Tony Q.S. Quek

• Ph.D. (MIT), Fellow of IEEE
• Director at Future Communications R&D Programme (FCP)

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...

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...

In the era of 6G networks, the demand for robust and trustworthy communication systems has become more critical than ever, particularly in MIMO-enabled flying ad hoc networks (FANETs), also known as low-altitude networks. These networks combine the flexibility of aerial platforms with the high-capacity advantages of MIMO technology to support criti...

Given the crucial role of the earth observation satellites in numerous key applications, accessing the Low Earth Orbit (LEO) satellite Internet via Laser Inter-Satellite Links (LISLs) has emerged as a promising solution to help transmit substantial amounts of observation data to ground stations. For Very Low Earth Orbit (VLEO) observation satellite...

Recently, blockchain (BC)-empowered wireless sensor networks (WSN) emerged as a promising solution for secure and reliable data management. However, the integration of BC and WSN brings several challenges including long processing delay at BC, which reduces freshness of sensed data. Motivated by this, we first model the BC-empowered WSN and define...

As the fog-based internet of vehicles (IoV) is equipped with rich perception, computing, communication and storage resources, it provides a new solution for the bulk data processing. However, the impact caused by the mobility of vehicles brings a challenge to the content scheduling and resource allocation of content dissemination service. In this p...

As a key pillar technology for the future 6G networks, Terahertz (THz) communications can provide high-capacity transmissions, but suffers from severe propagation loss and line-of-sight (LoS) blockage that limits the network coverage. Narrow beams are required to compensate for the loss, but they in turn bring in beam misalignment challenge and deg...

Driven by the demand of Industry 4.0, the integration of 5G and time-sensitive networking (TSN) is proposed to provide ubiquitous connection and deterministic transmission. However, the heterogeneous access mechanisms and scheduling resolutions between 5G and TSN make it still intractable to schedule 5G and TSN resources jointly. To address this is...

Compared to reflective-only or transmissive-only reconfigurable intelligent surface (RIS), simultaneous transmitting and reflecting RIS (STAR-RIS) has the capability to simultaneously serve users on its both sides. Then, simultaneous indoor-and-outdoor communication (SIOC) has been commonly regarded as one of the most evident and promising applicat...

In this letter, an application of interference cancellation scheme into ISAC is investigated. First, an interference cancellation scheme of ISAC (IC-ISAC) is proposed, where the communication and sensing tasks are simultaneously accomplished by mitigating the mutual interference, thereby significantly improving the spectrum efficiency. Second, the...

In current reconfigurable intelligent surface (RIS)-aided systems, adding a new pair of transceivers often requires the RIS phases to be entirely re-calculated for all elements, inducing great overhead, especially for large-scale RISs. In this paper, we propose to only adjust part of RIS elements to serve the newly added pair, while the other eleme...

Integrated sensing, communications and computing (ISCC) system has been emerged as a crucial paradigm for addressing the growing demand of emerging wireless applications that require both ultra-reliable low-latency computing and high-precision sensing. In this paper, we investigate a non-orthogonal multiple access (NOMA)-assisted integrated sensing...

The next-generation wireless network is perceived to integrate with sensing capability and evolve into the perceptive mobile network (PMN), enabling massive sensing-intensive applications. However, the sensing function will affect the communication performance in cellular networks. To study the sensing and communication performance of PMNs and thei...

With the development of unmanned aerial vehicle (UAV) technology, using UAVs as aerial communication platforms to provide additional communication services is a promising technology. However, due to the scarcity of spectrum resources, UAV will inevitably causes unintentional interference to primary users (PUs) when transmitting data to secondary us...

This paper investigates the semantic communication and cooperative tracking control for an UAV swarm comprising a leader UAV and a group of follower UAVs, all interconnected via unreliable wireless multiple-input-multiple-output (MIMO) channels. Initially, we develop a dynamic model for the UAV swarm that accounts for both the internal interactions...

