Weihua Zhuang

University of Waterloo | UWaterloo · Department of Electrical & Computer Engineering

In this article, we propose a digital agent (DA)-assisted network management framework for future sixth generation (6G) networks considering users' quality of experience (QoE). Particularly, a novel QoE metric is defined by incorporating the impact of user behavior dynamics and environment complexity on quality of service (QoS). A two-level DA arch...

We consider a mobile edge computing (MEC) assisted Industrial Internet of Things (IIoT) network, where multiple assembly processing lines in a smart factory are equipped with sensing devices. They sense raw products, generate and offload computing tasks, and finally process the raw products based on the computing results. In this scenario, differen...

In this paper, we consider an unmanned aerial vehicle (UAV)-assisted post-disaster rescue scenario, where UAV-mounted aerial base stations (ABSs) compute tasks related to post-disaster rescue operations while also providing communication services to ground users (GUs). With the limited computation capacity of ABSs, we aim to minimize the task compu...

Resource slicing in low Earth orbit satellite networks (LSN) is essential to support diversified services. In this paper, we investigate a resource slicing problem in LSN to reserve resources in satellites to achieve efficient resource provisioning. To address the challenges of non-stationary service demands, inaccurate prediction, and satellite mo...

Cooperative perception (CP) is a key approach to ensuring reliable situation awareness of connected and autonomous vehicles (CAVs). In this article, we discuss the key challenges in terms of scalability, dynamics, and performance uncertainty for supporting CP in a practical network environment. Then, we present a data/model co-driven framework for...

Cell-free massive multiple-input multiple-output (mMIMO) architecture is a promising solution for Industrial Internet of Things (IIoT) because it not only provides massive connectivity but also eliminates the traditional cell edges. Considering the heterogeneous traffic and requirements in the industry, in this paper, we propose a device priority-a...

In this article, we present a novel user-centric service provision for immersive communications (IC) in 6G to deal with the uncertainty of individual user behaviors while satisfying unique requirements on the quality of multi-sensory experience. To this end, we propose a data-oriented approach for network resource management, featuring personalized...

Multi-modal services, integrating various modalities such as audio, visual, and haptic, have emerged as leading multimedia applications in the 5G era and beyond. To fulfill the demands for low latency, high reliability, and large capacity, cross-modal transmission schemes have been proposed. Typically, these schemes emphasize on either audio-visual...

To accommodate high network dynamics in real-time cooperative perception (CP), reinforcement learning (RL) based adaptive CP schemes have been proposed, to allow adaptive switchings between CP and stand-alone perception modes among connected and autonomous vehicles. The traditional offline-training online-execution RL framework suffers from perform...

Low Earth orbit (LEO) satellite networks have shown strategic superiority in maritime communications, assisting in establishing signal transmissions from shore to ship through space-based links. Traditional performance modeling based on multiple circular orbits is challenging to characterize large-scale LEO satellite constellations, thus requiring...

Multi-modal services, integrating audio, video, and haptic streams, have shown their great potential to improve user immersive experience. However, due to their distinct requirements, simultaneous transmission of streams from different modalities is a significant challenge. To address the challenge, we propose a content-aware cross-modal stream tra...

We hope you will make a special effort to join the 100th edition of the IEEE Vehicular Technology Conference (VTC), to be held during 7–10 October 2024 at the Ronald Reagan Building and International Trade Center in Washington, DC, USA. We look forward to celebrating not only the 100th edition of the conference but also the 75th anniversary of IEEE...

Cooperative perception (CP) is a key technology to facilitate consistent and accurate situational awareness for connected and autonomous vehicles (CAVs). To tackle the network resource inefficiency issue in traditional broadcast-based CP, unicast-based CP has been proposed to associate CAV pairs for cooperative perception via vehicle-to-vehicle tra...

The emerging data-driven methods based on artificial intelligence (AI) have paved the way for intelligent, flexible, and adaptive network management in vehicular applications. To enhance network management toward network automation, this article presents a digital twin (DT) assisted two-tier learning framework, which facilitates the automated life-...

This paper explores the integration of active machine learning (ML) for 6G networks, an area that remains under-explored yet holds potential. Unlike passive ML systems, active ML can be made to interact with the network environment. It actively selects informative and representative data points for training, thereby reducing the volume of data need...

This is an exciting month in IEEE Vehicular Technology Society (VTS). We look forward to seeing many of you at the 99th IEEE Vehicular Technology Conference to be held on 24–27 June 2024 at the Marina Bay Sands, a landmark destination in Singapore. Many thanks to J. R. Cruz as Vice President of Conferences, Sumei Sun as General Chair, Chen Hui Ong...

