Tutorials

Session TUT-01

Age of Information as a New Data Freshness Metric in the IoT Era: From Theory to Implementation

Conference
9:00 AM — 12:30 PM CST
Local
Aug 8 Sat, 9:00 PM — 12:30 AM EDT

Age of Information as a New Data Freshness Metric in the IoT Era: From Theory to Implementation

Nikolaos Pappas (Linkoping University, Sweden, Email: [email protected]); He Chen (The Chinese University of Hong Kong, Hong Kong, China, Email: [email protected])

4
Internet of Things (IoT) represents one of the most significant paradigm shifts recently, which can revolutionize the information technology and several aspects of everyday life such as living, e-health and driving. Ericsson foresaw that by 2021, there will be around 28 billion IoT devices and a large share of them will be empowered by wireless communication technologies. As the most well-known application of the Internet of Things (IoT), remote monitoring is now pervasive. In IoT monitoring applications, information usually has a higher value when it is fresher. How to quantify the freshness and timeliness of information in IoT networks becomes of significant importance. Conventional performance metrics (e.g., throughput and delay) cannot adequately capture the information freshness. In this context, the age of information (AoI) concept was proposed as a new metric to measure the information freshness at the destination side. AoI is a function of both how often packets are transmitted and how much delay packets experience in the system. Recent research on AoI suggests that well-known design principles of wireless networks based on traditional objectives, such as achieving high throughput, need to be re-examined if information freshness is the new target. This tutorial aims to present recent efforts on the applications, analysis, optimization and prototyping of the AoI metric for quantifying and evaluating the information freshness in wireless IoT networks, with a comprehensive coverage including the definition and promising applications of AoI, queueing theory-based AoI analysis, AoI for energy harvesting wireless networks, age-oriented multiuser scheduling in single-/multi-antenna systems. Representative work in these areas will be went through during the tutorial. Finally, we will introduce two prototyping testbeds, built on software-defined radio platforms and off-the-shelf WiFi systems respectively, for validating and evaluating AoI-oriented analysis, designs and optimizations in real office environments.

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Session TUT-02

Privacy and Security in Federated Learning

Conference
9:00 AM — 12:30 PM CST
Local
Aug 8 Sat, 9:00 PM — 12:30 AM EDT

Privacy and Security in Federated Learning

Shi Jin (Southeast University, China, Email: [email protected]); Jun Li (NJUST, China, Email: [email protected]); Chuan Ma (NJUST, China, Email: [email protected])

2
Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) paradigm has emerged, namely federated learning (FL). Specifically, FL allows a decoupling of data provision at UEs and ML model aggregation at a central unit. By training model locally, FL is capable of avoiding direct data leakage from the UEs, thereby preserving privacy and security to some extend. However, even if raw data are not disclosed from UEs, individual's private information can still be extracted by some recently discovered attacks against the FL architecture. In this tutorial, we will provide three attractive sections to analyze the privacy and security issues in FL, and discuss several challenges on preserving privacy and security when designing FL systems. In addition, we provide extensive simulation results to showcase the discussed issues and possible solutions.

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Session TUT-03

Wireless Communications with Intelligent Reflecting Surface

Conference
9:00 AM — 12:30 PM CST
Local
Aug 8 Sat, 9:00 PM — 12:30 AM EDT

Wireless Communications with Intelligent Reflecting Surface

Caijun Zhong (Zhejiang University, China, Email: [email protected])

1
Intelligent reflecting surface (IRS) is an artificial planar structure made of sub-wavelength unit cells with adjustable electromagnetic responses, which has the potential to manipulate the propagation environments in an intelligent manner. Therefore, IRS has been envisioned as a promising technique to build spectral and energy efficient wireless communication systems, and has received considerable research interests from the community. Motivated by this, this tutorial aims to provide the audience a general picture of the recent developments in this exciting area. Specifically, in this interactive presentation we will address the following issues: We commence by introducing the basic of IRS, followed by its potential application scenarios in wireless communications. Then we elaborate on two major implementation architecture of IRS in wireless communications, namely, IRS enabled transceiver and IRS assisted communications. Later we discuss the potential integration of IRS with state-of-the-art transmission technologies, physical layer security, NOMA, SWIPT, two-way relaying, for example.

