A Stackelberg-game approach for disaster-recovery communications utilizing cooperative D2D

In this paper, we investigate disaster-recovery com- munications utilizing two-cell cooperative D2D communications. Specifically, one cell is in a healthy area while the other is in a disaster area. A user equipment (UE) in the healthy area aims to assist a UE in the disaster area to recover wireless information transfer (WIT) via an energy harvesting (EH) relay. In the healthy area, the cellular BS shares the spectrum with the UE, however, both of them may belong to different service providers. Thus, the UE pays an amount of price as incentive to the BS as part of two processes: energy trading and interference pricing. We formulate these two processes as two Stackelberg games, where their equilibrium is derived as closed- form solutions. The results help provide a sustainable framework for disaster recovery when the involving parties juggle between energy trading, interference compromise and payment incentives in establishing communications during the recovery process

A Stackelberg-game approach for disaster-recovery communications utilizing cooperative D2D

In this paper, we investigate disaster-recovery com- munications utilizing two-cell cooperative D2D communications. Specifically, one cell is in a healthy area while the other is in a disaster area. A user equipment (UE) in the healthy area aims to assist a UE in the disaster area to recover wireless information transfer (WIT) via an energy harvesting (EH) relay. In the healthy area, the cellular BS shares the spectrum with the UE, however, both of them may belong to different service providers. Thus, the UE pays an amount of price as incentive to the BS as part of two processes: energy trading and interference pricing. We formulate these two processes as two Stackelberg games, where their equilibrium is derived as closed- form solutions. The results help provide a sustainable framework for disaster recovery when the involving parties juggle between energy trading, interference compromise and payment incentives in establishing communications during the recovery process

Architecture design for disaster resilient management network using D2D technology

Huge damages from natural disasters, such as earthquakes, floods, landslide, tsunamis, have been reported in recent years, claiming many lives, rendering millions homeless and causing huge financial losses worldwide. The lack of effective communication between the public rescue/safety agencies, rescue teams, first responders and trapped survivors/victims makes the situation even worse. Factors like dysfunctional communication networks, limited communications capacity, limited resources/services, data transformation and effective evaluation, energy, and power deficiency cause unnecessary hindrance in rescue and recovery services during a disaster. The new wireless communication technologies are needed to enhance life-saving capabilities and rescue services. In general, in order to improve societal resilience towards natural catastrophes and develop effective communication infrastructure, innovative approaches need to be initiated to provide improved quality, better connectivity in the events of natural and human disasters. In this thesis, a disaster resilient network architecture is proposed and analysed using multi-hop communications, clustering, energy harvesting, throughput optimization, reliability enhancement, adaptive selection, and low latency communications. It also examines the importance of mode selection, power management, frequency and time resource allocation to realize the promises of Long-term Evolution (LTE) Device to Device (D2D) communication. In particular, to support resilient and energy efficient communication in disaster-affected areas. This research is examined by thorough and vigorous simulations and validated through mathematical modelling. Overall, the impact of this research is twofold: i) it provides new technologies for effective inter- and intra-agency coordination system during a disaster event by establishing a stronger and resilient communication; and ii) It offers a potential solution for stakeholders such as governments, rescue teams, and general public with new informed information on how to establish effective policies to cope with challenges before, during and after the disaster events

IEEE Access special section editorial: Mission critical public-safety communications: architectures, enabling technologies, and future applications

Disaster management organizations such as fire brigades, rescue teams, and emergency medical service providers have a high priority demand to communicate with each other and with the victims by using mission-critical voice and data communications [item 1) in the Appendix]. In recent years, public safety agencies and organizations have started planning to evolve their existing land mobile radio system (LMRS) with long-term evolution (LTE)-based public safety solutions which provides broadband, ubiquitous, and mission-critical voice and data services. LTE provides high bandwidth and low latency services to the customers using internet protocol-based LTE network. Since mission critical communication services have different demands and priorities for dynamically varying situations for disaster-hit areas, the architecture and the communication technologies of the existing LTE networks need to be upgraded with a system that has the capability to respond efficiently and in a timely manner during critical situations

A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network

Low-latency Data Uploading in D2D-enabled Cellular Networks

指導教員：姜　暁

Radio Resource Management for Unmanned Aerial Vehicle Assisted Wireless Communications and Networking

