IEEE Consumer Communications & Networking Conference
11-14 January 2019 // Las Vegas // USA


Full Day

TUT-1: Wireless Networks Design: Model-Based or Data-Driven?
Alessio Zappone, Marco Di Renzo, and Merouane Debbah

Half Day

TUT-2: IoT Systems and Smartness – Virtualization, Protocols, Applications and Big Data
R. Venkatesha Prasad and Abdur Rahim Biswas

TUT-3: Connected Vehicles in the 5G Landscape
Claudio Casetti

TUT-4: Ultra-Reliable and Low-Latency Communications Services in 5G
Li-Chun Wang

TUT-5: Name Data Vehicular Networks: Challenges, Solutions, and Future Directions
Syed Hassan Ahmed and Safdar Hussain Bouk

TUT-6: LTE-NR Dual Connectivity as the First Step to Commercial 5G
Dr. Oumer Teyeb and Dr. Antonino Orsino

TUT-7: Integrated Aerial/Terrestrial 6G Networks for Ubiquitous 3D Super-Connectivity
Halim Yanikomeroglu

TUT-8: Coding Theory Based Cryptography for the Internet-of-Things
Nuh Aydin, Bahattin Yildiz, and Suleyman Uludag



TUT-1: Wireless Networks Design: Model-Based or Data-Driven?

Recently, deep learning has received significant attention as a technique to design and optimize wireless communication systems and networks. The usual approach to use deep learning consists of acquiring large amount of empirical data about the system behavior and employ it for performance optimization (data-driven approach). We believe, however, that the application of deep learning to communication networks design and optimization offers more possibilities. As opposed to other fields of science, such as image classification and speech recognition, mathematical models for communication networks optimization are very often available, even though they may be simplified and inaccurate. We believe that this a priori expert knowledge, which has been acquired over decades of intense research, cannot be dismissed and ignored. In this tutorial, in particular, we put forth a new approach that capitalizes on the availability of (possibly simplified or inaccurate) theoretical models, in order to reduce the amount of empirical data to use and the complexity of training artificial neural networks (ANNs). We concretely show, with the aid of some examples, that synergistically combining prior expert knowledge based on analytical models and data-driven methods constitutes a suitable approach towards the design and optimization of communication systems and networks with the aid of deep learning based on ANNs.

The tutorial is structured in three main parts:

  • Data-driven design of wireless networks
  • Model-based design of wireless networks
  • Embedding expert knowledge into deep learning

and will be based on the following recent publications of the authors:

  • A. Zappone, M. Di Renzo, M. Debbah, ``From Model-Based to Data-Driven Wireless Communications. When is Deep Learning the Answer?'', invited paper to IEEE Transactions on Communications, in submiission, 2018.
  • A. Zappone, M. Di Renzo, M. Debbah, T. T. Lam, X. Qian, "Model-Aided Wireless Artificial Intelligence: Embedding Expert Knowledge in Deep Neural Networks Towards Wireless Systems Optimization",  submitted, August 2018, available online at

Speakers: Alessio Zappone, Marco Di Renzo, and Merouane Debbah


TUT-2: IoT Systems and Smartness – Virtualization, Protocols, Applications and Big Data

Speakers: R. Venkatesha Prasad and Abdur Rahim Biswas


TUT-3: Connected Vehicles in the 5G Landscape

The road is being paved right now to enact the vision of connected cars, leveraging efforts that have been going on since the beginning of this century, especially within IEEE and ETSI. Now, the upcoming 5G technology is expected to be a game changer for vehicular communication, with the automotive sector having already secured its place among the most prominent verticals. The possibility for vehicles to be connected to other vehicles, pedestrians, roadside infrastructure or application servers, enables the development of safety services as well as multiple revolutionary applications such as fully automated or remote driving. Additional use cases embrace the wider area of Intelligent Transportation Systems (ITS). The traditional approach through Dedicated Short Range Communication (IEEE 802.11p/DSRC) is being challenged by new paradigms that are often referred to as Cellular Vehicle-to-Everything (C-V2X), a technology concept that features prominent roles for cellular standards in a wide range of vehicle connectivity use cases and applications. A viable C-V2X technology implementation is available since 3GPP Release 14, shoehorning C-V2X support in 5G networks. This Tutorial will cover both the state-of-the-art of vehicular communication and networking, from the point of view of protocols and regulations, as well as the most recent proposals in the context of C-V2X along with the requirements for the novel use cases they are ushering, some of them taken from ongoing research projects. Overall, the Tutorial will provide a comprehensive view of how inter-vehicular communication will fit into the broader 5G landscape.

