio access network (RAN)-only slicing, where the physical RAN is judiciously tailored to accommodate computation and communication functionalities. Multiple service providers (SPs, a.k.a., tenants) compete for a limited number of channels across the discrete scheduling slots in order to serve their respective subscribed MUs. From a MU perspective, the age of information of data packets from traditional mobile services and the energy consumption at mobile device are of practical importance. We characterize the interactions among the SPs via a stochastic game, in which a SP selfishly maximizes its own expected long-term payoff. To approximate the Nash equilibrium solutions, we build an abstract stochastic game exploring the local information of SPs. Furthermore, the decision-making process at a SP can be much simplified by linearly decomposing the per-SP Markov decision process, for which we derive a deep reinforcement learning based scheme to find the optimal abstract control policies. TensorFlow-based experiments validate our studies and show that the proposed scheme outperforms the three baselines and yields the best performance in average utility.


– Slawomir Kuklinski, Lechoslaw Tomaszewski, Robert Kolakowski, On O-RAN, MEC, SON and Network Slicing integration, 2020 IEEE Globecom Workshops

doi: 10.1109/gcwkshps50303.2020.9367527



– Michail-Alexandros Kourtis, Themis Anagnostopoulos, Slawomir Kuklilski, Michal Wierzbicki, Andreas Oikonomakis, George Xilouris, Ioannis P. Chochliouros, Na Yi, Alexandros Kostopoulos, Lechoslaw Tomaszewski, Thanos Sarlas, Harilaos Koumaras, 5G Network Slicing Enabling Edge Services, 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)

doi: 10.1109/nfv-sdn50289.2020.9289880



– Akinsola Akinsanya, Manish Nair, Huiling Zhu, Jiangzhou Wang, Adaptive Power Control with Vehicular Trellis Architecture for Vehicular Communication Systems, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

doi: 10.1109/vtc2020-spring48590.2020.9129488

Abstract: Autonomous driving in future vehicle system has imposed a high demand for reliable and power efficient communication to provide safe-driving to vehicular users. In order to achieve reliability and power efficiency, in this paper, a vehicular trellis architecture (VTA) is proposed. VTA allows traffic information to be transmitted either via vehicle-to-infrastructure (V2I), through the dedicated remote radio head (RRH) and its dynamically select vehicle(s) or, direct vehicle-to-vehicle (V2V) communication. We investigated the adaptive switching over V2I/V2V, to enhance efficient system reliability while optimizing the average power consumption of VTA. This paper presents a vehicular trellis algorithm (VTRA), which approximate solutions to the optimization problem. Simulation results demonstrate that the selection of joint V2I/V2V communication reduces the total power consumption of the system for a varying number of threshold distance and vehicles.


– Xianfu Chen, Celimuge Wu, Tao Chen, Zhi Liu, Mehdi Bennis, Yusheng Ji, Age of Information-Aware Resource Management in UAV-Assisted Mobile-Edge Computing Systems, GLOBECOM 2020 – 2020 IEEE Global Communications Conference

doi: 10.1109/globecom42002.2020.9322632

Abstract: This paper investigates the problem of age of information (AoI)-aware resource awareness in an unmanned aerial vehicle (UAV)-assisted mobile-edge computing (MEC) system, which is deployed by an infrastructure provider (InP). A service provider leases resources from the InP to serve the mobile users (MUs) with sporadic computation requests. Due to the limited number of channels and the finite shared I/O resource of the UAV, the MUs compete to schedule local and remote task computations in accordance with the observations of system dynamics. The aim of each MU is to selfishly maximize the expected long-term computation performance. We formulate the non-cooperative interactions among the MUs as a stochastic game. To approach the Nash equilibrium solutions, we propose a novel online deep reinforcement learning (DRL) scheme, which enables each MU to behave using its local conjectures only. The DRL scheme employs two separate deep Q-networks to approximate the Q-factor and the post-decision Q-factor for each MU. Numerical experiments show the potentials of the online DRL scheme in balancing the tradeoff between AoI and energy consumption.


