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Dive into the research topics where Van-Dinh Nguyen is active.

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Featured researches published by Van-Dinh Nguyen.


IEEE Transactions on Information Forensics and Security | 2016

Joint Information and Jamming Beamforming for Secrecy Rate Maximization in Cognitive Radio Networks

Van-Dinh Nguyen; Trung Quang Duong; Octavia A. Dobre; Oh-Soon Shin

In this paper, we consider the secure beamforming design for an underlay cognitive radio multiple-input single-output broadcast channel in the presence of multiple passive eavesdroppers. Our goal is to design a jamming noise (JN) transmit strategy to maximize the secrecy rate of the secondary system. By utilizing the zero-forcing method to eliminate the interference caused by JN to the secondary user, we study the joint optimization of the information and JN beamforming for secrecy rate maximization of the secondary system while satisfying all the interference power constraints at the primary users, as well as the per-antenna power constraint at the secondary transmitter. For an optimal beamforming design, the original problem is a nonconvex program, which can be reformulated as a convex program by applying the rank relaxation method. To this end, we prove that the rank relaxation is tight and propose a barrier interior-point method to solve the resulting saddle point problem based on a duality result. To find the global optimal solution, we transform the considered problem into an unconstrained optimization problem. We then employ Broyden-Fletcher-Goldfarb-Shanno method to solve the resulting unconstrained problem, which helps reduce the complexity significantly, compared with the conventional methods. Simulation results show the fast convergence of the proposed algorithm and substantial performance improvements over the existing approaches.


wireless communications and networking conference | 2015

Opportunistic relaying with wireless energy harvesting in a cognitive radio system

Van-Dinh Nguyen; Son Dinh-Van; Oh-Soon Shin

In this paper, the performance of opportunistic relay selection (ORS) in a cognitive radio is analyzed over flat Rayleigh fading channels. Data transmission between source and destination is assumed to be entirely performed via the relays. Relay nodes are assumed to have ability to harvest energy from the source signal and use that harvested energy to forward the information to the destination. Specifically, we derive an exact expression for the outage probability of the secondary system considering the maximum transmit power at the secondary transmitter and relays, energy harvesting efficiency at relays, and interference constraint at the primary receiver. Under the assumption of perfect channel state information at the receivers, we evaluate the outage probability of a cognitive radio system with ORS and energy harvesting.


IEEE Journal on Selected Areas in Communications | 2017

Precoder Design for Signal Superposition in MIMO-NOMA Multicell Networks

Van-Dinh Nguyen; Hoang Duong Tuan; Trung Quang Duong; H. Vincent Poor; Oh-Soon Shin

The throughput of users with poor channel conditions, such as those at a cell edge, is a bottleneck in wireless systems. A major part of the power budget must be allocated to serve these users in guaranteeing their quality-of-service (QoS) requirements, hampering QoS for other users, and thus compromising the system reliability. In non-orthogonal multiple access (NOMA), the message intended for a user with a poor channel condition is decoded by itself and by another user with a better channel condition. The message intended for the latter is then successively decoded by itself after canceling the interference of the former. The overall information throughput is thus improved by this particular successive decoding and interference cancellation. This paper aims to design linear precoders/beamformers for signal superposition at the base stations of NOMA multiple-input multiple-output multi-cellular systems to maximize the overall sum throughput subject to the users’ QoS requirements, which are imposed independently on the users’ channel conditions. This design problem is formulated as the maximization of a highly nonlinear and nonsmooth function subject to nonconvex constraints, which is very computationally challenging. Path-following algorithms for its solution, which invoke only a simple convex problem of moderate dimension at each iteration, are developed. Generating a sequence of improved points, these algorithms converge at least to a local optimum. Extensive numerical simulations are then provided to demonstrate their merit.


IEEE Transactions on Communications | 2017

Spectral and Energy Efficiencies in Full-Duplex Wireless Information and Power Transfer

Van-Dinh Nguyen; Trung Quang Duong; Hoang Duong Tuan; Oh-Soon Shin; H. Vincent Poor

A communication system is considered consisting of a full-duplex multiple-antenna base station (BS) and multiple single-antenna downlink users (DLUs) and single-antenna uplink users (ULUs), where the latter need to harvest energy for transmitting information to the BS. The communication is thus divided into two phases. In the first phase, the BS uses all available antennas for conveying information to DLUs and wireless energy to ULUs via information and energy beamforming, respectively. In the second phase, ULUs send their independent information to the BS using their harvested energy while the BS transmits the information to the DLUs. In both the phases, the communication is operated at the same time and over the same frequency band. The aim is to maximize the sum rate and energy efficiency under ULU achievable information throughput constraints by jointly optimizing beamforming and time allocation. The utility functions of interest are nonconcave and the involved constraints are nonconvex, so these problems are computationally troublesome. To address them, path-following algorithms are proposed to arrive at least at local optima. The proposed algorithms iteratively improve the objectives with convergence guaranteed. Simulation results demonstrate that they achieve rapid convergence and outperform conventional solutions.


