Workshops

Session AoI-S1: Session 1: Information Updates for Estimation, Computing and Control Session AoI-S2: Session 2: Age of Information and Energy Efficiency Session AoI-S3: Session 3: Age of Information and Emerging Applications Session AoI-S4: Session 4: Age of Information in Wireless Networks
Session BigSecurity-S1: Big Security 1 Session BigSecurity-S2: Big Security 2 Session BigSecurity-S3: Big Security 3 Session BigSecurity-S4: Big Privacy 1
Session BlockSecSDN-KT1: Keynote Talk 1 Session BlockSecSDN-1: Software-Defined Networks Session BlockSecSDN-2: Internet of Things Session BlockSecSDN-KT2: Keynote Talk 2 Session BlockSecSDN-3: Vehicular Networks Session BlockSecSDN-4: Smart Grid and Heterogeneous Networks
Session Coffee-Break-1-AM: Virtual Coffee Break Session Lunch-Break-1: Virtual Lunch Break Session Coffee-Break-1-PM: Virtual Coffee Break
Session CNERT-Opening: Opening Session Session CNERT-Keynote: Keynote Session CNERT-Session-I: Session I: Wireless Networks Session CNERT-Panel-on-Reproducibility: Panel on Reproducibility Session CNERT-Session-II: Session II: Wired Networks Session CNERT-Demo-Session: Demo Session Session CNERT-Closing: Reproducibility Award and Closing
Session DDINS-OS: Opening Session — Message from the Chairs Session DDINS-S1: Data Driven Smart Cities Session DDINS-K1: Keynote Session 1 Session DDINS-S2: Data Driven Intelligent Computing and Application Session DDINS-S3: Data Driven Distributed Computing Session DDINS-K2: Keynote Session 2 Session DDINS-S4: Data Driven Brain Computing Session DDINS-S5: Data Driven Networking 1 Session DDINS-S6: Data Driven Networking 2
Session DroneCom-Opening: Opening Session Session DroneCom-KS1: Keynote Session 1 Session DroneCom-TS1: Technical Session I: Industrial Internet of Things Session DroneCom-IT1: Industrial Talk 1 Session DroneCom-IT2: Industrial Talk 2 Session DroneCom-TS2: Technical Session II: Heterogeneous Networks Session DroneCom-KS2: Keynote Session 2 Session DroneCom-TS3: Technical Session III: Security and Energy Efficiency Session DroneCom-IT3: Industrial Talk 3 Session DroneCom-TS4: Technical Session IV: Other Drone Applications Session DroneCom-Closing: Concluding Remarks
Session EdgeBlock-Open: Opening Session — Message From Chairs Session EdgeBlock-S1: Blockchain and Fog/Edge Session EdgeBlock-S2: Blockchain Application 1 Session EdgeBlock-S3: Smart Contract Session EdgeBlock-S4: Blockchain and RNG Session EdgeBlock-S5: Decentralization Session EdgeBlock-S6: Blockchain Application 2
Session Opening-HotPOST: Opening Remarks Session Keynote-HotPOST: Keynote Talk Session S1-HotPOST: Session 1: Pervasive Applications Session S2-HotPOST: Session 2: Social Systems Session Closing-HotPOST: Closing Remarks
Session ICCN-Opening: Opening Session Session ICCN-S1: Session 1: Cloud Applications 1 Session ICCN-KS1: Keynote Session 1 Session ICCN-S2: Session 2: Cloud Network Session ICCN-S3: Session 3: Cloud System Session ICCN-S4: Session 4: Cloud Security Session ICCN-KS2: Keynote Session 2 Session ICCN-S5: Session 5: Cloud Applications 2 Session ICCN-S6: Session 6: Edge Cloud
Session IWECN-S1: Session 1: Network Planning Session IWECN-S2: Session 2: Network Reliability
Session MobiSec-S1: Mobile Security Session MobiSec-Keynote: Keynote Session MobiSec-S2: Network & Communication Security Session MobiSec-S3: Privacy, Trust & Threats Session MobiSec-S4: General Topics
Session NI-Opening: Opening Session NI-Session-1: Session 1: Networking Aspects Session NI-Keynote: Keynote Session NI-Session-2: Session 2: Resource Management Aspects Session NI-Closing: Closing
Session New-IP-Opening: Opening Session Session New-IP-Keynote: Keynote Speech Session New-IP-S1: Session 1: The X-D-N for New Protocol Session New-IP-S2: Session 2: The New IP Capabilities and Protocol Design
Session PERSIST-IoT-Opening: Opening Session Session PERSIST-IoT-S1: Physical Layer Session PERSIST-IoT-kS1: Keynote Session Session PERSIST-IoT-S2: NOMA Session PERSIST-IoT-S3: Automated Connected Vehicles Session PERSIST-IoT-S4: Edge Computing & IoT
Session WCNEE-Opening: Opening Session Session WCNEE-Keynote: Keynote Session Session WCNEE-S1: Session 1: Secure and Reliable Communications in Smart Grid, Deep Space, Underwater and Wireless UAV Networks Session WCNEE-S2: Session 2: Wireless Communication and Localization Protocols for Underground Sensing, Autonomous Vehicles and In-Vivo NanoSensor Networks Session WCNEE-Closing: Closing Session
Session WNA-Opening: Opening Session Session WNA-Session-I: Session 1: Traffic Optimization Algorithms Session WNA-Demo-Session: Demo and Banner Show Session WNA-Session-II: Session 2: Traffic Engineering and Machine Learning
Session WISARN-O: Opening Session Session WISARN-K: Keynote Session Session WISARN-S1: Session I: Communication Technologies for UAV Tracking and Networking Session WISARN-S2: Session II: Integrating 5G and UAV Networks Session WISARN-S3: Session III: Frameworks for UAV-Based Networking and Computation