Speaker: Claudio Casetti


TUT-4: Ultra-Reliable and Low-Latency Communications Services in 5G

In this tutorial, we will discuss the key challenges and feasible approaches in supporting ultra-reliable and low-latency communication (URLLC) services in 5G. We first give an overview of various deployment scenarios in 5G. The challenges of 5G URLLC services lie in the fact that transmission losses, handoff delays, and re-routing delays have more severe impact when the link data rate increases. We will focus on dynamic resource allocation and intelligent interference management techniques to enhance reliability, system throughput and sustain low latency transmission. Last, potential research issues in radio access technologies for supporting URLLC services in 5G networks will be highlighted.

Speaker: Li-Chun Wang (IEEE Fellow), Chair Professor , Department Electrical and Computer Engineering, National Chiao Tung University, Taiwan

Li-Chun Wang (M’96 – SM’06 – F’11) received his Ph. D. degree from Georgia Institute Technology, USA, in 1996. He is now with National Chiao Tung University as Chair Professor of Electrical and Computer Engineering, Taiwan. From 1996 to 2000, he was with AT&T Laboratories as a Senior Technical Staff Member. His recent research interests are in the areas of cross-layer optimization for wireless systems, machine-learning radio resource management, software-defined heterogeneous networks, industrial Internet of things, and artificial intelligence-enabled unmanned aerial vehicular (UAV) networks.

Dr. Wang was elected to the IEEE Fellow in 2011 for his contributions to cellular architectures and radio resource management in wireless networks. He won twice Distinguished Research Award from Ministry of Science and Technology, Taiwan (2012, 2017). He was the co-recipients of IEEE Communications Society Asia-Pacific Board Best Award (2015), Y. Z. Hsu Scientific Paper Award (2013), and IEEE Jack Neubauer Best Paper Award (1997). He holds 19 US patents, and has published over 250 journal and conference papers, and co-edited a book, “Key Technologies for 5G Wireless Systems,” (Cambridge University Press 2017).


TUT-5: Name Data Vehicular Networks: Challenges, Solutions, and Future Directions

This tutorial aims to introduce our audience to the Named Data Networking (NDN) architecture and its application in the future vehicular networks and applications. The speakers will talk about the basic working principle of the NDN, the structure of the NDN’s forwarding daemon, basic characteristics and architecture of the vehicular communication network, application and advantage of NDN in vehicular communication, and finally the intrinsic security of the NDN in vehicular networks. In order to increase the understanding of the NDN-based vehicular communication, we present few well-known vehicular network (VN) applications, research challenges, and use cases.

Speakers: Syed Hassan Ahmed and Safdar Hussain Bouk


TUT-6: LTE-NR Dual Connectivity as the First Step to Commercial 5G

New Radio (NR) technology aims to satisfy both urgent market needs - by assisting LTE radio - and the longer-term requirements of the 5th Generation on (5G). In this context, Non-standalone (NSA) NR - by means of LTE-NR Dual Connectivity (DC) - is one of the primary technology components of 5G. The concept of NSA NR is identified by 3GPP as one of the most important technology components of 5G where NR, with its future-proof functionalities, can co-exist with LTE radio to improve network performance. Initially, this co-existence is enabled with a limited set of NR features by exploiting the existing LTE Radio Access Network (RAN) and Core Network (CN) - EPC - infrastructure. However, when the full set of standalone NR features will be developed, the dual connectivity between LTE and NR will comprehend more architecture options enabled by a new 5G CN (5GC). The introduction of NSA NR will make the key benefits of 5G technologies available to users much earlier than expected (i.e., Q4 2018/Q1 2019) since it will allow mobile operators to leverage their existing LTE deployments with on-demand NR aggregation. In this tutorial, we will explain the LTE-NR DC concepts and describe the key features that have been specified by the 3rd Generation Partnership Project (3GPP) during Release 15. Furthermore, we will analyze the NSA performance with respect to LTE and standalone NR and show 5G trial case stories that are happening all over the world. Finally, we will discuss the new concepts and upcoming features foreseen for the NR standardization such as Multi-RAT Dual Connectivity (MR-DC) cases with the 5G core network, 5GC.