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Session TUT-04

Sparsity Modulation for mmWave, Terahertz and Optical Wireless Communication

Conference
9:00 AM — 12:30 PM CST
Local
Aug 8 Sat, 9:00 PM — 12:30 AM EDT

Sparsity Modulation for mmWave, Terahertz and Optical Wireless Communication

Shuaishuai Guo (Shandong University, China, Email: [email protected]); Haixia Zhang (Shandong University, China, Email: [email protected]); Shuping Dang (King Abdullah University of Science and Technology (KAUST), Saudi Arabia, Email: [email protected]); Mohamed-Slim Alouini (King Abdullah University of Science and Technology (KAUST), Saudi Arabia, Email: [email protected])

2
Exploring millimeter wave (mmWave)/Terahertz /optical wireless communications paves the way to beyond 5G and 6G offering hundreds of Gbs up to Tbs transmission data rate. For communications at high frequency band, reducing the consumed power at the radio frequency front end becomes extremely urgent. In this tutorial, we will introduce a class of modulation techniques leveraging signal sparsity for modulation, with which the number of RF chains required for mmWave and Terahertz communications using massive number of antennas can be significantly reduced. Meanwhile, sparsity modulation can also be adopted to pulse/sub-carrier-based optical wireless communications under given average or peak optical power constraints, e. g., visible light communications with the eye-safety requirements. The emerged and newly emerging spatial modulation, beamspace modulation, space-time-frequency index modulation, reflecting modulation, pulse position modulation, and robust pulse interval modulation all belong to the sparsity modulation family. In sparsity modulation, the non-zero positions of a signal can carry information besides the signal amplitude/phase/frequency/intensity of the non-zero signal. This has enabled a new dimension helping transmit extra bits with the non-zero signal positions. We will reveal different non-zero positions have different capabilities in carrying information, which will result in different capacities and error-protection properties by summarizing works on system capacity, error performance, bit-mapping design, constellation design, signal shaping optimization, and applications.

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Session TUT-05

Information Freshness for IoT Networks: From Concept to Application

Conference
2:00 PM — 5:30 PM CST
Local
Aug 9 Sun, 2:00 AM — 5:30 AM EDT

Information Freshness for IoT Networks: From Concept to Application

Tony Q.S. Quek (Singapore University of Technology and Design (SUTD), Singapore, Email: [email protected]); Howard H. Yang (Singapore University of Technology and Design (SUTD), Singapore, Email: [email protected]); Xijun Wang (Sun Yat-sen University, Guangzhou, China, Email: [email protected]); Chao Xu (Northwest A&F University, Yangling, China, Email: [email protected])

0
Being one of the key technologies of the next generation (5G) wireless networks, Internet of Things (IoT) has attracted significant attention from both academia and industry alike in recent years. In particular, IoT aims at enabling the ubiquitous connectivity among billions of things, ranging from tiny, resource-constrained sensors to more powerful smartphones and networked vehicles. With the help of IoT, devices can sense and even interact with the physical surrounding environment, thereby providing us with many valuable and remarkable context-aware real time applications at an efficient cost, such as automatic control of electric appliance, intelligent transportation network, and event monitoring and predication for health safety. For these applications, the staleness of obtained information at the destination nodes (e.g., monitors and actuators) inevitably deteriorates the accuracy and reliability of derived decisions, and leads to compromises in safety and security. As such, it is essential to perform freshness update collection, data delivery, and information extraction. Before an adequate response can be given to preserves freshness of information at the destinations, the primary requirement will be to properly measure the freshness of information and attain a full understanding of the effects of key system parameters in IoT networks, ranging from the status update generating, processing, to delivery, on the concerned information freshness. Recently, the Age of Information (AoI) has been proposed as a particular metric to quantify the information freshness in real time applications. This quantity measures the time elapsed since the latest received packet was generated from the sensor. In contrast to many conventional metrics for performance evaluation, e.g., throughput and delay, the AoI metric is defined from the receiver¡¯s perspective. To this end, it calls for additional efforts to study the distinguishing feature of AoI, construct appropriate models to analyze it and provide design guidelines, and more importantly, treat it as a novel metric for network deployment and optimization. In this tutorial, we will first provide the background about the definition and advantages of AoI and its variations for more general applications in IoT networks. Then, we will introduce some fundamental queueing models which are appropriate for analyzing the information freshness of some basic IoT networks. Finally, we will introduce different applications of the information freshness related metric, which facilitates the design and optimization of various IoT networks augmented by emerging techniques, e.g., edge caching and computing, unmanned aerial vehicles (UAVs), ect. We hope this tutorial will endow new researchers with a good understanding of the AoI when they enter this exciting area.

