Tony Q.S. Quek

Tony Q.S. Quek
Future Communications R&D Programme (FCP)

Ph.D. (MIT), Fellow of IEEE

About

804
Publications
106,153
Reads
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18,858
Citations
Citations since 2016
578 Research Items
15660 Citations
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201620172018201920202021202205001,0001,5002,0002,5003,000
201620172018201920202021202205001,0001,5002,0002,5003,000
201620172018201920202021202205001,0001,5002,0002,5003,000
Introduction
Tony Q.S. Quek is a tenured Full Professor with the SUTD. He is also the ISTD Pillar Head and the Deputy Director of SUTD-ZJU IDEA. He received the B.E. and M.E. degrees in Electrical and Electronics Engineering from TIT, respectively. At MIT, he earned the Ph.D. in Electrical Engineering and Computer Science. Research topics include wireless communications and networks, security, internet-of-things, network intelligence, and big data processing. He is a fellow of IEEE.
Additional affiliations
July 2017 - present
Singapore University of Technology and Design
Position
  • Head of Department
October 2016 - present
Singapore University of Technology and Design
Position
  • Professor (Associate)
October 2016 - present
Singapore University of Technology and Design
Position
  • Professor (Associate)
Education
September 2002 - February 2008
Massachusetts Institute of Technology
Field of study
  • Electrical Engineering and Computer Science

Publications

Publications (804)
Article
Abstract—Cloud radio access network (C-RAN) aims to im- prove spectrum and energy efficiency of wireless networks by migrating conventional distributed base station functionalities into a centralized cloud baseband unit (BBU) pool. We propose and investigate a cross-layer resource allocation model for C- RAN to minimize the overall system power con...
Article
Full-text available
Wireless content caching in small cell networks (SCNs) has recently been considered as an efficient way to reduce the traffic and the energy consumption of the backhaul in emerging heterogeneous cellular networks (HetNets). In this paper, we consider a cluster-centric SCN with combined design of cooperative caching and transmission policy. Small ba...
Article
This paper investigates the problem of providing ultra-reliable and power-efficient virtual reality (VR) experiences for wireless mobile users. To ensure reliable ultra-high-definition (UHD) video frame delivery to mobile users and enhance their immersive visual experiences, a coordinated multipoint (CoMP) transmission technique and millimeter wave...
Preprint
As a promising architecture, Mobile Data Collector (MDC) enhanced Internet of Things (IoT) exhibits broad prospects in efficient data collection and data aggregation especially for sparse deployment scenarios. Combining the tools from queueing theory and stochastic geometry, we propose an analytical framework to study the network performance of an...
Preprint
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) net...
Article
Implementing federated learning (FL) algorithms in wireless networks has garnered a wide range of attention. However, few works have considered the impact of user mobility on the learning performance. To fill this research gap, we develop a theoretical model to characterize the hierarchical federated learning (HFL) algorithm in wireless networks wh...
Article
In this letter, we propose an integrated sensing and communication (ISAC) assisted energy-efficient mobile edge computing (MEC). To address the performance degradation due to interference between the radar sensing and MEC, we leverage advanced intelligent reflecting surface (IRS) to improve both the performance of the radar sensing and MEC. We adop...
Preprint
Personalized Federated Learning (PFL) is a new Federated Learning (FL) approach to address the heterogeneity issue of the datasets generated by distributed user equipments (UEs). However, most existing PFL implementations rely on synchronous training to ensure good convergence performances, which may lead to a serious straggler problem, where the t...
Conference Paper
Full-text available
In this paper, we propose an efficient near-field channel reconstruction and user localization scheme for extremely large-scale antenna array (ELAA) systems. Due to the non-negligible near-field effect in ELAA systems, a more realistic near-field multipath channel model, which incorporates the unequal path loss and the phase deviations across anten...
Article
As one of the key communication scenarios, ultrareliable low-latency communication (uRLLC) has become an important pillar to promote the vigorous development of intelligent mobile communications. In the practical scenarios, uRLLC services have strict and diverse Quality-of-Service (QoS) requirements. However, the existing networks are difficult to...
Article
Future Internet of Things (IoT) communication trends toward heterogeneous services and diverse quality-of-service requirements pose fundamental challenges for network management strategies. In particular, multiobjective optimization (MOO) is necessary in resolving the competition among different nodes sharing limited wireless network resources. A u...