– Matti Kutila, Kimmo Kauvo, Petri Aalto, Victor Garrido Martinez, Markku Niemi, Yinxiang Zheng, 5G Network Performance Experiments for Automated Car Functions, 2020 IEEE 3rd 5G World Forum (5GWF)

doi: 10.1109/5gwf49715.2020.9221295

Abstract: This article discusses the results of supporting transition towards fully automated driving with remote operator support via the novel V2X channels. Automated passenger cars are equipped with multiple sensors (radars, cameras, LiDARs, inertia, GNSS, etc.), the operation of which is limited by weather, detection range, processing power and resolution. The study explores the use of a dedicated network for supporting automated driving needs. The MEC server latencies and bandwidths are compared between the Tampere, Finland test network and studies conducted in China to support remote passenger car operation. In China the main aim is to evaluate the network latencies in different communication planes, whereas the European focus is more on associated driving applications, thus making the two studies mutually complementary. 5G revolutionizes connected driving, providing new avenues due to having lower and less latency variation and higher bandwidths. However, due to higher operating frequencies, network coverage is a challenge and one base station is limited to a few hundred meters and thus they deployed mainly to cities with a high population density. Therefore, the transport solutions are lacking so-called C-V2X (one form of 5G RAT) to enable data exchanges between vehicles (V2V) and also between vehicles and the digital infrastructure (V2I). The results of this study indicate that new edge-computing services do not cause a significant increase in latencies (<; 100 ms), but that latency variation (11 – 192 ms) remains a problem in the first new network configurations.


– Akinsola Akinsanya, Manish Nair, Huiling Zhu, Jiangzhou Wang, Joint Vehicle-Beam Allocation for Reliability and Coverage in Vehicular Communication Systems, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)

doi: 10.1109/vtc2020-spring48590.2020.9128605

Abstract: In vehicular communication systems, maximizing the number of served vehicles while simultaneously guaranteeing reliable coverage at all the vehicles can be a challenging proposition. A switched-beam based infrastructure can provide better reliability as the signal-to-interference-plus-noise ratio (SINR) can be improved. However, a simple switched-beam based vehicle-to-infrastructure (V2I) system alone may not suffice for serving all the vehicles because (i) the number of vehicle is more than the number of beam, and (ii) a vehicle may be out of the coverage region of a beam. Therefore, introducing vehicle-to-vehicle (V2V) communication becomes crucial in extending the number of served vehicles. In this paper, ajoint vehicle-beam allocation (VBA) and vehicular proximity (VP) algorithms for V2I and V2V, respectively are proposed to guarantee reliable coverage for vehicles. VBA is an SINR optimization algorithm, and VP is based on LTE Mode 4, a proximity based service for V2V communications. It is shown that setting a flexible SINR threshold helps in attaining a reliable beam coverage region in switched-beam based V2I communication. It is proven that the outage probability are also directly dependent on SINR thresholds. Lastly, the concept of utility ratio is also introduced as a metric for reliability. Simulation results show that joint V2I and V2V communication significantly improves the utility ratio.


– Ramiz Sabbagh, Huiling Zhu, Jiangzhou Wang, Cell-free Massive MIMO Systems under Jamming Attack, 2021 IEEE International Conference on Communications Workshops (ICC Workshops)

doi: 10.1109/iccworkshops50388.2021.9473710

Abstract: This paper evaluates the uplink spectral efficiency (SE) performance of a cell-free massive multiple-input-multiple-output (MIMO) network under the attack of several distributed jammers. The signal-to-interference-plus-noise ratio (SINR) formula for the maximum-ratio-combining (MRC) receiver is initially derived for an arbitrary legitimate user-equipment (UE) by considering the harmful impact of jammers. These jammers target the access points (APs) during both training and data transmissions. Two power control methods are developed to improve the SE performance, a max-min one aiming to ensure uniformly good service for UEs, and a second method aiming to achieve proportional fairness. The proposed system is compared with a single cell co-located massive MIMO system, and with another cell-free massive MIMO system including smart jammers, provided with the legitimate UEs’ pilot signals. Simulation results demonstrate the superiority of the proportional fairness power control compared with the max-min fairness and the other scenarios under the threat of jammers. The effect of the number of jammers and their transmission power is further presented and analysed.


– Ignas Laurinavicius, Huiling Zhu, Jiangzhou Wang, Yijin Pan, Beam Squint Exploitation for Linear Phased Arrays in a mmWave Multi-Carrier System, 2019 IEEE Global Communications Conference (GLOBECOM)

doi: 10.1109/globecom38437.2019.9013598

Abstract: To support millimeter-wave (mmWave) communications successfully, a large number of antennas (in the order of hundreds or thousands) must be implemented to mitigate significant propagation and scattering losses. Designing phased arrays for carrier frequency is a great method for narrowband systems, but the performance degrades significantly with larger bandwidth. We show that as the system bandwidth increases, the beams steer away from the focus direction, which is an effect known as beam squint in wideband systems. In this paper, at first, analysis of capacity is performed for an increasing number of antennas, to show the significance of beam squint. Then, a solution in digital domain is proposed. Conventionally, a single beam would be allocated to a user. By exploiting beam squint effect, in this solution more than one beam can carry a single-user’s data, which improves the system’s performance significantly, especially when the number of antennas in an array is large and there are multiple users.