Speakers: Dr. Oumer Teyeb and Dr. Antonino Orsino


TUT-7: Integrated Aerial/Terrestrial 6G Networks for Ubiquitous 3D Super-Connectivity

The 5G standards are currently being developed with a scheduled completion date of late-2019; the 5G wireless networks are expected to be deployed globally throughout 2020s. As such, it is time to reinitiate a brainstorming endeavour followed by the technical groundwork towards the subsequent generation (6G) wireless networks of 2030s.

One reasonable starting point in this new 6G discussion is to reflect on the possible shortcomings of the 5G networks to-be-deployed. 5G promises to provide connectivity for a broad range of use-cases in a variety of vertical industries; after all, this rich set of scenarios is indeed what distinguishes 5G from the previous four generations. Many of the envisioned 5G use-cases require challenging target values for one or more of the key QoS elements, such as high rate, high reliability, low latency, and high energy efficiency; we refer to the presence of such demanding links as the super-connectivity.

However, the very fundamental principles of digital and wireless communications reveal that the provision of ubiquitous super-connectivity in the global scale – i.e., beyond indoors, dense downtown or campus-type areas – is infeasible with the legacy terrestrial network architecture as this would require prohibitively expensive gross over-provisioning. The problem will only exacerbate with even more demanding 6G use-cases such as UAVs requiring connectivity (ex: delivery drones), thus the 3D super-connectivity.

In this talk, we will present a 5-layer vertical architecture composed of fully integrated terrestrial and non-terrestrial layers for 6G networks of 2030s:

  • Terrestrial HetNets with macro-, micro-, and pico-BSs
  • Flying-BSs (aerial-/UAV-/drone-BSs); altitude: up to several 100 m
  • High Altitude Platforms (HAPs) (floating-BSs); altitude: 20 km
  • Very Low Earth Orbit (VLEO) satellites; altitude: up to 1,000 km
  • Geostationary Orbit (GEO) satellites; altitude: 35,786 km

In the absence of a clear technology roadmap for the 2030s, the talk has, to a certain extent, an exploratory view point to stimulate further thinking and creativity. We are certainly at the dawn of a new era in wireless research and innovation; the next twenty years will be very interesting.

No specialized knowledge is expected from the audience. Researchers, engineers, and policy makers from government, industry, and academia (including graduate students and 4th year undergraduate students) will benefit from this visionary tutorial.

Speaker: Halim Yanikomeroglu, Professor, Carleton University

Halim Yanikomeroglu is a Professor at Carleton University. His research covers many aspects of communications technologies with emphasis on wireless networks. He supervised 20 PhD students (all completed with theses). He coauthored 360+ peer-reviewed research papers including 125 in the IEEE journals; these publications have received 11,000+ citations. He is a Fellow of IEEE, a Distinguished Lecturer for the IEEE Communications Society, and a Distinguished Speaker for the IEEE Vehicular Technology Society. He has been one of the most frequent tutorial presenters in the leading international IEEE conferences (30 times). He has had extensive collaboration with industry which resulted in 25 granted patents (plus more than a dozen applied). During 2012-2016, he led one of the largest academic-industrial collaborative research projects on pre-standards 5G wireless, sponsored by the Ontario Government and the industry. He served as the General Chair and Technical Program Chair of several major international IEEE conferences.


TUT-8: Coding Theory Based Cryptography for the Internet-of-Things
Speakers: Nuh Aydin, Bahattin Yildiz, and Suleyman Uludag