Direct-to-satellite (DtS) communication has gained importance recently to support globally connected Internet of things (IoT) networks. However, relatively long distances of densely deployed satellite networks around the Earth cause a high path loss. In addition, since high complexity operations such as beamforming, tracking and equalization have to be performed in IoT devices partially, both the hardware complexity and the need for high-capacity batteries of IoT devices increase. The reconfigurable intelligent surfaces (RISs) have the potential to increase the energy-efficiency and to perform complex signal processing over the transmission environment instead of IoT devices. But, RISs need the information of the cascaded channel in order to change the phase of the incident signal. This study evaluates the pilot signal as a graph and incorporates this information into the graph attention networks (GATs) to track the phase relation through pilot signaling. The proposed GAT-based channel estimation method examines the performance of the DtS IoT networks for different RIS configurations to solve the challenging channel estimation problem. It is shown that the proposed GAT both demonstrates a higher performance with increased robustness under changing conditions and has lower computational complexity compared to conventional deep learning methods. Moreover, bit error rate performance is investigated for RIS designs with discrete and non-uniform phase shifts under channel estimation based on the proposed method. One of the findings in this study is that the channel models of the operating environment and the performance of the channel estimation method must be considered during RIS design to exploit performance improvement as far as possible.
Internet of Things (IoT) is an innovative paradigm envisioned to provide massive applications that are now part of our daily lives. Millions of smart devices are deployed within complex networks to provide vibrant functionalities including communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art centralized cloud computing paradigm due to the bandwidth and resources scarcity. Hence, edge computing (EC) is eme…
School of Information Science and Technology, ShanghaiTech University（上海科技大学信息科学与技术学院）
In fog-assisted IoT systems, it is a common practice to offload tasks from IoT devices to their nearby fog nodes to reduce task processing latencies and energy consumptions. However, the design of online energy-efficient scheme is still an open problem because of various uncertainties in system dynamics such as processing capacities and transmission rates. Moreover, the decision-making process is constrained by resource limits on fog nodes and IoT devices, making the design even more complicated. In this paper, we formulate such a task offloading problem with unknown system dynamics as a combi…
In Fog-assisted IoT systems, it is a common practice to cache popular content at the network edge to achieve high quality of service. Due to uncertainties in practice such as unknown file popularities, cache placement scheme design is still an open problem with unresolved challenges: 1) how to maintain time-averaged storage costs under budgets, 2) how to incorporate online learning to aid cache placement to minimize performance loss (a.k.a. regret), and 3) how to exploit offline historical information to further reduce regret. In this paper, we formulate the cache placement problem with unknow…
Emerged as a promising solution for future wireless communication systems, intelligent reflecting surface (IRS) is capable of reconfiguring the wireless propagation environment by adjusting the phase-shift of a large number of reflecting elements. To quantify the gain achieved by IRSs in the radio frequency (RF) powered Internet of Things (IoT) networks, in this work, we consider an IRS-assisted cellular-based RFpowered IoT network, where the cellular base stations (BSs) broadcast energy signal to IoT devices for energy harvesting (EH) in the charging stage, which is utilized to support the up…
Unmanned aerial vehicle (UAV)-assisted data collection has been emerging as a prominent application due to its flexibility, mobility, and low operational cost. However, under the dynamic and uncertainty of IoT data collection and energy replenishment processes, optimizing the performance for UAV collectors is a very challenging task. Thus, this paper introduces a novel framework that jointly optimizes the flying speed and energy replenishment for each UAV to significantly improve the data collection performance. Specifically, we first develop a Markov decision process to help the UAV automatic…
A Home Area Network (HAN) is considered to be a significant component of Advanced Metering Infrastructure (AMI) and has been studied well in many works. It binds all the electrical components installed in a defined premise together for their close monitoring and management. However, HAN has been realized so far mostly as a centralized system. Therefore, like any other centralized system, the traditional realization of HAN also suffers from various well-known problems, such as single-point-of-failure, susceptibility to attacks, requirement of specialized infrastructure, inflexibility to easy ex…
In this work we discuss the utilization of micro-satellite constellations as effective infrastructures for the communication among ground stations or even among 'smart' devices in IoT scenarios. We design and implement a series of experiments in OMNeT++ (with the OS3 framework) and evaluate their results in different scenarios. Initially, we establish the necessary theoretical background for space communications, including satellite and constellation design features, with existing and novel satellite services in various areas of interest. Furthermore, we detail the OMNeT++ and OS3 frameworks a…
HAPS-RIS-assisted IoT Networks for Disaster Recovery and Emergency Response: Architecture, Application Scenarios, and Open Challenges
Manisa Celal Bayar University（马尼萨杰拉勒巴亚尔大学）；Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)（加泰罗尼亚电信技术中心）；Zonguldak Bulent Ecevit University（宗古尔达克布伦特·埃切维特大学）；Ericsson Research（爱立信研究）；University of Antwerp–IMEC（安特卫普大学-IMEC）；Carleton University（卡尔顿大学）