– L. Nykänen, M., Kutila, M. Lankinen, 5G-DRIVE: EU China C-V2X collaboration, The 8th Transport Research Arena (TRA 2020)

Abstract: This paper is a review of preliminary results and progress of the EU-5G-DRIVE and corresponding twinningproject in China. The project is funded under the EU Horizon-2020, from where 5G development and especiallyenhanced Mobile Broadband and V2X technologies are studied by various organizations around EU. The paperfocuses on the first field tests of the project, which has been done in Espoo Finland in May 2019. The field tests are planned so that there are two use case test scenarios, where hybrid communication technologies (ETSI ITS-G5 and LTE/5G) are experimented together with automated car. The tests will produce more information about 5G development and especially focus on interoperability issues between EU and China, where 5G-DRIVE’s counter project is executed in parallel. The preliminary results indicate that the current network is not ready for having real collaborative driving and especially, steps towards C-V2X is not straightforward as thought in headlines.


– Siqi Zhang, Na Yi, Yi Ma, Correlation-Based Device Energy-Efficient Dynamic Multi-Task Offloading for Mobile Edge Computing

doi: 10.1109/vtc2021-spring51267.2021.9448864

Abstract: Task offloading to mobile edge computing (MEC) has emerged as a key technology to alleviate the computation workloads of mobile devices and decrease service latency for the computation-intensive applications. Device battery consumption is one of the limiting factors needs to be considered during task offloading. In this paper, multi-task offloading strategies have been investigated to improve device energy efficiency. Correlations among tasks in time domain as well as task domain are proposed to be employed to reduce the number of tasks to be transmitted to MEC. Furthermore, a binary decision tree based algorithm is investigated to jointly optimize the mobile device clock frequency, transmission power, structure and number of tasks to be transmitted. MATLAB based simulation is employed to demonstrate the performance of our proposed algorithm. It is observed that the proposed dynamic multi-task offloading strategies can reduce the total energy consumption at device along various transmit power versus noise power point compared with the conventional one.


– M. Lu, R. Blokpoel, J. Ferragut, M. Kutila, T. Chen, Next-generation communications for V2X applications, The 8th Transport Research Arena (TRA 2020) Paper ID: 350. (Paper accepted; Conference cancelled)

– Songyan Xue, Yi Ma, Na Yi, Rahim Tafazolli, On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems, 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications

doi: 10.1109/pimrc48278.2020.9217173

Abstract: This paper aims to handle the joint transmitter and noncoherent receiver design for multiuser multiple-input multiple-output (MU-MIMO) systems through deep learning. Given the deep neural network (DNN) based noncoherent receiver, the novelty of this work mainly lies in the multiuser waveform design at the transmitter side. According to the signal format, the proposed deep learning solutions can be divided into two groups. One group is called pilot-aided waveform, where the information-bearing symbols are time-multiplexed with the pilot symbols. The other is called learning-based waveform, where the multiuser waveform is partially or even completely designed by deep learning algorithms. Specifically, if the information-bearing symbols are directly embedded in the waveform, it is called systematic waveform. Otherwise, it is called non-systematic waveform, where no artificial design is involved. Simulation results show that the pilot-aided waveform design outperforms the conventional zero forcing receiver with least squares (LS) channel estimation on small-size MU-MIMO systems. By exploiting the time-domain degrees of freedom (DoF), the learning-based waveform design further improves the detection performance by at least 5 dB at high signal-to-noise ratio (SNR) range. Moreover, it is found that the traditional weight initialization method might cause a training imbalance among different users in the learning-based waveform design. To tackle this issue, a novel weight initialization method is proposed which provides a balanced convergence performance with no complexity penalty.


-Use Cases and Standardisation Activities for eMBB and V2X Scenarios, A. Kostopoulos, I.P. Chochliouros, J. Ferragut, Y. Ma, M. Kutila, A. Gavras, S. Horsmanheimo, K. Zhang, L. Ladid, A. Dardamanis and M.-A Kourtis. In Proceedings of the 2020 IEEE International Conference on Communications Workshops (ICC Workshops 2020), June 07-11, 2020, Virtual Conference. Edited by the IEEE, pp.118-122. ISBN: 978-1-7281-7440-2/20/$31.00 ©2020 IEEE. Online ISSN: 2474-9133. IEEE Catalog number: CFP2001E-ART.

