Workshops and Tutorials

Session HWS1-S1: 5G and Beyond Technology-enabled Remote Health Systems I Session HWS1-S2: 5G and Beyond Technology-enabled Remote Health Systems II
Session HWS2-S1: Invited Keynote Speakers - Part 1 Session HWS2-S2: Aerial Communications in 5G and Beyond Networks Session HWS2-S3: Invited Keynote Speakers - Part 2 Session HWS2-S4: Panel Discussion
Session HWS5-S1: Invited Keynote Presenations Session HWS5-S2: Full Duplex Radio Technologies
Session FWS7-S1: Invited Keynote Presentation Session FWS7-S2: Distributed Sensing and Localization Session FWS7-S3: IoT Applications
Session FWS6-S1: Caching in Heterogenous Wireless Network Session FWS6-S2: Coded Caching at Network Edge Session FWS6-S3: Intellignet Edge Computing Session FWS6-S4: Enabling the Network Edge Intelligence
Session HWS10-Opening: Opening Session Session HWS10-Keynote: Keynote Session HWS10-S1: Smart Spectrum 1 Session HWS10-S2: Smart Spectrum 2
Session FWS8-S1: Invited Keynote Speaker - 1 Session FWS8-S2: Session 1: Open-RAN Infrastructure Session FWS8-S3: Invited Keynote Speaker - 2 Session FWS8-S4: Invited Keynote Speaker - 3 Session FWS8-S5: Session 2: Open-RAN Modelling and Analysis Session FWS8-S6: Invited Keynote Speaker - 4 Session FWS8-S7: Session 3: Open-RAN Intelligent ML/AI Evaluations
Session FWS9-S1: Mobile Wireless Networks Session FWS9-S2: Future Networking Technologies Session FWS9-S3: Intelligent Communication Technologies Session FWS9-S4: Communication Techniques
Session FWS3-S1: Keynotes and Industry Activity Session FWS3-S2: Measurements, RFIC, and Optical Methods Session FWS3-S3: Metasurface, Lens, and OAM Session FWS3-S4: Channel Sounder, Antenna Array, and MIMO
Session TUT01: Tutorial: Federated Learning at the Network Edge: Fundamentals, Key Technologies, and Future Trends Session TUT02: Tutorial: Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Networks Session TUT03: Tutorial: Machine Learning for Future Wireless Networks Session TUT05: Tutorial: Moving Towards Zero-Touch Automation, A Key Enabler for 6G: The Challenges & Opportunities Session TUT06: Tutorial: B5G: A New Frontier for Non-Orthogonal Multiple Access Session TUT04: Tutorial: Wireless Transmission for Advanced Internet of Things: A Unifying Data-Oriented Approach Session TUT07: Tutorial: UAV Communications in 5G and Beyond: Integration of Sensing, Control, and Learning Session TUT08: Tutorial: Orthogonal Time Frequency Space (OTFS) Modulation and Applications Session TUT09: Tutorial: URLLC for 5G and Beyond: Physical, MAC and Network Design and Solutions Session TUT10: Tutorial: NOMA-Based Random Access for Massive MTC in 5G
Session FWS4-S1: Access and Core Technologies: Part I Session FWS4-S2: Access and Core Technologies: Part II Session FWS4-S3: Architecture, Business Model and Services

Aerial Communications in 5G and Beyond Networks

Session HWS2-S1

Invited Keynote Speakers - Part 1

Conference
2:00 PM — 3:20 PM KST
Local
May 24 Sun, 10:00 PM — 11:20 PM PDT

Keynote: Challenges and benefits of 5G in Urban Air Mobility (Air taxis and logistics)

Gokul Srinivasan (Robots.expert, Finland)

4
This talk does not have an abstract.

Keynote: TERAWAY project: THz technology for ultra-broadband and ultra-wideband operation of BH and FH links in systems with SDN management of network and radio resources

Maria Massaouti (National Technical University of Athens, Greece)