The 3rd International Workshop on Intelligent Wireless Emergency Communications Networks: Theory and Applications (IWECN 2020)

Session IWECN-S1

Session 1: Network Planning

Conference
9:00 AM — 10:40 AM EDT
Local
Jul 6 Mon, 6:00 AM — 7:40 AM PDT

A Dynamic Resource Allocation Scheme in Vehicular Communications

Akinsola S Akinsanya (University of Kent, UK) Manish Nairn (University of Kent, UK) Yijin Pan (Southeast University, China & University of Kent, UK) Jiangzhou Wang (University of Kent, UK)

2
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 at the 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 vehicles is more than the number of beams, and (ii) vehicles 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, a joint vehicle beam allocation (VBA) and vehicular proximity (VP) algorithms for V2I and V2V, respectively are proposed for 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 V2I. It is proven that the outage probability and rates are also directly dependent on SINR thresholds. Lastly, the concept of utility ratio is also introduced as a metric for reliability. It is proven that joint V2I and V2V communication significantly improves the utility ratio.

Resource Allocation in Drone-Assisted Emergency Communication System

Tianqi Chen (University of Kent, UK) Jian He (Shanghai Aerospace Electronic Technology Institute & Key Laboratory of Intelligent Computing Technology (SAST), China) Huiling Zhu (University of Kent, UK) Lin Cai (Xidian University, China) Peng Yuen (Xidian University, China) Jiangzhou Wang (University of Kent, UK)

0
It is crucial for emergency communication networks to properly manage and coordinate between rescuers and disaster-affected users. Low-cost and high-mobility drones become important contributors to build up such kind of emergency communication networks. In this paper, we consider the drone as a deployed base station to provide communication for ground users in the post-disaster area. Considering the importance of providing guaranteed service for rescuers (compared to normal users), we have investigated power and subcarrier allocation to maximize the downlink system capacity in the drone-assisted emergency communication system. Due to the complexity of the formulated problem. a suboptimal solution is proposed by dividing users into two priority groups: high-priority users (rescuers) and low-priority users (affected people). According to analyses, the complexity of the proposed scheme is much lower than the optimal scheme. Simulation results have shown that when the transmit power of the drone is not very high, the performance of the proposed resource allocation scheme is very close to the optimal scheme.