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Session TUT-06

Cell-Free Massive MIMO Systems: A New Next-Generation Paradigm

Conference
2:00 PM — 5:30 PM CST
Local
Aug 9 Sun, 2:00 AM — 5:30 AM EDT

Cell-Free Massive MIMO Systems: A New Next-Generation Paradigm

Jiayi Zhang (Beijing Jiaotong University, China, Email: [email protected])

3
Cell-free (CF) massive multiple-input multiple-output (MIMO) systems have a large number of individually controllable antennas distributed over a wide area for simultaneously serving a small number of user equipment (UE). This solution has been considered as a promising next-generation technology due to its ability to offer a similar quality of service to all UEs, despite its low-complexity signal processing. In this tutorial, we provide a comprehensive survey of CF massive MIMO systems. To be more specific, the benefit of so-called of channel hardening and favorable propagation conditions are exploited. Furthermore, we quantify the advantages of CF massive MIMO systems in terms of their energy- and spectral-efficiency. Additionally, the signal processing techniques invoked for reducing the backhaul burden are analyzed. Finally, the open research challenges in both its deployment and network management are highlighted.

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Session TUT-07

Reconfigurable Intelligent Surface for 6G: Communication, Sensing, and Localization

Conference
2:00 PM — 5:30 PM CST
Local
Aug 9 Sun, 2:00 AM — 5:30 AM EDT

Reconfigurable Intelligent Surface for 6G: Communication, Sensing, and Localization

Boya Di (Imperial College London, London, UK, Email: [email protected]); Hongliang Zhang (Princeton University, USA, Email: [email protected]); Lingyang Song (Peking University, Beijing, China, Email: [email protected]); Zhu Han (University of Houston, Texas, USA, Email: [email protected])

2
To spearhead the emergence of future intelligent communication and sensing platform, many advanced techniques have been investigated such as small cell and massive MIMO to support ubiquitous high-speed data services. However, their performances greatly depend on the dynamic and unpredictable wireless propagation. Against this background, reconfigurable intelligent surface (RIS) stands out as a novel approach to improve the quality of communication links and extend coverage. It is capable to actively shape the uncontrollable wireless environments into a desirable form via flexible phase shift reconfiguration without extra hardware or power costs. To better exploit the potential of such a technique, it is essential to develop distributed configuration, to design new protocols, to explore and implement suitable application scenarios, as well as to perform intelligent control and orchestration. This proposal will emphasize on RIS aided cellular communication and its applicability to a variety of IoT use cases. We will first give a comprehensive introduction of the RIS techniques by revealing its unique features compared to traditional antenna arrays. Second, RIS-aided communications will be discussed targeting at network capacity improvement and coverage extension from different aspects such as hybrid beamforming design and structure optimization. Third, two typical RIS-aided IoT applications will be developed, i.e., smart sensing and enhanced localization. Challenges on protocol design, signal processing, intelligent configuration, and implementation issues will be addressed.

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