My publications


Chu Z, Fuhui Z, Zhu Z, Hu R, Xiao P (2017) Wireless Powered Sensor Networks for Internet of Things: Maximum Throughput and Optimal Power Allocation,IEEE Internet of Things Journal 5 (1) pp. 310-321 Institute of Electrical and Electronics Engineers (IEEE)
This paper investigates a wireless powered sensor
network (WPSN), where multiple sensor nodes are deployed to
monitor a certain external environment. A multi-antenna power
station (PS) provides the power to these sensor nodes during
wireless energy transfer (WET) phase, and consequently the
sensor nodes employ the harvested energy to transmit their own
monitoring information to a fusion center (FC) during wireless
information transfer (WIT) phase. The goal is to maximize
the system sum throughput of the sensor network, where two
different scenarios are considered, i.e., PS and the sensor nodes
belong to the same or different service operator(s). For the
first scenario, we propose a global optimal solution to jointly
design the energy beamforming and time allocation. We further
develop a closed-form solution for the proposed sum throughput
maximization. For the second scenario in which the PS and
the sensor nodes belong to different service operators, energy
incentives are required for the PS to assist the sensor network.
Specifically, the sensor network needs to pay in order to purchase
the energy services released from the PS to support WIT. In
this case, the paper exploits this hierarchical energy interaction,
which is known as energy trading. We propose a quadratic
energy trading based Stackelberg game, linear energy trading based
Stackelberg game, and social welfare scheme, in which we derive
the Stackelberg equilibrium for the formulated games, and the
optimal solution for the social welfare scheme. Finally, numerical
results are provided to validate the performance of our proposed
Li Bin, Fei Zesong, Chu Zheng, Zhou Fuhui, Wong Kai-Kit, Xiao Pei (2018) Robust Chance-Constrained Secure Transmission for Cognitive Satellite-Terrestrial Networks,IEEE Transactions on Vehicular Technology 67 (5) pp. 4208-4219 Institute of Electrical and Electronics Engineers (IEEE)
Cognitive satellite-terrestrial networks (CSTNs) have
been recognized as a promising network architecture for addressing
spectrum scarcity problem in next-generation communication
networks. In this paper, we investigate the secure transmission for
CSTNs where the terrestrial base station (BS) serving as a green
interference resource is introduced to enhance the security of the
satellite link. Adopting a stochastic model for the channel state
information (CSI) uncertainty, we propose a secure and robust
beamforming framework to minimize the transmit power, while
satisfying a range of outage (probabilistic) constraints concerning
the signal-to-interference-plus-noise ratio (SINR) recorded at the
satellite user and the terrestrial user, the leakage-SINR recorded at
the eavesdropper, as well as the interference power recorded at the
satellite user. The resulting robust optimization problem is highly
intractable and the key observation is that the highly intractable
probability constraints can be equivalently reformulated as the
deterministic versions with Gaussian statistics. In this regard, we
develop two robust reformulation methods, namely S-Procedure
and Bernstein-type inequality restriction techniques, to obtain a
safe approximate solution. In the meantime, the computational
complexities of the proposed schemes are analyzed. Finally, the effectiveness
of the proposed schemes are demonstrated by numerical
results with different system parameters.
Zhou F, Chu Z, Wu Y, Al-Dhahir N, Xiao P (2018) Enhancing PHY Security of MISO NOMA SWIPT
Systems With a Practical Non-Linear EH Model
Proceedings of 2018 IEEE ICC Workshop IEEE
Non-orthogonal multiple-access (NOMA) and simultaneous
wireless information and power transfer (SWIPT) are
promising techniques to improve spectral efficiency and energy
efficiency. However, the security of NOMA SWIPT systems has
not received much attention in the literature. In this paper, an
artificial noise-aided beamforming design problem is studied to
enhance the security of a multiple-input single-output NOMA
SWIPT system where a practical non-linear energy harvesting
model is adopted. The problem is non-convex and challenging
to solve. Two algorithms are proposed to tackle this problem
based on semidefinite relaxation (SDR) and successive convex
approximation. Simulation results show that a performance gain
can be obtained by using NOMA compared to the conventional
orthogonal multiple access. It is also shown that the performance
of the algorithm using a cost function is better than the algorithm
using SDR at the cost of a higher computation complexity.