IEEE Transactions on Vehicular Technology | 2015

Secrecy Capacity of the Primary System in a Cognitive Radio Network

Van-Dinh Nguyen; Tiep Minh Hoang; Oh-Soon Shin

With fast growth of wireless services, secrecy has become an increasingly important issue for wireless networks. In this paper, we investigate the secrecy capacity of the primary system in a cognitive radio system based on artificial noise, which has been proposed for dealing with the eavesdropper. We first consider a special case of one eavesdropper and two regimes of the eavesdropping channel condition. Specifically, we analyze the impact of interference generated by a secondary system toward the primary system in a cognitive radio system. The channel state information (CSI) of the primary channel is assumed to be perfectly known at both the primary transmitter and receiver, whereas that of the eavesdropper is partially known. Under these assumptions, we derive analytical expressions for the ergodic secrecy capacity in the cases of strong eavesdropping channel and weak eavesdropping channel and analyze the impact of the secondary system on the primary ergodic secrecy capacity. Moreover, we extend the analysis to the general case of arbitrary eavesdropping channel condition and arbitrary number of eavesdroppers. Some numerical results will be also presented to verify the analysis.


global communications conference | 2014

Physical Layer Security for Primary System: A Symbiotic Approach in Cooperative Cognitive Radio Networks

Van-Dinh Nguyen; Trung Quang Duong; Oh-Soon Shin

Abstract-In this paper, we proposed a symbiotic approach for a secure primary network by allowing the secondary users to send the jamming noise to degrade the wiretap ability of the eavesdropper. In particular, assuming that the global channel state information is perfectly known at tranceivers, we consider the case of the primary transmitter equipped with only one antenna, which implies that the primary transmitter does not have beamforming capability. As the reward of having access to the frequency spectrum which is licensed by the the primary user, the secondary transmitter will assist the primary systems in terms of security by sending the jamming noise to the eavesdropper. We propose an algorithm to find the optimal transmit power for maximizing the secrecy capacity of the primary system. Numerical results are presented to validate our proposed scheme.


IEEE Transactions on Vehicular Technology | 2017

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks With Interference Constraints

Van-Dinh Nguyen; Le-Nam Tran; Trung Quang Duong; Oh-Soon Shin; Ronan Farrell

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output (MIMO) broadcast channel, where the secondary system consisting of a secondary base station (BS) and a group of secondary users is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing (ZF) method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex–concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm.


IEEE Communications Letters | 2016

An Efficient Zero-Forcing Precoding Design for Cognitive MIMO Broadcast Channels

Van-Dinh Nguyen; Hieu V. Nguyen; Oh-Soon Shin

We consider linear precoding design for an underlay cognitive radio multiple-input multiple-output broadcast channel in the presence of multiple primary users (PUs). Under the assumption of imperfect channel state information (CSI) of the PUs, the objective of this letter is to maximize the sum rate of the secondary system, subject to the power budget at the secondary base station and the interference power constraints at the PUs. The design problem is non-convex, and thus is difficult to solve in general. Herein, we first convert a non-convex constraint related to the imperfect CSI of the PUs into a convex constraint, and then invoke a rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink duality result. Simulation results are provided to demonstrate the effectiveness and robustness of the proposed design against CSI imperfection.


IEEE Transactions on Cognitive Communications and Networking | 2017

Enhancing PHY Security of Cooperative Cognitive Radio Multicast Communications

Van-Dinh Nguyen; Trung Quang Duong; Oh-Soon Shin; Arumugam Nallanathan; George K. Karagiannidis

In this paper, we propose a cooperative approach to improve the security of both primary and secondary systems in cognitive radio multicast communications. During their access to the frequency spectrum licensed to the primary users, the secondary unlicensed users assist the primary system in fortifying security by sending a jamming noise to the eavesdroppers, while simultaneously protect themselves from eavesdropping. The main objective of this paper is to maximize the secrecy rate of the secondary system, while adhering to all individual primary users’ secrecy rate constraints. In the case of active eavesdroppers and perfect channel state information (CSI) at the transceivers, the utility function of interest is nonconcave and the involved constraints are nonconvex, and thus, the optimal solutions are troublesome. To solve this problem, we propose an iterative algorithm to arrive at least to a local optimum of the original nonconvex problem. This algorithm is guaranteed to achieve a Karush–Kuhn–Tucker solution. Then, we extend the optimization approach to the case of passive eavesdroppers and imperfect CSI knowledge at the transceivers, where the constraints are transformed into a linear matrix inequality and convex constraints, in order to facilitate the optimal solution.


IEEE Access | 2017

Spectral Efficiency of Full-Duplex Multi-user System: Beamforming Design, User Grouping, and Time Allocation

Van-Dinh Nguyen; Hieu V. Nguyen; Chuyen T. Nguyen; Oh-Soon Shin

Full-duplex (FD) systems have emerged as an essential enabling technology to further increase the data rate of wireless communication systems. The key idea of FD is to serve multiple users over the same bandwidth with a base station (BS) that can simultaneously transmit and receive the signals. The most challenging issue in designing an FD system is to address both the harmful effects of residual self-interference caused by the transmit-to-receive antennas at the BS as well as the co-channel interference from an uplink user (ULU) to a downlink user (DLU). An efficient solution to these problems is to assign the ULUs/DLUs in different groups/slots, with each user served in multiple groups. Hence, this paper studies the joint design of transmit beamformers, ULUs/DLUs group assignment, and time allocation for each group. The specific aim is to maximize the sum rate under the ULU/DLU minimum throughput constraints. The utility function of interest is a difficult nonconcave problem, and the involved constraints are also nonconvex, and so this is a computationally troublesome problem. To solve this optimization problem, we propose a new path-following algorithm for computational solutions to arrive at least the local optima. Each iteration involves only a simple convex quadratic program. We prove that the proposed algorithm iteratively improves the objective while guaranteeing convergence. Simulation results confirm the fast convergence of the proposed algorithm with substantial performance improvements over existing approaches.

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Trung Quang Duong

Queen's University Belfast

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Chuyen T. Nguyen

Hanoi University of Science and Technology

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Arumugam Nallanathan

Queen Mary University of London

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