–  5G Promotive Actions based upon enhanced Mobile Broadband (eMBB) Communication Trials between the EU and Chin”, I.P. Chochliouros, A.S. Spiliopoulou, D. Arvanitozisis, A. Kostopoulos, N. Yi, N. Gomes, T. Chen, J. Jidbeck, A. Dardamanis, P. Lazaridis, Z. Zaharis, M.-A. Kourtis and L. Ladid. In Proceedings of the SecRIoT-2020 Workshop (The 2nd  Workshop on Security and Reliability of IoT Systems) / SEEDA-CECNSM 2020 (the 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference) International Conference, September 25-27 (Virtual Conference), Corfu, Greece, pp.303-312. IEEE.  ISBN: 978-1-7281-6445-8/20/$31.00 ©2020 IEEE.

DOI: 10.1109/SEEDA-CECNSM49515.2020.9221805

– V2X Communications for the Support of GLOSA and Intelligent Intersection Applications, I.P. Chochliouros, A.S. Spiliopoulou, P. Lazaridis, Z. Zaharis, M.-A. Kourtis, S. Kuklinski, L. Tomazewski, D. Arvanitozisis and A. Kostopoulos. In Proceedings of the 6th (5G-DRIVE, 5G-VICTORI-, Smart5Grid- and MOTOR5G-based) Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE 2021) / AIAI-2021 International Conference, June 25-27, 2021, Hersonissos, Crete, Greece (Virtual Conference). In: I. Maglogiannis, J. Macintyre and L. Iliadis. (Eds.), Artificial Intelligence Applications and Innovations (AIAI) 2020 IFIP WG 12.5 International Workshops: 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021and MHDW 2021; IFIP Advances in Information and Communication Technology (AICT), vol.628, pp.138-152. Springer Nature Switzerland AG.     ISBN: 978-3-030-79156-8; ISBN (eBook): 978-3-030-79157-5; ISSN: 1868-4238; ISSN (electronic): 1868-422X.


– R. Kołakowski, L. Tomaszewski, S. Kukliński, Performance evaluation of the OSM orchestrator ,IEEE NFV-SDN’21

– S. Kukliński, L. Tomaszewski, R. Kołakowski, P. Chemouil, 6G-LEGO: A framework for 6G network slices, JCN Special Issue on 6G Wireless Systems

– L. Tomaszewski, I.P. Chochliouros, R. Kołakowski, S. Kukliński, M.-A. Kourtis, High mobility 5G services for vertical industries – network operator’s view, 5G-PINE 2021 Workshop at the 17th Int. Conference on Artificial Intelligence Applications and Innovations, IFIP Advances in Information and Communication Technology (AICT), vol. TBU

– I. Chochliouros, A. Spiliopoulou, P.Lazaridis, Z. Zaharis, M.-A. Kourtis, S. Kukliński, L. Tomaszewski, D. Arvanitozisis, A. Kostopoulos, V2X Communications for the Support of GLOSA and Intelligent Intersection Applications, 5G-PINE 2021 Workshop at the 17th Int. Conference on Artificial Intelligence Applications and Innovations, IFIP Advances in Information and Communication Technology (AICT), vol. TBU

Author: S. Kukliński, L. Tomaszewski


Author: Lechosław Tomaszewski, Sławomir Kukliński, Robert Kołakowski

AIAI 2020 IFIP WG 12.5 International Workshops – MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings 585

doi: 10.1007/978-3-030-49190-1_2

Abstract: This paper presents a concept of integration of MEC into the 5G network slicing architecture. Three variants of the architecture have been proposed, which incorporate: individual MEP/MEPM for each slice, shared ones for multiple network slices and Distributed Autonomous Slice Management and Orchestration (DASMO) approach. Each variant is focused on efficient integration of 5G Core and MEC solutions and utilizing additional functionalities of both components, including MEC APIs and 5G Control Plane exposure capabilities. Finally, main issues of 5G-MEC implementation have been discussed, which include the aspects of MEC service APIs, MEC Apps mobility in demanding use cases, challenges of service continuity in roaming scenarios as well as the role and availability of 5G enablers.


Author: Zheng Chang, Liqing Liu, Xijuan Guo, Tao Chen, Tapani Ristaniemi

AIAI 2020 IFIP WG 12.5 International Workshops – MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings 585

doi: 10.1007/978-3-030-49190-1_6

Abstract: In this work, we propose a dynamic optimization scheme for an edge computing system with multiple users, where the radio and computational resources, and offloading decisions, can be dynamically allocated with the variation of computation demands, radio channels and the computation resources. Specifically, with the objective to minimize the energy consumption of the considered system, we propose a joint computation offloading, radio and computational resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, the main problem is divided into several sub-problems at each time slot and are addressed separately. The simulation results demonstrate the effectiveness of the proposed scheme.


