Viet Quoc Pham

Trinity College Dublin | TCD · School of Computer Science and Statistics

Mobile edge computing (MEC) has been envisioned as a promising paradigm to handle the massive volume of data generated from ubiquitous mobile devices for enabling intelligent services with the help of artificial intelligence (AI). Traditionally, AI techniques often require centralized data collection and training in a single entity, e.g., an MEC se...

Since the invention in 2016, federated learning (FL) has been a key concept of artificial intelligence, in which the data of FL users needs not to be uploaded to the central server. However, performing FL tasks may not be feasible due to the unavailability of terrestrial communications and the battery limitation of FL users. To address these issues...

This work proposes a novel framework to address straggling and privacy issues for federated learning (FL)-based mobile application services, considering limited computing/communications resources at mobile users (MUs)/mobile application provider (MAP), privacy cost, the rationality and incentive competition among MUs in contributing data to the MAP...

Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-Things (IoT) devices to learn a collaborative model without sending the raw data to centralized nodes for processing. Despite numerous advantages, low computing resources at IoT devices and high communication costs for exchanging model parameters make applicat...

Federated learning (FL) has found many successes in wireless networks; however, the implementation of FL has been hindered by the energy limitation of mobile devices (MDs) and the availability of training data at MDs. How to integrate wireless power transfer and mobile crowdsensing towards sustainable FL solutions is a research topic entirely missi...

This paper investigates the performance of rate-splitting multiple access (RSMA)-assisted terahertz (THz)-based short-packet communication (SPC) networks to serve multi-users simultaneously. Considering the impact of imperfect successive interference cancellation (SIC), an approximate closed-form expression for the users’ block-error rate (BLER) is...

With the advent of new technologies and endeavors for automation in almost all day-to-day activities, the recent discussions on the metaverse life have a greater expectation. Furthermore, we are in the era of the fifth industrial revolution, where machines and humans collaborate to maximize productivity with the effective utilization of human intel...

Non-orthogonal multiple access (NOMA) has been viewed as a potential candidate for the upcoming generation of wireless communication systems. Comparing to traditional orthogonal multiple access (OMA), multiplexing users in the same time-frequency resource block can increase the number of served users and improve the efficiency of the systems in ter...

In this paper, an efficient automatic modulation classification for MIMO-OFDM signals is proposed for next generation wireless networks by exploiting cutting-edge deep learning techniques. Particularly, we design a deep network, namely OFDM modulation classification network (OMCNet), with asymmetric depthwise separable convolution, residual connect...

The paper presents an intelligent spectrum sensing approach for next-generation wireless networks by exploiting deep learning, in which we develop a deep convolutional network (ConvNet) to automatically identify Fifth Generation New Radio (5G NR) and Long-Term Evolution (LTE) signals under standards-specified channel models with diversified RF impa...

This paper investigates the performance of indoor terahertz (THz)-aided non-orthogonal multiple access (NOMA) systems in the context of spherical stochastic distances in downlink channel models. With the aim of improving system performance gains, a novel user pairing scheme subject to power control criterion is proposed to adaptively change with re...

Deep reinforcement learning (RL) has demonstrated great capabilities in dealing with sequential decision-making problems, but its performance is often bounded by suboptimal solutions in many complex applications. This paper proposes the use of human expertise to increase the performance of deep RL methods. Human domain knowledge is characterized by...

This paper analyzes the performance of simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS)-enabled short-packet non-orthogonal multiple access (NOMA) systems. A mode-switching protocol combined with partition strategies (MSPS) for the STAR-RIS design is proposed to simultaneously serve multiple actuators along w...

Integrated Communications and Sensing (ICS) has recently emerged as an enabling technology for ubiquitous sensing and IoT applications. For ICS application to Autonomous Vehicles (AVs), optimizing the waveform structure is one of the most challenging tasks due to strong influences between sensing and data communication functions. Specifically, the...

A novel partial decode-and-amplify non-orthogonal multiple access-inspired relaying (PDANR) protocol is proposed for uplink cooperative short-packet communication systems. Closed-form expressions for the average block-error-rate (BLER) of two cell-edge users are derived, based on which an asymptotic BLER expression is deduced to reveal valuable eng...

Recent technological advancements have considerately improved healthcare systems to provide various intelligent healthcare services and improve the quality of life. Federated learning (FL), a new branch of artificial intelligence (AI), opens opportunities to deal with privacy issues in healthcare systems and exploit data and computing resources ava...

The Internet of Things (IoT) is a major driving force for future sixth-generation (6G) wireless systems. With the emergence of various novel IoT applications, more data should be collected and transmitted. However, IoT devices are constrained by battery, transmit power, and processing capacity. Featured by line-of-sight communication links, favorab...