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；University of Chinese Academy of Sciences（中国科学院大学）；University of Macau（澳门大学）；University of New Brunswick（新不伦瑞克大学）
As Internet of Things devices become prevalent, using intrusion detection to protect IoT from malicious intrusions is of vital importance. However, the data scarcity of IoT hinders the effectiveness of traditional intrusion detection methods. To tackle this issue, in this paper, we propose the Adaptive Bi-Recommendation and Self-Improving Network (ABRSI) based on unsupervised heterogeneous domain adaptation (HDA). The ABRSI transfers enrich intrusion knowledge from a data-rich network intrusion source domain to facilitate effective intrusion detection for data-scarce IoT target domains. The AB…
The Internet of Things (IoT) brings connectivity to a massive number of devices that demand energy-efficient solutions to deal with limited battery capacities, uplink-dominant traffic, and channel impairments. In this work, we explore the use of Unmanned Aerial Vehicles (UAVs) equipped with configurable antennas as a flexible solution for serving low-power IoT networks. We formulate an optimization problem to set the position and antenna beamwidth of the UAV, and the transmit power of the IoT devices subject to average-Signal-to-average-Interference-plus-Noise Ratio ($\bar{\text{S}}\overline{\…
Pareto-Aware Hierarchical Reinforcement Learning for Online Resource Allocation in RIS-assisted Large-Scale IoT Systems
Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology（香港科技大学工业工程与决策科学系）；Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（香港科技大学电子及计算机工程学系）
The Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. In this paper, we propose to employ unmanned aerial vehicles (UAVs) to assist the clustered IoT data collection with blockchain-based security provisioning. In particular, the UAVs generate candidate blocks based on the collected data, which are then audited through a lightweight proof-of-stake consensus mechanism within the UAV-based blockchain network. To motivate efficient blockchain while reducing the operational cos…
The Internet of objects (IoT) will have to meet the non-functional needs (QoS, security, etc.) of new business applications supported by the cloud. To do this, the interactions between the underlying application software and the communicating objects will rely on networks and communication middleware with configurable, programmable and dynamically deployable capabilities. These capabilities will be available both on pre-existing entities but also on virtual entities, i.e. that will be dynamically created in the Cloud according to the need. In this new ecosystem, meeting the end-to-end QoS need…
Unmanned Aerial Vehicles (UAVs) have been emerging as an effective solution for IoT data collection networks thanks to their outstanding flexibility, mobility, and low operation costs. However, due to the limited energy and uncertainty from the data collection process, speed control is one of the most important factors to optimize the energy usage efficiency and performance for UAV collectors. This work aims to develop a novel autonomous speed control approach to address this issue. To that end, we first formulate the dynamic speed control task of a UAV as a Markov decision process taking into…
The ever-evolving internet of things (IoT) has led to the growth of numerous wireless sensors, communicating through the internet infrastructure. When designing a network using these sensors, one critical aspect is the longevity and self-sustainability of these devices. For extending the lifetime of these sensors, radio frequency energy harvesting (RFEH) technology has proved to be promising. In this paper, we propose CURE, a novel framework for RFEH that effectively combines the benefits of cell-free massive MIMO (CFmMIMO), unmanned aerial vehicles (UAVs), and reconfigurable intelligent surfa…
Metaverse has recently attracted much attention from both academia and industry. Virtual services, ranging from virtual driver training to online route optimization for smart goods delivery, are emerging in the Metaverse. To make the human experience of virtual life more real, digital twins (DTs), namely digital replicas of physical objects, are key enablers. However, DT status may not always accurately reflect that of its real-world twin because the latter may be subject to changes with time. As such, it is necessary to synchronize a DT with its physical counterpart to ensure that its status …
University of Ottawa（渥太华大学）；Nokia Bell Labs（诺基亚贝尔实验室）
Aerial base stations (ABSs) allow smart farms to offload processing responsibility of complex tasks from internet of things (IoT) devices to ABSs. IoT devices have limited energy and computing resources, thus it is required to provide an advanced solution for a system that requires the support of ABSs. This paper introduces a novel multi-actor-based risk-sensitive reinforcement learning approach for ABS task scheduling for smart agriculture. The problem is defined as task offloading with a strict condition on completing the IoT tasks before their deadlines. Moreover, the algorithm must also co…
Long-Range Communications in Unlicensed Bands: the Rising Stars in the IoT and Smart City Scenarios
连接性可能是物联网（IoT）范式最基本的构建块。据了解，提供对\emph{things}的数据访问的两种主要方法是基于在未许可频谱中使用短距离通信技术的多跳网状网络，或者基于在相应的许可频带中操作的长距离传统蜂窝技术，主要是2G/GSM。最近，这些参考模型受到了新型无线连接的挑战，其特征在于未许可的sub-GHz频带中的低速率、长距离传输技术，用于实现具有星形拓扑的接入网络，其被称为\emph{Low-Power Wide Area Networks}（LPWAN）。在本文中，我们介绍了这种在物联网场景中提供连接的新方法，讨论了其在效率，有效性和架构设计方面优于现有范例的优势，特别是对于典型的智能城市应用。
Cyber Resilience is an important property of complex systems and is important consideration in developing specific IoT applications. This work aims at introducing a novel approach to assess IoT resilience adopting the risk perception in network based epidemic spreading approach. In particular IoT has been considered a network of devices where the probability of infection and interactions (communication), needs to be balanced in order to reduce the malware outbreack while maintaining the network functionalities at an acceptable level. The mathematical model and the simulation results reveal the…