Joint publications

Tao Chen, Matti Kutila, Yinxiang Zheng, Wei Dei, Jiangzhou Wang (2020). Key Scenarios and Technologies in EU-China V2X Trial Cooperation. ZTE communications

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},


– Chih-Lin I, Slawomir Kuklinski, Tao Chen, Latif Ladid; A Perspective of O-RAN Integration with MEC, SON, and Network Slicing in the 5G Era, IEEE Network, Vol. 34 Issue 6, November/December 2020 pp 3–5

doi: 10.1109/mnet.2020.9277891

Abstract: The deployment of 5G mobile networks has begun in earnest. The 5G network is built on a service-based architecture (SBA) which enables programmability of the control plane of 5G Core (5GC) and supports network slicing (NS) in both core and access networks. NS enables the creation of multiple, isolated network slices tailored for specific services with diverse KPI objectives [1]. SBA of 5GC facilitates core network user plane functions (UPF) being deployed near the network edge, which has triggered intense interest in edge activities such as Multi-access Edge Computing (MEC), whereas the traditional Self-Organizing Network (SON) functions are being enhanced continuously in 5G RAN. Meanwhile, the development of open and smart RAN led by an industry alliance, O-RAN, has received great attention. In this short paper we would like to sort out if and how all of the above would fit together in a consistent and efficient manner regarding their architecture aspects and functionalities.


– Matti Kutila, Kimmo Kauvo, Pasi Pyykönen, Xiaoyun Zhang, Victor Garrido Martinez, Yinxiang Zheng, Shen Xu, A C-V2X/5G Field Study for Supporting Automated Driving. (2021)

Abstract: This article focuses on reviewing the results of a series of trials conducted in Europe and China to benchmark 5G’s benefits for automated driving challenges. The measurements have been conducted for studying the influence of the current 5G/LTE-V2X connectivity and optimizing antenna height, driving speed, and performance variation due to landscape variation. The results have been aggregated in real-world testing conducted in Finland and China. The vehicles have been equipped with onboard units (OBUs) and the infrastructure with the latest available 5G or LTE technologies.

The outcome of this study indicates that LTE-V2X highly depends on antenna height. However, the latencies are quite stable, being 20–50 ms unless line-of-sight connection is lost. The communication range is increased by 5G, and also package size can be increased by up to 1 MB without increasing the package error rate, which in the LTE-V2X case starts increasing when 0.5 MB is exceeded. This is not a problem for traditional C-ITS messages, but if considering “see through” or “remote video operation,” then the package size demand is much higher and goes beyond LTE-V2X’s capacity.


– Matti Kutila, Xiaoyun Zhang, Kimmo Kauvo, Victor Garrido Martinez, Juha Karppinen, Lasse Nykänen, Influence of infrastructure antenna location and positioning system availability to open-road C-V2X supported Automated Driving. (2021)

Abstract: Automated driving has attracted enthusiasm worldwide with its potential to transform mobility and realize transport, economical and societal benefits. Gaining perspectives from previous V2X trials in 5G-Drive project, this paper is motivated to focus on two challenges encountered with LTE-V2X enabled automated driving: the impact of infrastructure antenna height in C-V2X supported automated driving and the influence of C-V2X in vehicle positioning, especially when satellite signals is unavailable. Two trials have been designed and performed in Finland, as an attempt to continue and examine the two LTE-V2X enabled automated driving use cases in previous V2X trials. The outcome shows C-V2X latency is affected when antenna height is low. Optimizing and configuring the antenna height is crucial in C-V2X enabled automated driving tests. Important lessons on RTK, Inertial and C-V2X enabled automated vehicle positioning are drawn from the trials, where the enhancement of C-V2X could be augmented by testing and strengthening the GNSS signals.


– Kutila, M., Kauvo, K., Zheng, Y., Zhang, X. & Garrido Martinez, EU-China Joint V2X Trial Results, V., 8 Jun 2021, Proceedings of the 2021 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit): Special Session 2 – EU-China Collaboration in 5G and Beyond. 2 p

Abstract: This article summarizes the main research and trial results of the 5G-DRIVE project. The European 5G-DRIVE and Chinese 5G Large-Scale Trial projects were twinning projects that aim to design Cellular Vehicle-to-Everything (C-V2X) assisted automated driving use cases and to trial out these use cases in the field experiments under a harmonized trial framework. One of the main objectives was to benchmark C-V2X connectivity between Europe and China. Evaluating the benefits of C-V2X connectivity at urban intersection use cases has been conducted. The main Key Performance Indicators include coverage range at the urban intersection, packet error rate and latencies which depends on antenna height and channel load. The comparison between long-range LTE/5G and short-range C-V2X/PC5 channels has been conducted. C-V2X provides low latencies (< 40 milliseconds in average) and coverage is less than 800 meters. LTE/5G supports longer ranges but it cannot guarantee latencies less than 70 milliseconds, which reduces safe driving speed to 30 km/h to keep the safety-margin at 0,6 meters.