Intelligent UAV Based Flexible 5G Emergency Networks: Field Trial and System Level Results

Gao Yuan (Tsinghua University, China) Jiang Cao (Academy of Military Science of PLA, China) Ping Wang (Tsinghua University, China) Junsong Yin (Academy of Military Science of PLA, China) Ming He (CMCC, China) Ming Zhao (Tsinghua University, China) Mugen Peng (Beijing University of posts & Telecommunications, China) Su Hu (University of Electronic Science and Technology of China, China) Yunchuan Sun (Beijing Normal University, China) Jing Wang (Academy of Military Science of PLA, China) Shaochi Cheng (CDSTIC, China) Yang Guo (CDSTIC, China) Yanchang Du (CDSTIC, China) Yanxi Cai (Academy of Military Science of PLA, China) Jinhui Huang (Academy of Military Science of PLA, China) Kai Qiu (Academy of Military Science of PLA, China)

0
The commercialization of 5G is increasing in recent days, will provide users with satisfied speed and more reliable QoS. UAV is one possible carrier of wireless base stations and provide flexible coverage and wireless services to target users. In this work, we discuss an intelligent UAV based 5G emergency network model, with dedicated base stations, core networks and smart MIMO antennas located on UAV. As a solution of emergency environment, this model could provide timely access to users with higher speed, more flexible access mode, smart coverage area, customized service and longer time of duration. Field trial and system level simulation have been provided prior to this work and the results seem promising in some main indicators, the coverage area could exceed the radius of 30km, the downlink speed per user could reach 200Mbps when the height is within 4km. The remaining problems of the resource allocation, power control, deployment, etc. are still open for researchers to tackle.

An Integrated Platoon and UAV System for 3D Localization in Search and Rescue

Hongming Zhang (Beijing University of Posts and Telecommunications, China) Li Wang (Beijing University of Posts and Telecommunications, China) Aiguo Fei (Beijing University of Posts and Telecommunications, China)

0
In search and rescue (SAR), survivals' localization information is required to be obtained as quickly and accurately as possible. However, due to the accidental and destructive natural of emergency events, existing network infrastructures and devices may be unable to be use for performing the localization tasks. Furthermore, survivals may be trapped in isolated areas, where human being is unable to reach. To address these issues, in this paper, we propose an integrated platoon and unmanned aerial vehicle (UAV) system for implementing the three-dimensional (3D) localization task in SAR, where the platoon is consisted of self-driving vehicles and UAVs are controlled by these vehicles. Furthermore, in order to facilitate 3D localization, a platoon-aided UAV deployment strategy is proposed, where UAVs are deployed in different places for collecting direction-of-arrival (DoA) information of a target. As a further enhancement, a rotational invariance based beamforming (RIB) scheme is conceived to provide a simple DoA estimation for our multiple-in-multiple-out (MIMO) UAVs. Simulation results are provided for evaluating the system performance, showing that it is capable of achieving a beneficial trade-off between the attainable 3D localization performance and the corresponding time delay.

Latency and Reliability Oriented Collaborative Optimization for Multi-UAV Aided Mobile Edge Computing System

Xiangwang Hou (Xidian University, China) Zhiyuan Ren (Xidian University, China) Jingjing Wang (Tsinghua University, China) Shuya Zheng (Xidian University, China) Hailin Zhang (Xidian University, China)

0
Intelligent emergency rescue equipment (IERE), e.g., AR/VR aided intelligent helmet, robot, etc., plays an increasingly important role in emergency rescue, which can greatly enhance the capability and efficiency of the rescue activities. However, due to the limitations of its computing and energy capacities, deal with the generated computational-intensive tasks locally is difficult, even more, in disaster areas, the destruction of the terrestrial communication infrastructure also makes the cloud-based computation offloading disabled. Therefore, in this paper, we construct a multi-UAV enabled latency and reliability guaranteed mobile edge computing framework (LR-UMEN) to provide IERE the on-demand computing services. Furthermore, considering the harsh working environment of the IERE, not only the latency but also the reliability must be taken into account. Different from the existing work about the latency and reliability, which are solely paying attention to the optimization of communication resources, or both communication and computing resources, we propose the joint optimization of communication, computing and caching to further decrease the latency as well as enhance the reliability. Besides, to better optimize the latency and reliability, we derive a new quantity, namely Expected Latency, which can effectively reflect the characteristic both of the latency and reliability of the operation unit during a given processing period. And to solve the non-convex and NP-hard optimization problem, a hybrid binary particle swarm optimization algorithm is designed, moreover, extensive simulations validate its effectiveness.
Session Chair