Chen Hongzhi, Mi De, Chu Zheng, Xiao Pei, Tafazolli Rahim (2018) Rate-Splitting for Multigroup Multicast Beamforming in Multicarrier Systems,Proceedings of 19th IEEE international workshop on signal processing advances in wireless communications (SPAWC) Institute of Electrical and Electronics Engineers (IEEE)
In this paper, we consider multigroup multicast
transmissions with different types of service messages in an
overloaded multicarrier system, where the number of transmitter
antennas is insufficient to mitigate all inter-group interference.
We show that employing a rate-splitting based multiuser beamforming
approach enables a simultaneous delivery of the multiple
service messages over the same time-frequency resources in a
non-orthogonal fashion. Such an approach, taking into account
transmission power constraints which are inevitable in practice,
outperforms classic beamforming methods as well as current
standardized multicast technologies, in terms of both spectrum
efficiency and the flexibility of radio resource allocation.
Chu Zheng, Hao Wanming, Xiao Pei, Zhou Fuhui, Mi De, Zhu Zhengyu, Leung Victor C.M. (2018) Energy Efficient Hybrid Precoding in Heterogeneous Networks with Limited Wireless Backhaul Capacity,Proceedings of the IEEE Global Communications Conference, Abu Dhabi, UAE, 9-13 Dec 2018 Institute of Electrical and Electronics Engineers (IEEE)
This paper investigates a two-tier heterogeneous
networks (HetNets) with wireless backhaul, where millimeter
wave (mmWave) frequency is adopted at the macro base station
(MBS), and the cellular frequency is considered at small cell
BS (SBS) with orthogonal frequency division multiple access
(OFDMA). Subarray structure based hybrid analog/digital precoding
scheme is investigated to reduce the hardware cost
and energy consumption. Our goal is to maximize the energy
efficiency (EE) of the HetNets with limited wireless backhaul
capacity and all users? quality of service (QoS) constraints.
The formulated problem is non-convex mixed integer nonlinear
fraction programming (MINLFP), which is non-trivial to solve
directly. In order to circumvent this issue, we propose a two-loop
iterative resource allocation algorithm. Specifically, we transform
the outer-loop problem into a difference of convex programming
(DCP) by employing integer relaxation and Dinkelback method.
In addition, the first-order approximation is considered to linearize
this inner-loop DCP problem into a convex optimization
framework. Lagrange dual method is adapted to achieve the
optimal closed-form power allocation. Furthermore, we analyze
the convergence of the proposed iterative algorithm. Numerical
results are presented to demonstrate our proposed schemes.
Chu Zheng, Zhou Fuhui, Xiao Pei, Zhu hengyu, Mi De, Al-Dhahir Naofal, Tafazolli Rahim (2018) Resource Allocation for Secure Wireless Powered Integrated Multicast and Unicast Services with Full Duplex Self-Energy Recycling,IEEE Transactions on Wireless Communications IEEE
This paper investigates a secure wireless powered
integrated service system with full duplex self-energy recycling.
Specifically, an energy-constrained information transmitter (IT),
powered by a power station (PS) in a wireless fashion, broadcasts
two types of services to all users: a multicast service intended for
all users, and a confidential unicast service subscribed to by only
one user while protecting it from any other unsubscribed users
and an eavesdropper. Our goal is to jointly design the optimal
input covariance matrices for the energy beamforming, the multicast
service, the confidential unicast service, and the artificial
noises from the PS and the IT, such that the secrecy-multicast
rate region (SMRR) is maximized subject to the transmit power
constraints. Due to the non-convexity of the SMRR maximization
(SMRRM) problem, we employ a semidefinite programmingbased
two-level approach to solve this problem and find all of
its Pareto optimal points. In addition, we extend the SMRRM
problem to the imperfect channel state information case where
a worst-case SMRRM formulation is investigated. Moreover, we
exploit the optimized transmission strategies for the confidential
service and energy transfer by analyzing their own rank-one
profile. Finally, numerical results are provided to validate our
proposed schemes.
Wen Yun, Yoshida Makoto, Zhang Junqing, Chu Zheng, Xiao Pei, Tafazolli Rahim (2019) Machine Learning Based Attack Against Artificial Noise-aided Secure Communication,Proceedings of the 2019 IEEE International Conference on Communications (ICC): Communication and Information Systems Security Symposium (IEEE ICC 2019 - CISS Symposium) Institute of Electrical and Electronics Engineers (IEEE)
Physical layer security (PLS) technologies have attracted
much attention in recent years for their potential to
provide information-theoretically secure communications. Artificial
Noise (AN)-aided transmission is considered as one of
the most practicable PLS technologies, as it can realize secure
transmission independent of the eavesdropper?s channel status.