The fact that integrating the unmanned aerial vehicles (UAV) newfangled applications in the envisioned next generation (nextG) necessitates a considerable high throughput, makes terahertz (THz) band an emerging key enabler to support stringent requirements in the nextG wireless ecosystem. To fully utilize the potential of a synergy of UAV with THz...

Since Facebook officially changed its name to Meta in Oct. 2021, the metaverse has become a new norm of social networks and three-dimensional (3D) virtual worlds. The metaverse aims to bring 3D immersive and personalized experiences to users by leveraging many pertinent technologies. Despite great attention and benefits, a natural question in the m...

Unmanned aerial vehicle (UAV) swarms are considered as a promising technique for next-generation communication networks due to their flexibility, mobility, low cost, and the ability to collaboratively and autonomously provide services. Distributed learning (DL) enables UAV swarms to intelligently provide communication services, multi-directional re...

Along with the massive growth of the Internet from the 1990s until now, various innovative technologies have been created to bring users breathtaking experiences with more virtual interactions in cyberspace. Many virtual environments have been developed with immersive experience and digital transformation, but most are incoherent instead of being i...

The recent expansion of mobile IoT devices (MIoTDs) along with the exposure of many compute-intensive and latency-critical applications, have given a step rise to the mobile edge computing (MEC) platform to process computational microservices at the edge. The paramount importance of designing an effective incentive mechanism is a very important top...

Semantic communication (SemCom) and edge computing are two disruptive solutions to address emerging requirements of huge data communication, bandwidth efficiency and low latency data processing in Metaverse. However, edge computing resources are often provided by computing service providers and thus it is essential to design appealingly incentive m...

This paper studies the performance of unmanned aerial vehicle (UAV)-aided short-packet non-orthogonal multiple access (NOMA) systems under imperfect channel state information (ipCSI) and successive interference cancellation (ipSIC). Closed-form expressions for the average block-error rate (BLER), throughput, goodput, latency, reliability, and age o...

This paper investigates the performance of nonorthogonal multiple access (NOMA) systems with hybrid long and short-packet communications, where a cell-center user (CU) demands high quality-of-service while a cell-edge user (CE) faces poor channel quality. Targeting at this problem, we propose an effective power-beamforming scheme by jointly allocat...

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensi...

Data imbalance and complexity are the key challenges of applying federated learning (FL) techniques for wireless networks. In this paper, we propose a novel framework inspired by a divide-and-conquer algorithm. We aim to develop a full-stack federated distillation (FFD) method for federated learning over a massive Internet of Things network. We fir...

Sixth-generation mobile networks (6G) are expected to reach extreme communication capabilities to realize emerging applications demanded by the future society. This paper focuses on six technological directions towards 6G, namely, intent-based networking, THz communication, artificial intelligence, distributed ledger technology/blockchain, smart de...

In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an environment with heterogeneous data. Realizing the first problem, we aim to design a novel FL framework named Full-stack FL (F2L). More specifically, F2L utilizes a hierarchi...

Due to the fast, dynamic, and continuous arrival of data streams in the green Internet of Things (IoT) environment, the probability distribution of data streams changes over time. In real IoT scenarios such as unmanned aerial vehicle (UAV) detection and smart light switch control, data distribution changes have reduced the trained model’s accuracy...

This chapter discusses the key sixth‐generation driving trends elaborating why and how each trend demands a new generation of communication networks. Internet of Things (IoT) envisions to weave a global network of machines and devices that are capable of interacting with each other. The term “Small Data” refers to small data sets representing a lim...

This conclusion presents some closing thoughts on the concepts covered in the preceding chapters of this book. The book provides a visionary insight in to the present and future developments of sixth‐generation (6G). It covers a multitude of 6G aspects, including, what will be the 6G requirements, and how to build different architectures to play to...

Sixth‐generation (6G) is envisaged to play a key role in emerging healthcare applications. This chapter discusses the evolution of telehealth toward intelligent healthcare applications. It details emerging trends of intelligent healthcare applications. The chapter also focuses on security and privacy aspects of future healthcare applications. The e...

Harmonized mobile networks refer to the smooth interconnection of multiple communication technologies, data storage, and processing platforms at different scales. Extreme global network coverage refers to the digital inclusion through seamless global service coverage by connecting remote, rural, deep‐sea, and even space locations. This chapter focu...

Sixth‐generation (6G) is envisaged to rely on the advancements of Artificial Intelligence and data analytics to provide personalized and fully automated seamless communication services. However, this may lead to several security and privacy issues and concerns. This chapter discusses the security threat landscape of future 6G networks. In the fifth...