Wenchi Cheng

Session IWECN-S2

Session 2: Network Reliability

Conference
11:10 AM — 12:30 PM EDT
Local
Jul 6 Mon, 8:10 AM — 9:30 AM PDT

Statistical QoS Provisioning Based Caching Placement for D2D Communications Based Emergency Networks

Jianyu Wang (Xidian University, China) Wenchi Cheng (Xidian University, China) Hailin Zhang (Xidian University, China)

0
When natural disasters strike, the communication infrastructure may be severely damaged, which leads to the congestion or even destruction of communication networks. Cache can be equipped on the mobile devices of rescuers to provide imperative data for victims via device-to-device (D2D) transmissions. To support the effectiveness and timeliness of emergency communication, network throughput and delay-requirements of victims need to be comprehensively considered, which posts a new challenge for the design of caching placement strategy. In this paper, we formulate the statistical delay-bounded quality of service (QoS) provisioning framework for cache-enabled D2D emergency network. Particularly, we build up the optimization problem to maximize the average effective capacity of D2D transmissions subject to the delay-QoS requirement. Then, we prove that this optimization problem is convex. For solving this problem, we develop the QoS-aware caching placement strategy, which can maximize the average effective capacity of D2D transmission while guaranteeing the delay-QoS requirement. Simulation results verify our theoretical analyses and show that the proposed QoS-aware caching placement scheme can achieve larger average effective capacity as compared with the caching placement strategies without QoS provisioning.

Green Cognitive Internet of Things with Self Supply of Energy and Spectrum in Emergency Communications

Xin Liu (Dalian University of Technology, China) Xueyan Zhang (Dalian University of Technology, China)

0
In the emergency scenario, wireless communications will face spectrum shortage and energy cut-off in case of infrastructure destruction. In this paper, a green cognitive Internet of Things (CIoT) with wireless energy harvesting (WEH) is proposed to share the spectrum licensed to primary user (PU) and harvest its radio frequency (RF) energy, in order to achieve self supply of energy and spectrum. Energy-efficient resource allocations are presented to maximize the average transmission rate of CIoT while guaranteeing the energy saving requirements. The underlay and overlay spectrum access models for CIoT with WEH are described, in which the energy-efficient resource allocations are formulated as joint optimization problems that can be solved using alternating direction optimization (ADO) and Karush-Kuhn-Tucker (KKT) conditions. Results show that the CIoT with WEH can consume less power to achieve larger transmission rate.

RAT-NHP: Radio Access Technology Selection Based on N-hop Prediction

Weifeng Sun (Dalian University of Technology, China) Guanghao Zhang (Dalian University of Technology, China) Yuankui Zhang (Dalian University of Technology, China)

1
Radio access technology (RAT) is the decision for user to choose a best target network during network entry or vertical handover. It could be used for the rescuing scenario in the wireless multi-hop UVA networks. Most researches about RAT selection focus on heterogeneous cell networks. The RAT selection method for cell networks is no longer suitable for heterogeneous wireless multi-hop network (HWMN), because the communicating quality to the expected access point (EAP) couldn't reflect the whole network capability due to its multi-hop characteristic. This paper presents a novel metric, named n-hop prediction (NHP), for RAT selection in HWMN. It takes into account of network capability and load within n-hop range of the expected access point, besides users QoS requirement. Simulation results reveal that the proposed approach achieves better performance than that without considering these factors.

Security Enhancement and Evaluation for Noise Aggregation over Wireless Fading Channels

Yu Liu (Xi'an Jiaotong University, China) Qinghe Du (Xi'an Jiaotong University, China)

0
This paper studies the noise aggregation scheme with convolutional code in frequency-flat block-fading channel. While there is still a lot of limitation in the noise aggregation scheme, we combine the noise aggregation scheme with convolutional code for further study. By analysing the structure of its encoding system, we derives the optimal decoding algorithm in this scheme, and design three different decoding schemes. Considering the complexity and correctness of the decoding progress, we will adopt different decoding scheme in different situation. Due to the introduction of fading channel, the effect of the noise aggregation scheme has been increased significantly. In the meanwhile, we combine the noise aggregation scheme with adaptive modulation technology, the advantage of noise aggregation become more obvious. Simulation results show that the noise aggregation scheme can achieve a remarkable safety performance improvement and have good application prospects.
Session Chair

Huiling Zhu

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