Article
The conventional federated learning (FL) framework usually assumes synchronous reception and fusion of all the local models at the central aggregator and synchronous updating and training of the global model at all the agents as well. However, in a wireless network, due to limited radio resource, inevitable transmission failures and heterogeneous c...
Article
Federated learning (FL) has been considered as a promising approach for enabling distributed learning without sacrificing edge-devices’ (EDs’) data privacy. However, training machine learning (ML) model distributively is challenging to the EDs with limited energy supply. In this work, we consider that the central parameter-server (which is co-locat...
Article
With the rapid development of marine activities, there has been an increasing use of Internet-of-Things (IoT) devices for maritime applications. This leads to a growing demand for high-speed and ultra-reliable maritime communications. Current maritime communication networks (MCNs) mainly rely on satellites and on-shore base stations (BSs). The form...
Article
Due to its high mobility and flexible deployment, unmanned aerial vehicle (UAV) is drawing unprecedented interest in both military and civil applications to enable agile and ubiquitous connectivity. Mainly operating in an open environment, UAV communications benefit from dominant line-of-sight links; however, this on the other hand renders the comm...
Article
In this paper, we investigate the minimization of age of information (AoI), a metric that measures the information freshness, at the network edge with unreliable wireless communications. Particularly, we consider a set of users transmitting status updates, which are collected by the user randomly over time, to an edge server through unreliable orth...
Article
The forthcoming of automated driving has led to vehicular heterogeneity, where vehicles with different automation levels, including connected and automated vehicles (CAVs), connected vehicles (CVs) and human-driven vehicles (HVs), coexist in the road traffic. However, the design of current traffic control systems fail to account for the vehicular t...
Article
Statistical priority-based multiple access protocol (SPMA) has attracted more and more attention in virtue of its support for multi-priority traffic, and the guarantee of low-latency and high-reliability transmissions for high-priority. In this work, we propose an analytical framework to study the performance of SPMA from spatial perspective with t...
Article
The concept of hierarchical federated edge learning (H-FEEL) has been recently proposed as an enhancement of federated learning model. Such a system generally consists of three entities, i.e., the server, helpers, and clients, in which each helper collects the trained gradients from clients nearby, aggregates them, and sends the result to the serve...
Article
In this paper, we study the resource allocation in D2D underlaying cellular network with uncertain channel state information (CSI). For satisfying the minimum rate requirement for cellular user and the reliability requirement for D2D user, we attempt to maximize the cellular user’s throughput whilst ensuring a chance constraint for D2D. Then, a rob...
Article
Reconfigurable intelligent surface (RIS) is a promising material that can passively manipulate electromagnetic waves and improve the quality of mobile communication services at a low cost. It can be made large to extend the service region and acquire the ability for localization enhancement. However, the lack of a signal processing module at the RI...
Preprint
Full-text available
We study the average Age of Information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. Although the double queue parallel transmission is instrumental in reducing AoI, the out of order of data arrivals also imposes a significant challenge to the performance analysis. We consider two setting...
Article
Future networks are envisioned to create digital twin representations of the physical world, motivated by the integrated sensing and communication (ISAC). To meet the needs, millimetre wave (mmWave) and terahertz (THz) signals shine with outstanding performance in high-speed transmission and high-accuracy perception, but requiring narrow beamwidth...
Preprint
Full-text available
Data privacy and class imbalance are the norm rather than the exception in many machine learning tasks. Recent attempts have been launched to, on one side, address the problem of learning from pervasive private data, and on the other side, learn from long-tailed data. However, both assumptions might hold in practical applications, while an effectiv...
Preprint
This work studies the average age of information (AoI) of a monitoring system in which two sensors are sensing the same physical process and update status to a common monitor using their dedicated channels. Generally, using redundant devices to update the status of a process can improve the information timeliness at the monitor, but the disordered...
Article
In this letter, we study the age of information (AoI) of a ${K}$ -tier cellular Internet-of-Things (IoTs) network by taking into account both weighted path loss association policy and fractional power control strategy. By adopting tools from stochastic geometry, we first obtain the conditional per-tier AoI and conditional success probability, and...
Article
Unmanned aerial vehicle (UAV) is expected to bring transformative improvement to the integrated sensing and communication (ISAC) system. However, due to shared spectrum resources, it is challenging to achieve a critical trade-off between these two integrated functionalities. To address this issue, we propose in this letter a new integrated periodi...