In this paper, we reveal that AN transmission has the dependency
of eavesdropper?s channel condition by introducing our proposed
attack method based on a supervised-learning algorithm which
utilizes the modulation scheme, available from known packet
preamble and/or header information, as supervisory signals of
training data. Numerical simulation results with the comparison
to conventional clustering methods show that our proposed
method improves the success probability of attack from 4.8%
to at most 95.8% for the QPSK modulation. It implies that
the transmission to the receiver in the cell-edge with low order
modulation will be cracked if the eavesdropper?s channel is good
enough by employing more antennas than the transmitter. This
work brings new insights into the effectiveness of AN schemes and
provides useful guidance for the design of robust PLS techniques
for practical wireless systems.
Hao Wanming, Chu Zheng, Zhou Fuhui, Xiao Pei, Leung Victor C. M., Tafazolli Rahim (2019) Hybrid Precoding Design for SWIPT Joint Multicast-Unicast mmWave System with Subarray Structure,IEEE ICC Conference Proceedings
In this paper, we investigate the hybrid precoding
design for joint multicast-unicast millimeter wave (mmWave) system, where the simultaneous wireless information and power transform is considered at receivers. The subarray-based sparse radio frequency chain structure is considered at base station (BS).
Then, we formulate a joint hybrid analog/digital precoding and power splitting ratio optimization problem to maximize the energy efficiency of the system, while the maximum transmit power at BS and minimum harvested energy at receivers are considered. Due to the difficulty in solving the formulated problem, we first design the codebook-based analog precoding approach and then, we only need to jointly optimize the digital precoding and power splitting ratio. Next, we equivalently transform the fractional objective function of the optimization problem into a subtractive form one and propose a two-loop iterative algorithm to solve it. For the outer loop, the classic Bi-section iterative algorithm is applied.
For the inner loop, we transform the formulated problem into a convex one by successive convex approximation techniques, which is solved by a proposed iterative algorithm. Finally, simulation results are provided to show the performance of the proposed algorithm.
Chu Zheng, Hao Wanming, Xiao Pei, Zhou Fuhui, Hu Rose Qingyang (2019) Low-Latency Driven Energy Efficiency for D2D
IEEE ICC Conference Proceedings IEEE
Low latency and energy efficiency are two important
performance requirements in various fifth-generation (5G) wire-less networks. In order to jointly design the two performance requirements, in this paper a new performance metric called effective energy efficiency (EEE) is defined as the ratio of the effective capacity (EC) to the total power consumption in a cellular network with underlaid device to device (D2D) communications. We aim to maximize the EEE of the D2D network subject to the D2D device power constraints and the minimum rate constraint of the cellular network. Due to the non-convexity
of the problem, we propose a two-stage difference-of-two-concave (DC) function approach to solve this problem. Towards that end, we first introduce an auxiliary variable to transfer the fractional objective function into a subtractive form. We then propose a successive convex approximation (SCA) algorithm to iteratively
solve the resulting non-convex problem. The convergence and the global optimality of the proposed SCA algorithm are both analyzed. The numerical results are presented to demonstrate the effectiveness of the proposed algorithm.
Hao Wanming, Zhou Fuhui, Chu Zheng, Xiao Pei, Tafazolli Rahim, Al Dhahir Naofal (2019) Beam Alignment for MIMO-NOMA Millimeter Wave Communication Systems,IEEE International Conference on Communications (ICC) Conference Proceedings
Abstract?Millimeter wave (mmWave) communication is a
promising technology in future wireless networks because of its wide bandwidths that can achieve high data rates. However, high beam directionality at the transceiver is needed due to the large path loss at mmWave. Therefore, in this paper, we investigate the beam alignment and power allocation problem in a nonorthogonal multiple access (NOMA) mmWave system. Diýerent from the traditional beam alignment problem, we consider the NOMA scheme during the beam alignment phase when two users
are at the same or close angle direction from the base station. Next, we formulate an optimization problem of joint beamwidth selection and power allocation to maximize the sum rate, where the quality of service (QoS) of the users and total power constraints are imposed. Since it is diýcult to directly solve the formulated
problem, we start by fixing the beamwidth. Next, we transform the power allocation optimization problem into a convex one, and a closed-form solution is derived. In addition, a one-dimensional search algorithm is used to find the optimal beamwidth. Finally, simulation results are conducted to compare the performance of the proposed NOMA-based beam alignment and power allocation scheme with that of the conventional OMA scheme.