2
This talk does not have an abstract.
Session Chair

Edward Mutafungwa (Aalto University, Finland), Toktam Mahmoodi (King's College London, United Kingdom)

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Session HWS2-S2

Aerial Communications in 5G and Beyond Networks

Conference
3:20 PM — 4:30 PM KST
Local
May 24 Sun, 11:20 PM — 12:30 AM PDT

Time-Weighted Coverage of Integrated Aerial and Ground Networks for Post-Disaster Communications

Xiaoli Xu and Yong Zeng (Southeast University, China)

1
In this paper, we propose a new three dimensional (3D) networking architecture with integrated aerial and ground base stations (BSs) for swift post-disaster communication recovery. By exploiting their respective advantages in terms of response time, coverage area, and operational duration, the proposed network is highly heterogeneous, consisting of sustained ground BSs, ground-vehicle mounted BSs, dropping-off BSs and flying BSs. To reflect the importance of swift communication recovery and the dynamics of coverage area in post-disaster scenarios, we propose a new performance metric called "time weighted coverage", which is an integration of the achieved communication coverage area multiplied with a weighting function over time. By choosing different weighting functions, the network deployment can be designed to achieve tradeoffs between the "swift communication recovery" and "stable communication coverage". Simulation results show that the proposed integrated aerial and ground network has high implementation flexibility and it can significantly enhance the communication coverage compared with the conventional approaches.

Joint Trajectory Optimization and Time Slot Allocation for Buffer-Aided UAV Mobile Relaying

Yili Liu, Ning Wang, Lingfeng Shen, Zhengyu Zhu and Xiaomin Mu (Zhengzhou University, China)

1
Unmanned aerial vehicle (UAV) communication has attracted increasing research interests in the wireless communication community recently. In this paper, we study a buffer-aided single-UAV mobile relaying system which assists communication between a source node and a destination node on the ground. Specifically, in a slotted time system where each time slot is assumed to experience quasi-static channel condition, we optimize the buffer-aided UAV relay's flight trajectory and the allocation of the time slots for transmission and reception, subject to the information causality and UAV mobility constraints. The original formulated problem is non-convex and the two sets of design variables are coupled, which make the problem challenging. In order to make the problem tractable, we relax and decompose the problem into two subproblems, i.e., the flight trajectory optimization subproblem and the time slot allocation subproblem, such that the trajectory variables and the time slot allocation variables are decoupled. Each subproblem can then be solved effectively by fixing the other set of design variables. The two subproblems are optimized in an alternating manner until convergence to solve the problem. Simulation results show that the proposed iterative algorithm is efficient and fast converging.

Robust AN-Aided Secure Beamforming Design for A2G Communication Networks with UAV Jitter

Yang Wen, Huici Wu, Hanjie Li and Xiaofeng Tao (Beijing University of Posts and Telecommunications, China)

1
Vibrations of UAV platform have great negative impact on establishing robust and secure transmission link in air-to-ground (A2G) wiretap system. In this paper, we investigate robust and secure beamforming in a downlink A2G wiretap network considering the impact of UAV jitter. Worst-case secrecy rate maximization by jointly optimizing the beamformer of confidential signal and artificial noise signal is studied. Detailed, considering the impact of UAV jitter on the antenna array response, the worst case indicates the scenario with the minimum legitimate data rate and the maximum eavesdropping data rate. The formulated problem is a non-convex optimization. To tackle it, auxiliary variables are introduced and Taylor expansion is employed to linearize the term related to each auxiliary
variable. Further, the non-convex problem is then reformulated with linear approximation for channel variations and linear matrix inequality alternation for constraints with the aid of S-procedure and Cauchy-Schwarz inequality. Finally, a robust iterative algorithm is proposed to obtain the optimal solutions to the reformulated problem. Numerical results demonstrate the effectiveness of the proposed robust beamforming scheme and the solutions.