Preprint
We exploit a behavior-shaping proactive mechanism, namely, recommendation, in cache-assisted non-orthogonal multiple access (NOMA) networks, aiming at minimizing the average system’s latency. Thereof, the considered latency consists of two parts, i.e., the backhaul link transmission delay and the content delivery latency. Towards this end, we first...
Conference Paper
In cellular-based federated learning (FL), the base station (BS) is only used to aggregate parameters, which incurs a waste of computing resources at the BS. In this paper, a novel semi-federated learning (SemiFL) framework is proposed to break this bottleneck, where local devices simultaneously send their gradient updates and training samples to t...
Article
Irregular repetition slotted ALOHA (IRSA) is a promising mechanism to support massive access in Internet of Things (IoT). As IoT devices are usually battery capacity-limited, the energy efficiency (EE) should be paid close attention to when operating the IRSA scheme. This letter improves the EE of devices by adjusting the transmit power and maximum...
Preprint
Full-text available
We demonstrate that merely analog transmissions and match filtering can realize the function of an edge server in federated learning (FL). Therefore, a network with massively distributed user equipments (UEs) can achieve large-scale FL without an edge server. We also develop a training algorithm that allows UEs to continuously perform local computi...
Article
Full-text available
In graph signal processing (GSP), complex datasets arise from several underlying graphs and in the presence of heterogeneity. Graph learning from heterogeneous graph signals often results in challenging high-dimensional multiple graph estimation problems, and prior information regarding which graph the data was observed is typically unknown. To add...
Preprint
Federated learning (FL) is a privacy-preserving distributed learning paradigm that enables clients to jointly train a global model. In real-world FL implementations, client data could have label noise, and different clients could have vastly different label noise levels. Although there exist methods in centralized learning for tackling label noise,...
Article
Full-duplex (FD) mode has great potential in improving the spectral efficiency. Mitigating the effect of self-interference becomes one key for performance enhancement of FD system. This work proposes a novel hybrid duplex scheme where the relay receives information for a fraction of time and simultaneously transmits and receives information for the...
Article
Federated learning (FL) has been considered as a promising paradigm for enabling distributed training/learning in many machine-learning services without revealing users’ local data. Driven by the growing interests in exploiting FL in wireless networks, this paper studies the Non-orthogonal Multiple Access (NOMA) assisted FL in which a group of end-...
Article
The papers in this special section focus on the use of distributed machine learning for wireless communications. With the emergence of new application scenarios (e.g., real-time and interactive services and Internet of Things) and the fast development of smart terminals, wireless data traffic has increased drastically, and the existing wireless net...
Article
Despite the great promises that the resistive random access memory (ReRAM) has shown as the next generation of non-volatile memory technology, its crossbar array structure leads to a severe sneak path interference to the signal read back from the memory cell. In this paper, we first propose a novel belief propagation (BP) based detector for the sne...
Preprint
In Internet of Things (IoT), the decision timeliness of time-sensitive applications is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for making decisions with exponential or periodic inter...
Preprint
Unmanned aerial vehicle (UAV) is expected to bring transformative improvement to the integrated sensing and communication (ISAC) system. However, due to shared spectrum resources, it is challenging to achieve a critical trade-off between these two integrated functionalities. To address this issue, we propose in this paper a new integrated \emph{per...
Preprint
Full-text available
On-demand and resource reservation pricing models have been widely used in cloud computing, catering to different user requirements. Nevertheless, in Multi-Access Edge Computing (MEC), as the edge has limited resources compared to the cloud, on-demand users may not get their jobs served on time, or at all, if too many resources were reserved by res...
Article
The advances in deep neural networks (DNN) have significantly enhanced real-time detection of anomalous data in IoT applications. However, the complexity-accuracy-delay dilemma persists: Complex DNN models offer higher accuracy, but typical IoT devices can barely afford the computation load, and the remedy of offloading the load to the cloud incurs...
Preprint
Full-text available
Federated learning (FL) is an emerging machine learning method that can be applied in mobile edge systems, in which a server and a host of clients collaboratively train a statistical model utilizing the data and computation resources of the clients without directly exposing their privacy-sensitive data. We show that running stochastic gradient desc...