In a smart city, the administration/government uses Information and Communications Technology (ICTs) for efficient administration and governance to provide quality and better services to the urban citizens. Recent advances and innovations in technologies and devices, such as smart phones, cloud computing, edge computing, AI and allied technologies,...

Industrial automation together with the advent of Industry 5.0 is envisaged to be one of the key emerging sixth‐generation (6G) applications in the coming decade. This chapter discusses the network‐level requirements to enable Industry 5.0, Collaborative Robots, and Digital Twin. It examines the relevance of 6G networks for realization of Industria...

Network softwarization emerged with the advent of fifth‐generation. These functionalities are expected to evolve toward intelligent network softwarization with the dawn of sixth‐generation networks. This chapter focuses on the technological development toward intelligent network softwarization. Softwarized network architecture integrates the princi...

This chapter provides an overview of key technologies in future sixth‐generation (6G) wireless systems. It presents important 6G radio network technologies, including terahertz (THz) communications and nonterrestrial networks toward 3D networking. THz band channel is highly frequency‐selective. These channels suffer from high atmospheric absorption...

Sixth‐generation (6G) introduces a new landscape for mobile communication. This requires new legal framework and standardization efforts. This chapter focuses on 6G legal aspects and standardization approaches. The evolving 6G landscape will also demand changes in legal and regulatory domains. For instance, 6G mobile networks will heavily depend on...

Sixth‐generation (6G) has a tremendous potential and vision that can push new industries, applications, and businesses through connecting earth‐to‐space, space‐to‐space, space‐to‐deep sea, and so on. This chapter explores three visionary applications of 6G, namely, metaverse, space communication, and deep‐sea tourism. The concept of metaverse refer...

Mobile networks have been evolving since the 1980s, resulting in a new generation of mobile network every decade. Presently, fifth‐generation (5G) mobile networks are being deployed. The sixth‐generation (6G) mobile communication networks are expected to mark a disruptive transformation to the mobile networking paradigm by reaching extreme network...

Sixth‐generation (6G) mobile network architecture is envisaged to undergo a remarkable evolution from fifth‐generation to facilitate the flexible infrastructure demanded by future technologies and applications. This chapter describes how 6G evolves to be an intelligent and energy efficient network. The network architecture proposed by Letaief et al...

Future sixth‐generation (6G) networks are expected to have fully automated (zero‐touch) network services and management. This chapter discusses the needs of automated network and service management for 6G. It details the zero‐touch network and service management (ZSM) architecture and its components. One of the main design objectives of the ZSM ref...

Sixth‐generation (6G) networks are envisaged to have greater energy efficiency and green computing capabilities compared to its predecessors. This chapter focuses on the energy‐efficient network management with 6G. It discusses the energy‐efficient security. The chapter also focuses on the energy‐efficient resource management. Exploiting machine‐le...

Edge AI, also known as edge intelligence, combines the capabilities of edge computing with Artificial Intelligence (AI) to facilitate sixth‐generation applications and services. This chapter details the benefits of edge AI and explores building blocks for edge AI. Edge AI is the processing of AI algorithms on edge, that is, on users' devices. It ha...

The sixth‐generation (6G) networks are required to develop over existing fifth‐generation (5G) networks to support emerging technologies and applications. Enhanced Mobile Broadband (eMBB) represents a continuing evolution from traditional Long‐Term Evolution, which enables mobile broadband in limited applications. In 5G, eMBB is being enhanced grea...

A Radio Access Network (RAN) is an important part of any wireless communication system that connects end users with the other components of a network through radio communication links. This chapter discusses the three key concepts of sixth‐generation (6G) RANs, including Aerial Radio Access Network (ARAN), AI‐enabled Radio Access Network, and Open...

This article proposes a cooperative friendly jamming framework for swarm unmanned aerial vehicle (UAV)-assisted amplify-and-forward (AF) relaying networks with wireless energy harvesting. In particular, we consider a swarm of hovering UAVs that relays information from a terrestrial base station to a distant mobile user and simultaneously generates...

With outstanding features, machine learning (ML) has become the backbone of numerous applications in wireless networks. However, the conventional ML approaches face many challenges in practical implementation, such as the lack of labeled data, the constantly changing wireless environments, the long training process, and the limited capacity of wire...

Multi-access Edge Computing (MEC) is a novel edge computing paradigm that moves cloud-based processing and storage capabilities closer to the mobile users by implementing server resources in the access nodes. MEC helps fulfill the stringent requirements of 5G and beyond networks to offer anytime-anywhere connectivity for many devices with ultra-low...

The Internet of Things (IoT) has remarkably evolved over the last few years to realize a wide range of newly emerging services and applications empowered by the unprecedented proliferation of smart devices. The quality of IoT networks heavily relies on the involvement of devices for undertaking functions from data sensing, computation to communicat...

Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. One of those deep learning-powered applications recent...

In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris hawk optimizer (HHO), along with an updated set of applications in well established works. For this purpose, we first present an overview of HHO, including its logic of equations and mathematical m...

Data is generated over time by each device in the Internet of Things (IoT) ecosphere. Recent years have seen a resurgence in interest in the IoT due to its positive impact on society. However, due to the automatic management of IoT devices, the possibility of disclosing sensitive information without user consent is high. A situation in which inform...

Aerial access networks (AANs) and mobile edge computing (MEC) have been considered as key enablers of future networks. In this article, we investigate the application of MEC-empowered AANs (also known as aerial computing) for federated learning (FL), a promising technology for providing private and distributed solutions to mobile edge networks. We...

Recently, a considerable amount of works have been made to tackle the communication burden in federated learning (FL) (e.g., model quantization, data sparsification, and model compression). However, the existing methods, that boost the communication efficiency in FL, result in a considerable trade-off between communication efficiency and global con...

In this paper, an efficient deep learning-based waveform recognition method is introduced for coexistence radar-communication systems in the presence of channel impairments. The method first leverages smooth pseudo Wigner-Ville distribution (SPWVD) to analyze signals in the time-frequency domain, which in turn provides a high-resolution visual repr...

In recent years, the increasing popularity of unmanned aerial vehicles (UAVs) has arisen from the emergence of cutting-edge technologies deployed in small and low-cost devices. With the great capability of friendly uses and wide applications for multiple purposes, amateur drones can be piloted to effortlessly access any geographical area. This pose...

This paper is an influential attempt to identify and alleviate some of the issues with the recently proposed optimization technique called the Marine Predator Algorithm (MPA). With a visual investigation of its exploratory and exploitative behavior, it is observed that the transition of search from being global to local can be further improved. As...

Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry 4.0 and paves an insight for new industrial era. Nowadays smart machines and smart factories use machine learning/deep learning based models for incurring intelligence. However, storing and communicating the data to the cloud and end device leads to issues in prese...

In this article, we present our vision of preamble detection in a physical random access channel for next-generation (Next-G) networks using machine learning techniques. Preamble detection is performed to maintain communication and synchronization between devices of the Internet of Everything and next-generation nodes. Considering the scalability a...

In this article, we present our vision of preamble detection in a physical random access channel for next-generation (Next-G) networks using machine learning techniques. Preamble detection is performed to maintain communication and synchronization between devices of the Internet of Everything (IoE) and next-generation nodes. Considering the scalabi...

Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-Things (IoT) devices to learn a collaborative model without sending the raw data to centralized nodes for processing. Despite numerous advantages, low computing resources at IoT devices and high communication costs for exchanging model parameters make applicat...

In this paper, we propose a deep learning (DL)-based method to automatically identify the modulations of orthogonal frequency-division multiplexing (OFDM) signals in wireless communication systems. In particular, a cost-efficient OFDM modulation classification convolutional neural network (COM-ConvNet) is principally designed with grouped convoluti...

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry...

Machine learning methods are widely used to implement intrusion detection models for detecting and classifying intrusions in a network or a system. However, many challenges arise since hackers continuously change the attacking patterns by discovering new system vulnerabilities. The degree of malicious attempts increases rapidly; as a result, conven...

With the rapid emergence of advanced technologies for wireless communications, automatic modulation classification (AMC) has been deployed in the physical layer to blindly identify the modulation fashion of an incoming signal at the receiver and consequently improve the efficiency of spectrum utilization and management. Although recent works on AMC...

Since Facebook officially changed its name to Metaverse in Oct. 2021, the metaverse has become a new norm of social networks and three-dimensional (3D) virtual worlds. The metaverse aims to bring 3D immersive and personalized experiences to users by leveraging many pertinent technologies. Despite great attention and benefits, a natural question in...

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry...

In this chapter, we overview intelligent reflecting surface (IRS)-empowered wireless communication systems. We first present the fundamentals of IRS-assisted wireless transmission. On this basis, we explore the integration of IRS with various advanced transmission technologies, such as millimeter wave/Terahertz, non-orthogonal multiple access, mobi...

Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand for new business-oriented services in the fifth-generation (5G) and beyond network, the management of mobile networks is getting complex. Thus, traditional Network Management and Orchestration (MANO) approaches cannot keep up with rapidly evolving applicatio...

Automatic modulation classification (AMC) plays a vital role in cognitive radio to improve spectrum utilization efficiency, however, most of the existing works have focused on single-carrier communications in single-input single-output systems. In this paper, we propose an efficient AMC method for multiple-input multiple-output orthogonal frequency...