In recent years, employing unmanned aerial vehicles (UAVs) as aerial communication platforms or users is envisioned as a promising solution to enhance the performance of the existing wireless communication systems. However, applying UAVs for information technology applications also introduces many new challenges. This thesis focuses on the UAV-assisted wireless communication and networking, and aims to address the challenges through exploiting and designing efficient radio resource management methods. Specifically, four research topics are studied in this thesis. Firstly, to address the constraint of network heterogeneity and leverage the benefits of diversity of UAVs, a hierarchical air-ground heterogeneous network architecture enabled by software defined networking is proposed, which integrates both high and low altitude platforms into conventional terrestrial networks to provide additional capacity enhancement and expand the coverage of current network systems. Secondly, to address the constraint of link disconnection and guarantee the reliable communications among UAVs as aerial user equipment to perform sensing tasks, a robust resource allocation scheme is designed while taking into account the dynamic features and different requirements for different UAV transmission connections. Thirdly, to address the constraint of privacy and security threat and motivate the spectrum sharing between cellular and UAV operators, a blockchain-based secure spectrum trading framework is constructed where mobile network operators and UAV operators can share spectrum in a distributed and trusted environment based on blockchain technology to protect users' privacy and data security. Fourthly, to address the constraint of low endurance of UAV and prolong its flight time as an aerial base station for delivering communication coverage in a disaster area, an energy efficiency maximization problem jointly optimizing user association, UAV's transmission power and trajectory is studied in which laser charging is exploited to supply sustainable energy to enable the UAV to operate in the sky for a long time

Terminal cooperation in next generation wireless networks: aerial and regional access networks

Throughout the years, progress of humankind has depended on the power of communication and over the decades, the ways of communication has witnessed mammoth changes. Specifically wireless communication in the last decade has completely revolutionized the way we communicate with each other. Smartphones have become an ubiquitous part of our life. With most operators throughout the world deploying fourth generation wireless communication systems, peculiar use cases and scenarios are being envisioned such as public safety networks, aerial networks, etc. to be addressed by the next generation wireless systems. Moreover, as urban areas are becoming saturated commercial network operators are looking for business cases to move towards the untapped regional areas. However, to deploy networks in regional areas economically, novel technologies and architectures need to be developed and investigated. In this thesis, we study the novel concept of terminal cooperation in the context of next generation wireless communication systems especially looking into aerial and regional access networks. In the first part of the thesis, we investigate the physical radio channel for device-to-device (D2D) communication which would help in enabling terminal cooperation in wireless networks. Specifically, we propose propagation model for D2D in rural areas using 922 MHz and 2466 MHz, a channel model for vehicular communications using 5.8 GHz and a propagation model for D2D using millimetre wave frequencies. In the second part of the thesis, we evaluate the coverage performance of aerial access networks using different technologies and develop algorithms to enhance the coverage using terminal cooperation in regional access networks. Specifically, we evaluate the performance of two different technologies, LTE and WiFi, in aerial access networks. We propose game-theoretic algorithms to enable terminal cooperation to enhance coverage in regional access networks and perform system level simulation to evaluate the proposed algorithms. In the last part of this thesis, we analyse and develop techniques to enhance energy efficiency in aerial access networks using terminal cooperation. Specifically, we propose a clustering algorithm called EECAN which improves the energy efficiency of the terrestrial nodes accessing the aerial base-station, a clustering algorithm based on Matern Hardcore Point Process which allows us to optimize cluster head spacing analytically and we further enhance this algorithm by including impairments introduced by the wireless channel. Throughout this thesis, we verify and validate our analytic results, algorithms and techniques with Monte-Carlo simulations of the considered scenarios. Most of the work presented in this thesis was published in-part or as a whole in conferences, journals, book-chapters, project reports or otherwise undergoing a review process. These publications and reports are highlighted in the course of the thesis. Lastly, we invite the reader to enjoy exploring this thesis and we hope that it will add more understanding to this promising new technology of terminal cooperation in aerial and regional access networks

Computing on the Edge of the Network

Um Systeme der fünften Generation zellularer Kommunikationsnetze (5G) zu ermöglichen, sind Energie effiziente Architekturen erforderlich, die eine zuverlässige Serviceplattform für die Bereitstellung von 5G-Diensten und darüber hinaus bieten können. Device Enhanced Edge Computing ist eine Ableitung des Multi-Access Edge Computing (MEC), das Rechen- und Speicherressourcen direkt auf den Endgeräten bereitstellt. Die Bedeutung dieses Konzepts wird durch die steigenden Anforderungen von rechenintensiven Anwendungen mit extrem niedriger Latenzzeit belegt, die den MEC-Server allein und den drahtlosen Kanal überfordern. Diese Dissertation stellt ein Berechnungs-Auslagerungsframework mit Berücksichtigung von Energie, Mobilität und Anreizen in einem gerätegestützten MEC-System mit mehreren Benutzern und mehreren Aufgaben vor, das die gegenseitige Abhängigkeit der Aufgaben sowie die Latenzanforderungen der Anwendungen berücksichtigt.To enable fifth generation cellular communication network (5G) systems, energy efficient architectures are required that can provide a reliable service platform for the delivery of 5G services and beyond. Device Enhanced Edge Computing is a derivative of Multi-Access Edge Computing (MEC), which provides computing and storage resources directly on the end devices. The importance of this concept is evidenced by the increasing demands of ultra-low latency computationally intensive applications that overwhelm the MEC server alone and the wireless channel. This dissertation presents a computational offloading framework considering energy, mobility and incentives in a multi-user, multi-task device-based MEC system that takes into account task interdependence and application latency requirements