Edge-device collaboration has the potential to facilitate compute-intensive device pose tracking for resource-constrained mobile augmented reality (MAR) devices. In this paper, we devise a 3D map management scheme for edge-assisted MAR, wherein an edge server constructs and updates a 3D map of the physical environment by using the camera frames upl...

Recently, mobile crowdsensing (MCS) has emerged as a promising solution for traffic state estimation (TSE), which provides real-time and accurate traffic information for supporting diversified intelligent transportation systems (ITS) applications. However, the prohibitive overhead of collecting massive data in vehicular networks limits the availabl...

The low Earth orbit (LEO) satellite-assisted communications are envisioned as a prospective solution in next-generation networks to provide reliable, flexible, cost-effective, and globally seamless services. In this paper, we investigate satellite-terrestrial vehicular network (STVN) supporting connected autonomous vehicle (CAV) applications anytim...

As you read in our last issue, we are excited to see what 2024 holds for the field of vehicular technology. In this article, we showcase the IEEE Vehicular Technology Society (VTS) technical committees in the fields of land transportation, motor vehicles, and mobile communications and networks. Follow along at https://vtsociety.org/about/standing-...

In this chapter, we provide a comprehensive study on wireless multi-hop networks with cut-through capability. The goal of this chapter is to improve the end-to-end throughput. In particular, we first establish an effective analytical model and find that the achievable end-to-end throughput is mainly determined by the cut-through mode, the spatial r...

In this chapter, we first summarize the main content, including MAC protocol designs and schemes that can improve FD network performance, presented in this monograph, and then highlight future research directions of FD network design and analysis.

In this chapter, we design a random-access directional FD MAC (DFDMAC) protocol compatible with IEEE 802.11ay, supporting typical directional FD transmission modes, including bidirectional FD transmission, simultaneous uplink and downlink transmissions, and FD relay transmission. To reduce the impact of the residual self-interference, inter-beam in...

This is Part II of the two-part Special Issue (SI) on 5G/6G Precise Positioning on Cooperative Intelligent Transportation Systems (C-ITS) and Connected Automated Vehicles (CAV). The SI aims at bringing together contribution from both academia and industry to highlight the recent progress in various aspects of positioning systems. We have included 3...

Tile-based streaming has been proposed to address the challenge of high transmission rate demand in 360 $^{\circ}$ virtual reality (VR) video streaming. However, it suffers from network and viewing behavior dynamics (i.e., head movements), while encoded video tiles have various properties in terms of transmission priority, deadline, and reliabilit...

In this paper, we investigate infrastructure-assisted environment sensing in satellite-terrestrial vehicular networks (STVN) for connected autonomous vehicles (CAVs), where satellites and roadside units (RSUs) cooperate to provide CAVs with fresh sensing data. To support satellite-and RSU-assisted environment sensing for CAVs, we formulate a long-t...

Vehicular edge computing (VEC) helps improve the task computational performance of vehicles on roads but has difficulty in defending against eavesdropping and selfish attacks simultaneously. In this paper, we design a reputation-based smart contract with blockchain and propose a multi-agent reinforcement learning (RL) based secure offloading scheme...

Generative artificial intelligence (GAI) and digital twin (DT) are advanced data processing and virtualization technologies to revolutionize communication networks. Thanks to the powerful data processing capabilities of GAI, integrating it into DT is a potential approach to construct an intelligent holistic virtualized network for better network ma...

To bring 5G systems and networks to life in large-scale commercial applications, academia community has started the research beyond 5G (B5G), in which Network Slicing (NS) is proposed as a new paradigm for building service-tailored B5G networks. In each network slice, to precisely control the service quality and cost, deploying the service-required...

While network slicing has become a prevalent approach to service differentiation, radio access network (RAN) slicing remains challenging due to the need of substantial adaptivity and flexibility to cope with the highly dynamic network environment in RANs. In this paper, we develop a slicing-based resource management framework for a two-tier RAN to...

The advancement of connected intelligent transportation systems (C-ITS) and connected automated vehicles (CAV) has brought about a growing need for precise positioning solutions. Positioning technologies play a crucial role in many use cases such as emergency call systems, disaster rescue operations, automated robotics, and more. To ensure the avai...

As 2023 comes to a close, we reflect on the highlights of this calendar year in the IEEE Vehicular Technology Society (VTS). We welcome your feedback on how we can better serve our community, and we look forward to what 2024 holds in the field of vehicular technology, including mobile communications and networks, motor vehicles, and land transporta...