This paper is concerned with the theoretical modeling and analysis of uplink connection performance of a radiosonde network deployed in a typhoon. Similar to existing works, the stochastic geometry theory is leveraged to derive the expression of the uplink connection probability (CP) of a radiosonde. Nevertheless, existing works assume that network...

Timely status updating is the premise of emerging interaction-based applications in the Internet of Things (IoT). Using redundant devices to update the status of interest is a promising method to improve the timeliness of information. However, parallel status updating leads to out-of-order arrivals at the monitor, significantly challenging timeline...

In the era of 6G, featuring compelling visions of digital twins and metaverses, Extended Reality (XR) has emerged as a vital conduit connecting the digital and physical realms, garnering widespread interest. Ensuring a fully immersive wireless XR experience stands as a paramount technical necessity, demanding the liberation of XR from the confines...

The expansion of the Internet of Things (IoT) has led to a significant surge in data flow over edge networks, posing substantial challenges to data mining and management. While federated edge learning (FEEL) effectively accomplishes global integration and local training based on decentralized datasets, its deployment across expansive IoT networks i...

Spectrum sharing is promising as a solution to address the spectrum crunch by enabling the coexistence of different networks in the same frequency band. However, interference from concurrent transmissions remains an obstacle to further enhance spectral efficiency. Therefore, to overcome the bottleneck caused by multi-user interference, both rate-sp...

We optimize the Age of Information (AoI) in mobile networks using the age-threshold slotted ALOHA (TSA) protocol. The network comprises multiple source-destination pairs, where each source sends a sequence of status update packets to its destination over a shared spectrum. The TSA protocol stipulates that a source node must remain silent until its...

This paper proposes a novel integrated sensing and communication (ISAC) receiver design framework for OTFS (orthogonal time frequency space)-based MIMO (multi-inputmulti-output) systems from a unified perspective of variational inference. We first construct a factor graph representation for the OTFS-based MIMO system according to the factorization...

The integration of vehicle edge computing (VEC) and air-ground integrated network is considered as a key technology to achieve autonomous driving. It exploits the ubiquitous service coverage and enables tasks to be offloaded to various components such as high altitude platform (HAP), unmanned aerial vehicle (UAV) and road side unit (RSU). In this p...

Federated learning (FL) emerges as an innovative approach to manage a collection of client UAVs in order to co-train machine-learning models that are readily integrated into an Unmanned Aerial Vehicle (UAV) swarm. However, due to more erratic communication conditions than in terrestrial wireless networks, synchronous aggregation-which is utilized i...

Thanks to its superior features of fast read/write speed and low power consumption, spin-torque transfer magnetic random access memory (STT-MRAM) has become a promising non-volatile memory (NVM) technology that is suitable for many applications. However, the reliability of STT-MRAM is seriously affected by the variation of the memory fabrication pr...

With the rapid development of large-scale Low Earth Orbit (LEO) satellite internet, Very Low Earth Orbit (VLEO) Earth observation constellations are increasingly using InterSatellite Links (LISLs) for cross-layer access to Internet satellites. It is an effective means to enhance data return throughput. When both observation and communication satell...

With the rapid development of Mobile Edge Computing (MEC), various real-time applications have been deployed to benefit people's daily lives. The performance of these applications relies heavily on the freshness of collected environmental information, which can be quantified by its Age of Information (AoI). In the traditional definition of AoI, it...

Unmanned aerial vehicle (UAV) is expected to bring transformative improvements to the integrated sensing and communication (ISAC) systems, due to its high flexibility, high autonomy, large coverage and strong adaptability to various terrains. Sensory data is gathered by sensing UAVs (SUs) from the coverage area and then relayed to the corresponding...

Future wireless networks are envisioned to provide ubiquitous sensing services, driving a substantial demand for multi-dimensional non-convex parameter estimation. This entails dealing with non-convex likelihood functions containing numerous local optima. Variational Bayesian inference (VBI) provides a powerful tool for modeling complex estimation...