– K. Zeng, W. Deng, R. Wang, L. Zhang, J. Cheng, T. Chen, N. Yi, “5G Network Performance Evaluation and Deployment Recommendation Under Factory Environment,” IEEE PIMRC 2021.


– Y. Xiao, F. Luo, C. Zhao, F. Xu, T. Chen, “Delay and Deployment Cost Optimization of Edge Computing based on C-RAN in Intelligent Plant,” IEEE ICC 2021 workshop, Montreal, Canada, Jun. 2021

doi: 10.1109/iccworkshops50388.2021.9473552

Abstract: In order to minimize the deployment cost of network equipment and delay for data offloading of intelligent services in intelligent plants, this paper proposes a new edge computing architecture based on the cloud radio access network(C-RAN). In this architecture, we consider a computing offload mode which allows one sensing device (SD) to offload computing tasks to more than one access point. The problem of joint optimizing deployment cost and delay is solved based on the immune algorithm and Lagrange multiplier algorithm. The simulation result shows the significantly decrease of delay for data offloading in single-SD multi-access point mode.


– Xin Li, Wei Deng, Lei Liu, Yuqi Tian, Hui Tong, Jianhua Liu, Yi Ma, Jiangzhou Wang, Seppo Horsmanheimo, Anastasius Gavras, Novel Test Methods for 5G Network Performance Field Trial 2020 IEEE International Conference on Communications Workshops (ICC Workshops)

doi: 10.1109/iccworkshops49005.2020.9145321

Abstract: In this paper, several novel test methods are proposed for 5G mobile network field trials. As it is known, field trial plays an important role in wireless network commercialization process. However, several new technologies have been considered in 5G communication networks, such as massive MIMO. Therefore, conventional filed trial methods used in 4G mobile networks cannot fulfill the new test requirements for 5G mobile networks. Four new field trial methods have been discussed in our work. Moreover, real measurement data has been collected to demonstrate the proposed methods from 5G large scale filed trial supported by China Mobile Communications Group Co., Ltd.


– Yixue Hao, Yingying Jiang, Tao Chen, Donggang Cao, Min Chen, iTaskOffloading: Intelligent Task Offloading for a Cloud-Edge Collaborative System, IEEE Network 33/5

Journal publications

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)},


S. Noor, P. Assimakopoulos, M. Wang, H.A. Abdulsada, N. Genay, L.A. Neto, P. Chanclou, N.J. Gomes. (2020). Comparison of Digital Signal Processing Approaches for Subcarrier Multiplexed 5G and Beyond Analog Fronthaul. IEEE/OSA Journal of Optical Communications and Networking, vol. 12, no.  pp. 62-71.

doi: 10.1364/JOCN.381341

Abstract: Analog fronthaul transport architectures with digital signal processing at the end stations are promising as they have the potential to achieve high spectral efficiencies, increased flexibility and reduced latency. In this paper, two digital techniques for frequency domain multiplexing/de-multiplexing large numbers of channels are contrasted: one operates on the pre-Inverse Fast Fourier Transform (IFFT) “frequency-domain” samples while the other does so on the post-IFFT “time-domain” samples. Performance criteria including computational complexity and sampling rate requirements are used in the comparison. Following modeling and simulation of the techniques, implemented within a radio-over-fiber transport architecture, error vector magnitude performance estimates are obtained. These results show that each technique has performance advantages under specific channel transport scenarios.


E.Moutaly, P. Assimakopoulos, S. Noor, S. Faci, A. Billabert, N. J. Gomes, M. L. Diakité, C. Browning, C. Algani. (2019). Phase Modulated Radio-over-Fiber for Efficient 5G Fronthaul Uplink. Journal of Lightwave Technology vol. 37, no. 23 pp. 5821 – 5832

doi: 10.1109/JLT.2019.2940200

Abstract: AAnalog radio-over-fiber technology is gaining interest as a potential candidate for radio signal transport over the future fronthaul section of the 5th generation (and beyond) radio access network. In this paper, we propose a radio-over-fiber fronthaul with intensity modulation in the downlink and phase modulation with interferometric detection in the uplink, for simplified and power efficient remote units. We conduct an experimental investigation and verification of theoretical and simulation models of the performance of the phase-modulated uplink and demonstrate the ability of such an architecture to transport single-channel and multi-channel 5G-type radio waveforms. Experimentally verified data rates of 4.3 Gbps and simulation-based predictions, using a well matched-to-measurements model of the uplink, of 12.4 Gbps are presented, with error-vector magnitude performance well within relevant standard specifications for 64-QAM.