The advances in artificial intelligence (AI) and edge computing enable edge intelligence to support pervasive intelligent Internet of Things (IoT) applications in the future wireless networks. We focus on deep neural network (DNN) based classification tasks, and investigate how to improve the confidence level and delay performance of DNN inference...

Precise positioning is a key factor and enabler technology for many use cases on intelligent transportation systems (ITS) and connected and automated vehicles (CAVs). 3GPP with Release 16 introduces native support for positioning with the new-radio (NR) carrier that will be applicable for millimeter Wave (mmW) frequencies. The mmW technology can al...

In this paper, we present a novel content caching and delivery approach for mobile virtual reality (VR) video streaming. The proposed approach aims to maximize VR video streaming performance, i.e., minimizing video frame missing rate, by proactively caching popular VR video chunks and adaptively scheduling computing resources at an edge server base...

This time of year is special for the IEEE Vehicular Technology Society (VTS). We will recognize this year’s VTS Award recipients at the 98th Annual IEEE Vehicular Technology Conference held in Hong Kong (VTC2023-Fall). We will also bring together engineers, researchers, and other professionals at the 2023 IEEE Vehicle Power and Propulsion Conferenc...

For connected automated vehicles (CAVs), safety and security are two interrelated critical issues since many in-vehicle components are both safety critical and security critical. To achieve both safety and security in the presence of functional failures or cyberattacks, this article proposes a dynamic heterogeneous redundancy (DHR) scheme for CAVs....

This is an exciting month in the IEEE Vehicular Technology Society (VTS). We look forward to seeing many of you at the 97th Annual IEEE Vehicular Technology Conference (VTC2023-Spring) held on 20–23 June 2023 in Florence, Italy. We owe many thanks to J.R. Cruz as VTS vice president for conferences; Alberto Reatti and Lorenzo Ciani as general cochai...

Full-duplex (FD) technique can remarkably boost the network capacity in the millimeter wave (mmWave) bands by enabling simultaneous transmission and reception. However, due to directional transmission and large bandwidth, the throughput and fairness performance of a mmWave FD network are affected by deafness and directional hidden-node (HN) problem...

In this paper, we design a 3D map management scheme for edge-assisted mobile augmented reality (MAR) to support the pose estimation of individual MAR device, which uploads camera frames to an edge server. Our objective is to minimize the pose estimation uncertainty of the MAR device by periodically selecting a proper set of camera frames for upload...

In this book, we have discussed maritime communications based on RL to enhance reliability and security performance, including IRS-aided communications, privacy-aware IoT communications, intelligent resource management, and location privacy protection (Jo and Shim, IEEE Access 7:53,172–53,181, 2019; Zeng et al., IEEE Trans. Comm. 69:8100–8115, 2021...

In maritime networks (MNs), ships and other maritime mobile devices release their geographical and semantic information of the visited places (e.g., harbors, passenger terminals, and oil terminals) to request location-based services (LBS). This sensitive information enables the inference attacker to exploit the ship users’ identity or business info...

Mobile edge computing helps maritime IoT devices with energy harvesting to provide satisfactory experiences for computation-intensive applications in maritime communication systems, such as real-time cargo status notification, emergency rescue in maritime affairs, and accurate early warning. In this chapter, we present an RL-based privacy-aware off...

Physical layer security (PLS) has attracted increasing attention as an alternative to cryptography-based techniques for maritime wireless communications (Liu et al., IEEE J. Sel. Areas Commun. 39(10), 2992–3005 (2021)). For instance, secure communication services in (Liu et al., IEEE J. Sel. Areas Commun. 39(10), 2992–3005 (2021); Shi et al., China...

With the booming smart maritime services from IoT devices, located in the underwater vehicles, ships, sensors and underwater industrial the 5G networks that have supported industrial automation in Palattella et al. (IEEE J Sel Areas Commun 34:510–527, 2016), Jo and Shim (IEEE Access 7:53,172–53,181, 2019), and Liu et al. (IEEE Signal Procss Mag 35:...

Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into a device-side model and a server-side model at a cut layer. The existing SL approach conducts the training process sequentially across devices, which incurs significant t...

I am greatly honored and committed to serve as the president of the IEEE Vehicular Technology Society (VTS). The VTS serves as the association of reference for mobility professionals’ needs in the areas of lifelong learning, standards creation, dissemination of new technologies, and networking. I will work closely with VTS volunteers to enhance ser...