Multiband technology has recently received incremental attention for its ability to jointly utilize multiple non-contiguous frequency bands to achieve high-resolution delay estimation. In multiband scenarios, numerous signal processing algorithms for delay estimation have been proposed, while research on the fundamental limits remains underexplored...

This paper investigates the joint uplink (UL) and downlink (DL) robust transmission design for cell-free networks. The total data amount of the UL and DL transmissions is maximized in the presence of the statistical channel state information error by optimizing the UL digital combiners, UL transmission power, DL transmit beamforming vectors and UL/...

In existing federated learning (FL), the base station (BS) coordinates devices to collaboratively train a shared model by avoiding the transmission of raw data. To achieve communication-efficient model uploading, over-the-air computation (AirComp) is often employed to aggregate model parameters. However, in conventional AirComp assisted FL, the BS’...

Leveraging over-the-air computations for model aggregation is an effective approach to cope with the communication bottleneck in federated edge learning. By exploiting the superposition properties of multi-access channels, this approach facilitates an integrated design of communication and computation, thereby enhancing system privacy while reducin...

Vehicle-to-everything (V2X) communication supports numerous tasks, from driving safety to entertainment services. To achieve a holistic view, vehicles are typically equipped with multiple sensors to compensate for undetectable blind spots. However, processing large volumes of multi-modal data increases transmission load, while the dynamic nature of...

Digital twin (DT) technology has a high potential to satisfy different requirements of the ever-expanding new applications. Nonetheless, the DT placement in wireless digital twin networks (WDTNs) poses a significant challenge due to the conflict between unpredictable workloads and the limited capacity of edge servers. In other words, each edge serv...

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deploy...

Digital twin (DT) technology has a high potential to satisfy different requirements of the ever-expanding new applications. Nonetheless, the DT placement in wireless digital twin networks (WDTNs) poses a significant challenge due to the conflict between unpredictable workloads and the limited capacity of edge servers. In other words, each edge serv...

In space-air-ground integrated networks (SAGIN), receivers experience diverse interference from both the satellite and terrestrial transmitters. The heterogeneous structure of SAGIN poses challenges for traditional interference management (IM) schemes to effectively mitigate interference. To address this, a novel UAV-RIS-aided IM scheme is proposed...

The integration of unmanned aerial vehicles (UAVs) and marine communication networks has been emerging as a promising paradigm to cater for the growing maritime activities, e.g., marine environment monitoring and ocean resource exploration. The increasing growth of marine applications and services poses challenges for processing marine data, while...

Integrated sensing and communication (ISAC) provides a spectrum-efficient approach for simultaneously enabling reliable data transmission and high-quality sensing. This paper investigates an ISAC-enabled multi-device cooperative sensing system in which the devices perform cooperative sensing towards multiple targets in a time-division manner. Withi...

Generative artificial intelligence (GenAI) offers various services to users through content creation, which is believed to be one of the most important components in future networks. However, training and deploying big artificial intelligence models (BAIMs) introduces substantial computational and communication overhead. This poses a critical chall...

Semantic Communication (SemCom) is envisaged as the next-generation paradigm to address challenges stemming from the conflicts between the increasing volume of transmission data and the scarcity of spectrum resources. However, existing SemCom systems face drawbacks, such as low explainability, modality rigidity, and inadequate reconstruction functi...

Task-oriented semantic communication has gained increasing attention due to its ability to reduce the amount of transmitted data without sacrificing task performance. Although some prior efforts have been dedicated to developing semantic communications, the semantics in these works remains to be unexplainable. Challenges related to explainable sema...

Semantic Communication (SemCom) has garnered widespread attention due to its effectiveness and intelligence as an emerging technique. The current image SemCom system, based on Deep Joint Source-Channel Coding (JSCC), requires joint model training at both ends, leading to coupled models that need concurrent updates. Additionally, the semantics trans...

The surge in connected devices in 6G with typical massive access scenarios, such as smart agriculture, and smart cities, poses significant challenges to unsustainable traditional communication with limited radio resources and already high system complexity. Fortunately, the booming artificial intelligence technology and the growing computational po...