A Public Safety Framework for Immersive Aerial Monitoring through 5G Commercial Network

Sejin Seo, Seunghwan Kim and Seong-Lyun Kim (Yonsei University, Korea (South))

1
Are 5G connection and UAVs merely parts of an extravagant and luxurious world, or are they essential parts of a practical world in a way we have yet to see? To aid in a direction to address the issue, we provide a practical framework for immersive aerial monitoring for public safety. Because the framework is built on top of actual realizations and implementations designed to fulfill specific use cases, high level of practicality is ensured by nature. We first investigate 5G network performance on UAVs by isolating performance for different aspects of expected flight missions. Finally, the novel aerial monitoring scheme that we introduce relies on the recent advances brought by 5G networks and mitigates the inherent limitations of 5G network that we investigate in this paper.

Energy-Efficient UAV Communications with Interference Management: Deep Learning Framework

Fayezeh Ghavimi (Aalto University School of Electrical Engineering, Finland); Riku Jäntti (Aalto University, Finland)

1
In this paper, an interference-aware energy-efficient scheme for a network of coexisting aerial-terrestrial cellular users is proposed. In particular, each aerial user aims at achieving a trade-off between maximizing energy efficiency and spectral efficiency while minimizing the incurred interference on the terrestrial users along its path. To provide a solution, we first formulate the energy efficiency problem for UAVs as an optimization problem by considering different key performance indicators (KPIs) for the network, coexisting terrestrial users, and UAVs as aerial users. Then, leveraging tools from deep learning, we transform this problem into a deep queue learning problem and present a learning-powered solution that incorporates the KPIs of interest in the design of the reward function to solve energy efficiency maximization for aerial users while minimizing interference to terrestrial users. A broad set of simulations have been conducted in order to investigate how the altitude of UAVs, and the tolerable level of interference, shape the optimal energy-efficient policy in the network. Simulation results show that the proposed scheme achieves better energy and spectral efficiency for UAV and less interference to terrestrial users incurred from aerial users. The obtained results further provide insights on the benefits of leveraging intelligent energy-efficient schemes. For example, a significant increase in the energy efficiency of aerial users with respect to increases in their spectral efficiency, while a considerable decrease in incurred interference to the terrestrial users is achieved in comparison to the non-learning scheme.
Session Chair

Edward Mutafungwa (Aalto University, Finland), Toktam Mahmoodi (King's College London, United Kingdom)

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Session HWS2-S3

Invited Keynote Speakers - Part 2

Conference
4:30 PM — 5:20 PM KST
Local
May 25 Mon, 12:30 AM — 1:20 AM PDT

Keynote: Intelligent Sensing in the IoT using Data-aided Sensing

Jinho Choi (Deakin University, Australia)

1
As a number of Internet-of-Things (IoT) applications need to collect data sets from a large number of sensors or devices in real-time, sensing and communication can be integrated for efficient uploading from devices. In this talk, we introduce the notion of data-aided sensing (DAS) for efficient data collection or sensing with limited wireless bandwidth. Based on DAS, certain tasks in IoT applications, including federated learning, can be carried out by uploading from a small number of selected devices. Two different types of DAS are considered: one is centralized DAS and the other is distributed DAS. In centralized DAS, a gateway or base station decides the uploading order, while each device can decide when to upload its own local data set among multiple uploading rounds in distributed DAS. In distributed DAS, random access is employed where the access probability of each device is decided according to its local measurement for efficient uploading.

Keynote: NFV in the air

Fabrizio Granelli (University of Trento, Italy)

1
This talk does not have an abstract.
Session Chair

Edward Mutafungwa (Aalto University, Finland), Toktam Mahmoodi (King's College London, United Kingdom)

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Session HWS2-S4

Panel Discussion

Conference
5:20 PM — 6:00 PM KST
Local
May 25 Mon, 1:20 AM — 2:00 AM PDT
Session Chair

Edward Mutafungwa (Aalto University, Finland), Toktam Mahmoodi (King's College London, United Kingdom)

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