Article
Full-text available
Mobile edge computing (MEC) is a prominent computing paradigm which expands the application fields of wireless communication. Due to the limitation of the capacities of user equipments and MEC servers, edge caching (EC) optimization is crucial to the effective utilization of the caching resources in MEC-enabled wireless networks. However, the dynam...
Article
In this paper, we explore the interplay between personalized bundle recommendation and cache decision on the performance of wireless edge caching networks. A revenue maximization perspective is provided. To this end, we first examine the quantitative impact of bundle recommendation on the content request probability of different users. We then spec...
Article
Full-text available
By focusing on unmanned aerial vehicle (UAV) communications in non-terrestrial networks (NTNs), this paper provides a guideline on the appropriate base station (BS) service provisioning scheme with considering the antenna tilt angle of BSs. Specifically, two service provisioning schemes are considered including the inclusive-service BS (IS-BS) sche...
Article
The data freshness at decision epochs of time-sensitive applications, e.g., auto-driving vehicles and autonomous underwater robots, is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for mak...
Article
Associated with multi-packet reception at the access point, irregular repetition slotted ALOHA (IRSA) holds a great potential in improving the access capacity of massive machine type communication systems. This work investigates the packet repetition of the users in an IRSA-based random access system where the access point can simultaneously retrie...
Article
Reconfigurable intelligent surface (RIS) assisted millimeter wave (mmWave) communications has been envisioned as a prominent technology for future wireless networks, since it is capable of simultaneously providing abundant spectrum resources and favorable propagation environments. The small wavelength at mmWave bands also enables the widespread use...
Article
To support massive connections of Internet of things (IoT) devices, backscatter communication has been proposed as a promising technique. However, its transmission reliability cannot be guaranteed due to the lack of error protection. To solve this problem, the optimization design of backscatter communications with retransmissions is studied in this...
Article
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...
Article
Full-text available
This paper considers the problem of learning the underlying graph topology of Gaussian Graphical Models (GGMs) from observations. Under high-dimensional settings, to achieve low sample complexity, many existing graph topology learning algorithms assume structural constraints such as sparsity to hold. Without prior knowledge of graph sparsity, the c...
Article
We consider a homogeneous Poisson bipolar network in which the bipoles represent source-destination pairs. The source nodes need to update their destinations about the new status perpetually, and the communications are taken place over a shared spectrum. The common goal of the source nodes is to minimize the network-wide age of information (AoI). W...
Article
Personalized Federated Learning (PFL) is a new Federated Learning (FL) approach to address the heterogeneity issue of the datasets generated by distributed user equipments (UEs). However, most existing PFL implementations rely on synchronous training to ensure good convergence performances, which may lead to a serious straggler problem, where the t...
Article
Wireless federated learning (FL), which allows edge devices to perform local deep/machine learning (DL/ML) training and further aggregates the locally trained models from them via radio channels, establishes a promising framework for enabling various DL/ML-based services in future B5G/6G networks. Despite respecting the data privacy, periodically p...
Article
In this letter, we propose a spatio-temporal analytical framework to comprehensively assess the performance of a statistical priority-based multiple access (SPMA) network. By combining tools from stochastic geometry with queueing theory, we characterize both the macroscopic interference distribution of the spatially interacting priority queues, and...
Article
Development of applications in real-time service promotes more stringent freshness and fidelity requirements for the status update and decision systems. However, the freshness and fidelity of status updates are mutually restrictive, as fresh information requires timely transmission whereas high quantization precision incurs long transmission time....
Article
As a promising architecture, Mobile Data Collector (MDC) enhanced Internet of Things (IoT) exhibits broad prospects in efficient data collection and data aggregation especially for sparse deployment scenarios. Combining the tools from queueing theory and stochastic geometry, we propose an analytical framework to study the network performance of an...
Article
Wireless federated learning (FL) is a collaborative machine learning (ML) framework in which wireless client-devices independently train their ML models and send the locally trained models to the FL server for aggregation. In this paper, we consider the coexistence of privacy-sensitive client-devices and privacy-insensitive yet computing-resource c...
Article
The boom in Internet of Things has spawned many real-time applications, which have stringent requirements for the timeliness of information delivery. As a result, age of information (AoI) has emerged as a metric to evaluate information freshness at the destination and aroused widespread attention from both academia and industry. In this paper, we d...