S. Xue, A. Li, J. Wang, N. Yi, Y. Ma, R. Tafazolli and T. E. Dodgson. (2019). To learn or not to learn: deep learning assisted wireless modem design. ZTE Communications vol. 17, no. 4, December 2019 pp. 3-11

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 discuss the fundamental bottlenecks of machine learning as well as their potential solutions in this paper.


Xianfu Chen, Celimuge Wu, Tao Chen, Honggang Zhang, Zhi Liu, Yan Zhang, Mehdi Bennis. (2020). Age of information-aware radio resource management in vehicular networks: A proactive deep reinforcement learning perspective. IEEE Transactions on Wireless Communications, Vol.19, issue 4, 2020.

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 discuss the fundamental bottlenecks of machine learning as well as their potential solutions in this paper.


– Michail‐Alexandros Kourtis, Thanos Sarlas, Themis Anagnostopoulos, Sławomir Kukliński, Lechosław Tomaszewski, Michał Wierzbicki, Andreas Oikonomakis, George Xilouris, Ioannis P. Chochliouros, Na Yi, Alexandros Kostopoulos, Harilaos Koumaras, “Network slicing for 5G edge services“, Internet Technology Letters, e289

doi: 10.1002/itl2.289

Abstract: In the current 5G technology domain network slicing already plays an important role as a critical enabler. An industry that 5G aims to disrupt is the vehicular one. In this paper the brief scope of the 5G-DRIVE research project is presented, regarding 5G vehicular research between the EU and China. In the frame of 5G-DRIVE a set of slicing mechanisms are investigated and evaluated in regard to their performance. Firstly, related to slicing mechanisms in the NFV domain the OSM orchestrator is measured in terms of scalability and performance. In the next experimental set related to RAN slicing, the Katana Slice Manager is evaluated and depicts how different slicing configurations can achieve different performance results. Furthermore, the paper showcases how 5G network slicing can be integrated as a key enabler to the stringent demands of a vehicular network environment. Finally, the paper concludes, setting future directions in the related field.


– Jiangzhou Wang, Wei Deng, Xin Li, Huiling Zhu, Manish Nair, Tao Chen, Na Yi, Nathan J. Gomes, 3D Beamforming Technologies and Field Trials in 5G Massive MIMO Systems, IEEE Open Journal of Vehicular Technology, 1

doi: 10.1109/ojvt.2020.3030774

Abstract: In this paper, three-dimensional (3D) beamforming characteristics and applications in fifth generation (5G) mobile communications have been studied by considering the physical structure of array antennas, and the properties of the 3D beam pattern formed by planar, rectangular array antennas. Array beam gains are formulated according to rectangular array antennas. The effect of array antenna configuration on 3D beamforming is studied especially according to the building height. The field trial and measurement results have been presented for single and multiple mobile users. The field trial results show that (1) The total sum rate from all users can be increased multiple times (i.e., 3 to 4 times) as large as that of a single user. When the number of users is larger than 8, the sum rate becomes saturated; (2) Users with uniform angular distribution can achieve larger sum rate than users with centralized distribution due to space separation; (3) The performance of the multi-antenna system is best under static-user conditions, with it dropping considerably for mobile conditions, even by more than 50% due to poor channel state information estimation; (4) In case of 3D beamforming, good coverage performance can be achieved in medium or high buildings.


– Philippos Assimakopoulos, Shabnam Noor, Minqi Wang, Hazim Abdulsada, Luiz Anet Neto, Naveena Genay, Philippe Chanclou, Nathan J. Gomes, Flexible and Efficient DSP-Assisted Subcarrier Multiplexing for an Analog Mobile Fronthaul, IEEE Photonics Technology Letters, 33/5

doi: 10.1109/lpt.2021.3056511

Abstract: The digital formation of an analog subcarrier multiplex employing in combination both a technique using pre-IFFT frequency-domain samples and one using post-IFFT time-domain samples is proposed and demonstrated. This combined technique enables a compromise for sampling rate requirements, while maintaining low complexity and good performance.