This paper is concerned with unmanned aerial vehicle (UAV) video coding and transmission in scenarios such as emergency rescue and environmental monitoring. Unlike existing methods of modeling video source coding and channel transmission separately, we investigate the joint source-channel optimization issue for video coding and transmission. Partic...

Traditional base station siting (BSS) methods rely heavily on drive testing and user feedback, which are laborious and require extensive expertise in communication, networking, and optimization. As large language models (LLMs) and their associated technologies advance, particularly in the realms of prompt engineering and agent engineering, network...

Image semantic communication (ISC) has garnered significant attention for its potential to achieve high efficiency in visual content transmission. However, existing ISC systems based on joint source-channel coding face challenges in interpretability, operability, and compatibility. To address these limitations, we propose a novel trustworthy ISC fr...

Trustworthy task-oriented semantic communication (ToSC) emerges as an innovative approach in the 6G landscape, characterized by the transmission of only vital information that is directly pertinent to a specific task. While ToSC offers an efficient mode of communication, it concurrently raises concerns regarding privacy, as sophisticated adversarie...

The integration of a near-space information network (NSIN) with the reconfigurable intelligent surface (RIS) is envisioned to significantly enhance the communication performance of future wireless communication systems by proactively altering wireless channels. This paper investigates the problem of deploying a RIS-integrated NSIN to provide energy...

Spectrum sensing and communication security are of crucial importance in cognitive radio networks (CRNs). In this paper, we utilize intelligent reflecting surfaces (IRS) to simultaneously enhance spectrum sensing accuracy and the secrecy performance of secondary users (SUs) through physical layer security (PLS) techniques. Additionally, we employ I...

Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients’ data. This paper delves into a class of federated problems characterized by non-convex and non-smooth loss functions, that are preva...

This paper explores an unmanned aerial vehicle (UAV)-assisted wireless sensor network (WSN), where one UAV-enabled mobile data collector periodically collects data from a set of ground sensor nodes (SNs) to the data center (DC), intending to fulfill the users' diverse needs. To accurately evaluate information freshness, we introduce the Age of Mult...

The rapidly evolving field of generative artificial intelligence technology has introduced innovative approaches for developing semantic communication (SemCom) frameworks, leading to the emergence of a new paradigm-generative SemCom (GSC). However, the complex processes involved in semantic extraction and generative inference may result in consider...

Given the crucial role of the earth observation satellites in numerous key applications, accessing the Low Earth Orbit (LEO) satellite Internet as intermediaries via Laser Inter-Satellite Links (LISLs) has emerged as a promising solution to help transmit substantial amounts of observation data to ground stations. For Very Low Earth Orbit (VLEO) obs...

Motivated by the information transmission in neurons with various applications in in-vivo nano-machines or emerging medical applications, Ye and Elishco introduced a communication channel, called the absorption channel, and proposed codes correcting absorption errors. For a non-binary alphabet Σ_q , the authors presented constructions of codes of l...

The Internet of Things (IoT) is widely acknowledged as an innovative paradigm that engenders profound alterations along with society's development due to its inevitability and universality. To effectively control IoT systems for specific tasks, it is important to tackle their emerging challenges, such as information transmission and sensing for the...

Massive random access has gained attention as a potential solution for IoT networks due to the throughput comparable to orthogonal multiple access and significantly lower signaling overhead. In this article, we introduce the design of modern random access-based IoT networks, focusing on enhancing the timeliness and fidelity of the status update inf...

The exponential growth of intelligent devices has given rise to the emergence of the intelligent Internet of Everything (IoE) as a significant scenario within 6G networks. In this context, Digital Twin (DT) plays a vital role in integrating 6G with IoE by providing a virtual replica of physical entities, facilitating seamless communication and inte...

We optimize the Age of Information (AoI) in mobile networks using the age-threshold slotted ALOHA (TSA) protocol. The network comprises multiple source-destination pairs, where each source sends a sequence of status update packets to its destination over a shared spectrum. The TSA protocol stipulates that a source node must remain silent until its...