The sixth generation (6G) networks are expected to enable immersive communications and bridge the physical and the virtual worlds. Integrating extended reality, holography, and haptics, immersive communications will revolutionize how people work, entertain, and communicate by enabling lifelike interactions. However, the unprecedented demand for dat...

In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed architecture has two key elements, i.e., holistic network virtualization and pervasive artificial intelligence (AI). The holistic network virtualization consists of ne...

This paper focuses on trigger-based (TB) random access (RA) strategies for a multiple-packet reception channel with channel capability $M$ ( $M$ -MPR channel), where up to $M$ packets can be received simultaneously, while more than $M$ concurrent packet transmissions result in collisions and are considered lost. We model the contention for t...

Iteration based collaborative learning (CL) paradigms, such as federated learning (FL) and split learning (SL), faces challenges in training neural models over the rapidly growing yet resource-constrained edge devices. Such devices have difficulty in accommodating a full-size large model for FL or affording an excessive waiting time for the mandato...

In this study, we consider linear-quadratic (LQ) mean-field social control problems for a class of stochastic systems with ordinary control input and delay control input. We define a stabilization problem via a memoryless static output feedback (SOF) strategy and then solve the problem of minimizing the upper bound of the cost function using guaran...

Dual connectivity is a feature that allows dual-wireless interface devices to concurrently utilize radio resources from two different wireless network technologies. The aggregate data rate achievable using dual connectivity is expected to enhance application performance and user experience if the radio resources of contributing wireless networks ar...

The ubiquitous data collection has raised potential risks of leaking physical and private attribute information associated with individuals in a collected dataset. A data collector who wants to collect data for provisioning its machine learning (ML)-based services requires establishing a privacy-preserving data collection protocol for data owners....

Mounting reconfigurable intelligent surface (RIS) on unmanned aerial vehicle (UAV), called UAV-RIS, combines the benefits of these two techniques, which can further improve the communication performance. However, high-quality air-ground channel links are more vulnerable to both the adversarial eavesdropping and the malicious jamming. Therefore, thi...

To maintain high perception performance among connected and autonomous vehicles (CAVs), in this paper, we propose an accuracy-aware and resource-efficient raw-level cooperative sensing and computing scheme among CAVs and road-side infrastructure. The scheme enables fined-grained partial raw sensing data selection, transmission, fusion, and processi...

The metaverse is envisioned to create immersive and virtual worlds for people to experience interoperable 3D applications. However, the real-time, interactive, and multimedia characteristics of the metaverse applications require strict quality-of-service (QoS) on the underlying networking architecture, including high throughput, ultra-low delay, an...

In this paper, we study a network slicing problem for edge-cloud orchestrated vehicular networks, in which the edge and cloud servers are orchestrated to process computation tasks for reducing network slicing cost while satisfying the quality of service requirements. We propose a two-stage network slicing framework, which consists of 1) network pla...

Future networks incorporate artificial intelligence to enable smart resource management and adaptive service provisioning. With a heterogeneous architecture and a large number of users in future networks, transparent and decentralized data sharing is required to promote data circulation and break data silos, for which blockchain is a potential solu...

This paper presents a novel approach for computing resource management of edge servers in vehicular networks based on digital twins and artificial intelligence (AI). Specifically, we construct two-tier digital twins tailored for vehicular networks to capture networking-related features of vehicles and edge servers. By exploiting such features, we p...

Network function virtualization is a key enabling technology in future wireless networks for flexible and efficient sharing of network resources. Due to the increasing heterogeneity of network resource providers, a blockchain-based distributed architecture is a promising solution to enable reliable and transparent virtualized network function (VNF)...

In this paper, we design a resource management scheme to support stateful applications, which will be prevalent in 6G networks. Different from stateless applications, stateful applications require context data while executing computing tasks from user terminals (UTs). Using a multi-tier computing paradigm with servers deployed at the core network,...

Secure cross-domain authorization and authentication (AA) enable application service providers (ASPs) to allow users for resource access from different trusted domains. In this article, we propose a unified blockchain-assisted secure cross-domain AA framework for smart city, which can guarantee transparent cross-domain resource access while preserv...

In this paper, we design a resource management scheme to support stateful applications, which will be prevalent in sixth generation (6G) networks. Different from stateless applications, stateful applications require context data while executing computing tasks from user terminals (UTs). Using a multi-tier computing paradigm with servers deployed at...

Federated learning (FL) over resource-constrained wireless networks has recently attracted much attention. However, most existing studies consider one FL task in single-cell wireless networks and ignore the impact of downlink/uplink inter-cell interference on the learning performance. In this paper, we investigate FL over a multi-cell wireless netw...