– Abdelwahab Boualouache, Hichem Sedjelmaci, Thomas Engel, Consortium Blockchain for Cooperative Location Privacy Preservation in 5G-Enabled Vehicular Fog Computing, IEEE Transactions on Vehicular Technology, 70/7

doi: 10.1109/tvt.2021.3083477

Abstract: Privacy is a key requirement for connected vehicles. Cooperation between vehicles is mandatory for achieving location privacy preservation. However, non-cooperative vehicles can be a big issue to achieve this objective. To this end, we propose a novel monetary incentive scheme for cooperative location privacy preservation in 5G-enabled Vehicular Fog Computing. This scheme leverages a consortium blockchain-enabled fog layer and smart contracts to ensure a trusted and secure cooperative Pseudonym Changing Processes (PCPs). We also propose optimized smart contracts to reduce the monetary costs of vehicles while providing more location privacy preservation. Moreover, a resilient and lightweight Utility-based Delegated Byzantine Fault Tolerance (U-DBFT) consensus protocol is proposed to ensure fast and reliable block mining and validation. The performance analysis shows that our scheme has effective incentive techniques to stimulate non-cooperative vehicles and provides optimal monetary cost management and secure, private, fast validation of blocks.


– Joydev Ghosh, Huiling Zhu, Huseyin Haci, A Novel Channel Model and Optimal Beam Tracking Schemes for Mobile Millimeter-Wave Massive MIMO Communications, IEEE Transactions on Vehicular Technology, 70/7

doi: 10.1109/tvt.2021.3083635

Abstract: A novel channel model has been proposed for mobile millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) communications to evaluate the effect of end-user mobility. In this model the variance of number of clusters and number of rays generated from each cluster is taken into account that is novel and different from widely used channel models. Two optimum codebook based beam-tracking schemes-multi-objective joint optimization codebook (MJOC) and linear hybrid combiner (LHC)- have been proposed for the novel channel model and their performance for spectral efficiency (SE) is presented. Performance for the two most commonly used channel state information (CSI) estimation approaches is investigated. Finally, the relationship between the beamforming training blocks and optimal beam tracking scheme is presented.


– Songyan Xue, Yi Ma, Na Yi , End-to-End Learning for Uplink MU-SIMO Joint Transmitter and Non-Coherent Receiver Design in Fading Channels, IEEE Transactions on Wireless Communications

doi: 10.1109/twc.2021.3068302

Abstract: In this paper, a novel end-to-end learning approach, namely JTRD-Net, is proposed for uplink multiuser single-input multiple-output (MU-SIMO) joint transmitter and non-coherent receiver design (JTRD) in fading channels. The basic idea lies in the use of artificial neural networks (ANNs) to replace traditional communication modules at both transmitter and receiver sides. More specifically, the transmitter side is modeled as a group of parallel linear layers, which are responsible for multiuser waveform design; and the non-coherent receiver is formed by a deep feed-forward neural network (DFNN) so as to provide multiuser detection (MUD) capabilities. The entire JTRD-Net can be trained from end to end to adapt to channel statistics through deep learning. After training, JTRD-Net can work efficiently in a non-coherent manner without requiring any levels of channel state information (CSI). In addition to the network architecture, a novel weight-initialization method, namely symmetrical-interval initialization, is proposed for JTRD-Net. It is shown that the symmetrical-interval initialization outperforms the conventional method (e.g. Xavier initialization) in terms of well-balanced convergence-rate among users. Simulation results show that the proposed JTRD-Net approach takes significant advantages in terms of reliability and scalability over baseline schemes on both i.i.d. complex Gaussian channels and spatially-correlated channels.


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.


Author: 5G-DRIVE consortium

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

Author: Adrian Quesada Rodriguez (MI); Renáta Radócz (MI); Cédric Crettaz (MI); Abdelwahab Boualouache (; Ridha Soua (; Sébastien Ziegler (MI), Kinga Képessy (MI), Anna Kourakli (MI)

Publication & Date: 5G-DRIVE website (2021)

Author: S. Kukliński, L. Tomaszewski

doi: 10.1002/9781119471509.w5gref094

Author: A. Boualouache, R. Soua, T. Qiang,  T.  Engel

Machine Intelligence and Data Analytics for Sustainable Future Smart Cities

Abstract: While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardization groups to propose convenient solutions for privacy preservation. One of the main proposed solutions is the use of Pseudonym-Changing Strategies (PCSs). However, ETSI has recently published a technical report which highlights the absence of standardized and efficient PCSs [1]. This alarming situation mandates an innovative shift in the way that the privacy of end-users is protected during their journey. Software Defined Networking (SDN) is emerging as a key 5G enabler to manage the network in a dynamic manner. SDN-enabled wireless networks are opening up new programmable and highly-flexible privacy-aware solutions. We exploit this paradigm to propose an innovative software-defined location privacy architecture for vehicular networks. The proposed architecture is context-aware, programmable, extensible, and able to encompass all existing and future pseudonym-changing strategies. To demonstrate the merit of our architecture, we consider a case study that involves four pseudonym-changing strategies, which we deploy over our architecture and compare with their static implementations. We also detail how the SDN controller dynamically switches between the strategies according to the context.