Tony Q.S. Quek

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

Ph.D. (MIT), Fellow of IEEE

About

774
Publications
101,343
Reads
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16,224
Citations
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 (774)
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
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...
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...
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...
Preprint
In this paper, 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 thi...
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...
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,...
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
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
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 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...
Article
This letter presents deep neural network (DNN) approaches for non-orthogonal random access (NORA) systems where several devices are allowed to occupy the identical preamble. We desire to improve the reliability of the packet transmission of NORA devices with a careful management of multi-user interference. A novel transmit power control (TPC) mecha...
Article
We study a distributed machine learning problem carried out by an edge server and multiple agents in a wireless network. The objective is to minimize a global function that is a sum of the agents local loss functions. And the optimization is conducted by analog over-the-air model training. Specically, each agent modulates its local gradient onto a...
Article
Towards the sixth generation (6G) wireless communications, multiple access is a potential technology to achieve thousand times of traffic capacity enhancement comparing with 5G. This paper investigates the feasible signal-to-interference-plus-noise-ratio (SINR) region for the multi-cell downlink and uplink non-orthogonal multiple access (NOMA) syst...
Conference Paper
Full-text available
In this paper, we investigate the problem of edge caching (EC) optimization in a multi-user privacy-preserving mobile edge computing (MEC) system. The time-varying content popularity is considered and the primary objective is to maximize the EC hit rate on each caching entity in the distributed network. To this end, we introduce the concept of loca...
Preprint
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
Packet-level forward erasure correction (FEC) is effective for achieving low-latency transmissions in non-terrestrial networks (NTNs), which often contain lossy links with long propagation delay. This letter considers the problem of dynamically sending FEC coded packets based on delayed feedback to achieve fast in-order data delivery without retran...
Article
In this paper, we consider a practical scenario for secure wireless-powered communication in the presence of imperfect channel state information (CSI) with simultaneous energy harvesting, in which it is required to keep information secret from an untrusted energy receiver allowed only to harvest energy from the transmitted signals. We aim to find t...
Preprint
Full-text available
Internet of unmanned aerial vehicle (I-UAV) networks promise to accomplish sensing and transmission tasks quickly, robustly, and cost-efficiently via effective cooperation among UAVs. To achieve the promising benefits, the crucial I-UAV networking issue should be tackled. This article argues that I-UAV networking can be classified into three catego...
Article
Private 5G edge networks support secure and private service, spectrum flexibility, and edge intelligence. In this paper, we aim to design a dynamic scheduling policy to explore the spectrum flexibility for heterogeneous federated learning (FL) in private 5G edge networks. Particularly, FL is implemented with multiple communication rounds, in each o...
Preprint
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...
Article
This letter proposes an analytical framework to assess the network performance of a wireless network adopting statistical priority-based multiple access (SPMA) scheme with nodes equipping with directional antennas. By taking into account the spatial randomness of nodes and the impact of directional antenna, we first derive the analytical expression...
Article
In this paper, we investigate a private and cache-enabled unmanned aerial vehicle (UAV) network for content provision. Aiming at delivering fresh, fair, and energy-efficient content files to terrestrial users, we formulate a joint UAV caching, UAV trajectory, and UAV transmit power optimization problem. This problem is confirmed to be a sequential...
Preprint
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
With automated driving forthcoming, lane-changing for Connected and Automated Vehicles (CAVs) has received wide attention. The main challenge is that lane-changing requires not only local CAV control but also interactions with the surrounding traffic. Nevertheless, the Line-of-Sight (LoS) sensing range of the CAVs imposes severe limitations on lane...
Preprint
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. Considering the time-frequency resource efficiency, K = 2 (multi-packet reception capability) may be the most suitable scheme for scenarios that...
Article
Age of Information (AoI) is a critical metric for Internet of Things (IoT) real-time applications, where real-time services need fresh data. The AoI is directly affected by the arrival rate of packet in the IoT, yet the optimal arrival rate based on the hard AoI and peak AoI constraints has not been investigated. Knowing the optimal arrival rate ca...
Article
Full-text available
We consider a resource allocation and offloading decision-making problem in a mobile edge computing (MEC) network. Since the locations of user equipments (UEs) vary over time in practice, we consider a dynamic network, where the UEs could leave or join the network coverage at any location. Since the joint offloading decision that minimizes the netw...
Article
We investigate the age-of-information (AoI) in the context of random access networks, in which transmitters need to send a sequence of information packets to the intended receivers over a shared spectrum. Due to interference, the dynamics at the link pairs will interact with each other over both space and time, and the effects of these spatiotempor...
Article
Timeliness is an emerging requirement for many Internet of Things (IoT) applications. In IoT networks with a large-number of nodes, severe interference may incur that leads to age of information (AoI) degradation. It is therefore important to study how to optimize the AoI performance. This paper focus on the AoI minimization in random access Poisso...
Article
Full-text available
This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, multiple base stations, and a malicious eavesdropper. Specifically, the users adopt the partial offloading strategy by partitioning the computation task into several parts. One is executed locally and the others are securely offloaded to multiple...
Preprint
This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, multiple base stations, and a malicious eavesdropper. Specifically, the users adopt the partial offloading strategy by partitioning the computation task into several parts. One is executed locally and the others are securely offloaded to multiple...
Preprint
Full-text available
We investigate the age-of-information (AoI) in the context of random access networks, in which transmitters need to send a sequence of information packets to the intended receivers over a shared spectrum. Due to interference, the dynamics at the link pairs will interact with each other over both space and time, and the effects of these spatiotempor...
Article
Future mobile systems have shown a growing trend towards wider frequency bands, larger antenna arrays, and more user equipment, simultaneously expanding the channel in the frequency, space, and user domains. However, the huge size of the multi-domain channel brings great challenges to the acquisition of channel state information (CSI), especially i...
Article
TeraHertz (THz) wireless communication constitutes a promising technique of satisfying the ever-increasing appetite for high-rate services. However, the ultra-wide bandwidth of THz communications requires high-speed, high-resolution analog-todigital converters, which are hard to implement due to their high complexity and power consumption. In this...
Article
Federated learning provides a promising paradigm to enable network edge intelligence in the future sixth generation (6G) systems. However, due to the high dynamics of wireless circumstances and user behavior, the collected training data is non-independent and identically distributed (non-IID), which causes severe performance degradation of federate...
Preprint
Full-text available
This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, multiple base stations, and a malicious eavesdropper. Specifically, the users adopt the partial offloading strategy by partitioning the computation task into two parts. One is executed locally and the other is securely offloaded to multiple MEC se...
Article
Full-text available
Mobile Edge Computing (MEC) is a promising architecture to reduce energy consumption of mobile devices and provide satisfactory quality-of-service to time-sensitive services. How to jointly optimize task offloading and resource allocation to minimize the energy consumption subject to the latency requirement remains an open problem, which motivates...