Most existing works on dual-function radar-communication (DFRC) systems mainly focus on active sensing, but ignore passive sensing. To leverage multi-static sensing capability, we explore integrated active and passive sensing (IAPS) in DFRC systems to remedy sensing performance. The multi-antenna base station (BS) is responsible for communication a...

In integrated sensing and communication (ISAC) systems, communication signals are supposed to provide high-resolution sensing services. Toward this goal, multiband sensing has recently emerged as a promising technology that jointly utilizes multiple noncontiguous communication bands to improve the sensing performance of ISAC systems. In this articl...

This work focuses on the problem of data generation rate control in multi-stream status update system and proposes a decentralized node data generation rate control algorithm based on game theory. By analyzing the interaction between nodes during data transmission, a non-cooperative game model for node data generation rate is constructed. It is pro...

The use of integrated sensing and communications (ISAC) can improve the performance of both sensing and communication functionalities of wireless networks by flexibly sharing radio resources. However, its performance cannot be always guaranteed due to the dynamic interference circumstances. Therefore, it requires a sophisticated design of cooperati...

Foundation models (FMs) are general-purpose artificial intelligence (AI) models that have recently enabled multiple brand-new generative AI applications. The rapid advances in FMs serve as an important contextual backdrop for the vision of next-generation wireless networks, where federated learning (FL) is a key enabler of distributed network intel...

Timely status updating is the premise of emerging interaction-based applications in the Internet of Things (IoT). Using redundant devices to update the status of interest is a promising method to improve the timeliness of information. However, parallel status updating leads to out-of-order arrivals at the monitor, significantly challenging timeline...

Semantic communication (SemCom) has received considerable attention for its ability to reduce data transmission size while maintaining task performance. However, existing works mainly focus on analog SemCom with simple channel models, which may limit its practical application. To reduce this gap, we propose an orthogonal frequency division multiple...

The Industrial Internet of Things (IIoT) is emerging as a promising technology that can accelerate the application of industrial intelligence to smart factories. Because of the sensitive nature of user data, federated learning (FL) which performs distributed machine learning while preserving data privacy, is leveraged to meet the accuracy and priva...

In this paper, we aim to maximize the SSR for heterogeneous service demands in the cooperative MEC-assisted RAN slicing system by jointly considering the multi-node computing resources cooperation and allocation, the transmission resource blocks (RBs) allocation, and the time-varying dynamicity of the system. To this end, we abstract the system int...

We propose a federated version of adaptive gradient methods, particularly AdaGrad and Adam, within the framework of over-the-air model training. This approach capitalizes on the inherent superposition property of wireless channels, facilitating fast and scalable parameter aggregation. Meanwhile, it enhances the robustness of the model training proc...

Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Federated learning (FL) has emerged as a suitable and appealing distributed learning paradigm to deploy these applications at the network edge. Despite the many successful e...

Although numerous state-of-the-art deep neural networks have recently been proposed for malware classification, effectively detecting malware on a large-scale sample set and identifying zero-day or new malware variants still pose significant challenges. To address this issue, a deep hashing-based malware classification model is designed for malware...

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...

This work studies the average Age of Information (AoI) of a remote monitoring setup in which a multi-sensor system observes independent sources and updates the status to a common monitor using orthogonal channels. Considering the limited buffer size at the sensors, we first model each sensor as a first-come-first-served M/M/1/1 queue. Leveraging to...

In this paper, we consider an unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) network, where multiple UAVs with caching and computation functionalities are deployed to satisfy the heterogeneous content and service requests from the user equipments (UEs). In order to comprehensively characterize the capability of our considered net...

Satellite edge computing (SEC) has emerged as an innovative paradigm for future satellite-terrestrial integrated networks (STINs), expanding computation services by sinking computing capabilities into Low-Earth-Orbit (LEO) satellites. However, the mobility of LEO satellites poses two key challenges to SEC: 1) constrained onboard computing and trans...