Federated learning (FL) over resource-constrained wireless networks has recently attracted much attention. However, most existing studies consider one FL task in single-cell wireless networks and ignore the impact of downlink/uplink inter-cell interference on the learning performance. In this paper, we investigate FL over a multi-cell wireless netw...

Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into a device-side model and a server-side model at a cut layer. The existing SL approach conducts the training process sequentially across devices, which incurs significant t...

Traditional one-bit compressed stochastic gradient descent can not be directly employed in multi-hop all-reduce, a widely adopted distributed training paradigm in network-intensive high-performance computing systems such as public clouds. According to our theoretical findings, due to the cascading compression, the training process has considerable...

Not only in control problems, but also in dynamic games, several sources of performance degradation, such as model variation, deterministic and stochastic uncertainties and state delays, need to be considered. In this paper, we present an [Formula: see text] constrained Pareto suboptimal strategy for stochastic linear parameter-varying (LPV) time-d...

With the global rollout of fifth generation (5G) networks, it is necessary to look beyond 5G and envision 6G networks. 6G networks are expected to have space-air-ground integrated networks, advanced network virtualization, and ubiquitous intelligence. This article presents an artificial intelligence (AI)-native network slicing architecture for 6G n...

Federated meta-learning (FML) has emerged as a promising paradigm to cope with the data limitation and heterogeneity challenges in today’s edge learning arena. However, its performance is often limited by slow convergence and corresponding low communication efficiency. In addition, since the available radio spectrum and IoT devices’ energy capacity...

In China, some e-commerce platform (EP) companies such as Alibaba and JD are now allowed to partner with network operators (NOs) to act as virtual network operators (VNOs) to provide mobile data services for mobile users (MUs). However, it is a question worth researching on how to generate more profits for all network players, with EP companies bei...

The existing packet forwarding technology cannot meet the increasing requirements of Internet development due to its rigid framework. Application of artificial intelligence (AI) for efficient packet forwarding is gaining more and more interest as a new direction. Recently, the explosive development of programmable data plane (PDP) has provided a po...

Sixth-generation (6G) cellular systems will have an inherent vulnerability to physical (PHY)-layer attacks and privacy leakage, due to the large-scale heterogeneous networks with booming time-sensitive applications. Important wireless techniques including non-orthogonal multiple access, mobile edge computing, millimeter-wave, massive multiple-input...

Next-generation networks are endowed with enhanced capabilities thanks to software-defined networking and network function virtualization (NFV). There is a radical shift from device-centric to experience-driven environments of which data is the primary driver behind its running engines. In this paper, we consider joint topology design, traffic rout...

A static output feedback (SOF) strategy for robust incentive Stackelberg games with a large population for mean-field stochastic systems is investigated. First, the saddle point equilibrium condition of external disturbance and control strategy is derived based on stochastic algebraic matrix equations (SAMEs). Then, a centralized SOF incentive Stac...

In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed architecture has two key elements, i.e., holistic network virtualization and pervasive artificial intelligence (AI). The holistic network virtualization consists of ne...

In this paper, we propose a multi-layer Ka/Q-band satellite-terrestrial integrated network for the Internet of remote things (IoRT) to achieve a high transmission rate with communication robustness in dynamic network environments. Under this architecture, we investigate how to jointly manage the offloading path selection and resource allocation to...

In this chapter, a delay-aware VNF scheduling problem is studied in the presence of small-timescale traffic dynamics, to achieve network utility maximization with QoS guarantee for each deadline-constrained service. A state-of-the-art time quantum in the 100 μs to ms granularity is used for CPU resource scheduling. Based on the Lyapunov optimizatio...

In this chapter, VNF scalability via joint resource scaling and migration is studied in a local network segment, to meet a probabilistic delay requirement in the presence of non-stationary traffic with changing traffic statistics. A change point detection scheme determines boundaries between stationary traffic segments in an online manner as new tr...

In this chapter, we draw conclusions on dynamic resource management in service-oriented core networks as discussed in this book, and identify some future research directions.

Edge intelligence leverages computing resources on the network edge to provide artificial intelligence (AI) services close to network users. As it enables fast inference and distributed learning, edge intelligence is envisioned to be an important component of 6G networks. In this article, we investigate AI service provisioning for supporting edge i...

Millimeter-wave (mmWave) frequency bands, which offer abundant underutilized spectral resources, have been explored and exploited in the past several years to meet the requirements of emerging wireless services highlighted by high data rates, ultrareliability, and ultralow delivery latency. Yet, the unique characteristics of mmWave, e.g., continuou...