Hao Wanming, Sun Gangcan, Chu Zheng, Xiao Pei, Zhu Zhengyu, Yang Shouyi, Tafazolli Rahim (2019) Beamforming Design in SWIPT-Based Joint Multicast-Unicast mmWave Massive MIMO with Lens-Antenna Array,IEEE Wireless Communications Letters pp. 1-1 Institute of Electrical and Electronics Engineers (IEEE)
In this letter, we study the beamforming design in a lens-antenna array-based joint multicast-unicast millimeter wave massive MIMO system, where the simultaneous wireless information and power transfer at users is considered. First, we develop a beam selection scheme based on the structure of the lens-antenna array and then, the zero forcing precoding is adopted to cancel the inter-unicast interference among users. Next, we formulate a sum rate maximization problem by jointly optimizing the unicast power, multicast beamforming and power splitting ratio. Meanwhile, the maximum transmit power constraint for the base station and the minimum harvested energy for each user are imposed. By employing the successive convex approximation technique, we transform the original optimization problem into a convex one, and propose an iterative algorithm to solve it. Finally, simulation results are conducted to verify the effectiveness of the proposed schemes.
Chu Zheng, Yu Wenjuan, Xiao Pei, Zhou Fuhui, Al-Dhahir Naofal, ul Quddus Atta, Tafazolli Rahim (2019) Opportunistic Spectrum Sharing for D2D-Based URLLC,IEEE Transactions on Vehicular Technology pp. 1-1 Institute of Electrical and Electronics Engineers (IEEE)
A device-to-device (D2D) ultra reliable low latency communications (URLLC) network is investigated in this paper. Specifically, a D2D transmitter opportunistically accesses the radio resource provided by a cellular network and directly transmits short packets to its destination. A novel performance metric is adopted for finite block-length code. We quantify the maximum achievable rate for the D2D network, subject to a probabilistic interference power constraint based on imperfect channel state information (CSI). First, we perform a convexity analysis which reveals that the finite block-length rate for the D2D pair in short-packet transmission is not always concave. To address this issue, we propose two effective resource allocation schemes using the successive convex approximation (SCA)-based iterative algorithm. To gain more insights, we exploit the mono- tonicity of the average finite block-length rate. By capitalizing on this property, an optimal power control policy is proposed, followed by closed-form expressions and approximations for the optimal average power and the maximum achievable average rate in the finite block-length regime. Numerical results are provided to confirm the effectiveness of the proposed resource allocation schemes and validate the accuracy of the derived theoretical results.
Chu Zheng, Hao Wanming, Xiao Pei, Shi Jia (2019) Intelligent Reflecting Surface Aided Multi-Antenna Secure Transmission,IEEE Wireless Communications Letters Institute of Electrical and Electronics Engineers (IEEE)
In this paper, we propose intelligent reflecting surface (IRS) aided multi-antenna physical layer security. We present a power efficient scheme to design the secure transmit power allocation and the surface reflecting phase shift. It aims to minimize the transmit power subject to the secrecy rate constraint at the legitimate user. Due to the non-convex nature of the formulated problem, we propose an alternative optimization algorithm and the semidefinite programming (SDP) relaxation to deal with this issue. Also, the closed-form expression of the optimal secure beamformer is derived. Finally, simulation results are presented to validate the proposed algorithm, which highlights the performance gains of the IRS to improve the secure transmission.
Chen Hongzhi, Mi De, Clerckx Bruno, Chu Zheng, Shi Jia, Xiao Pei (2019) Joint Power and Subcarrier Allocation Optimization for Multigroup Multicast Systems with Rate Splitting,IEEE Transactions on Vehicular Technology 69 (2) pp. 2306-2310 IEEE
In this article, we investigate a resource allocation problem for multicarrier multiuser MISO (multiple-input-Single-output) downlink systems, where multiple co-channel multicast groups are served simultaneously. We consider a rate-splitting transmission scheme to address the inevitable inter-group interference under an overloaded multigroup multicast scenario, where the insufficient number of transmit antennas prevents the conventional schemes from neutralizing the interference. We first formulate an optimization problem for maximizing the minimum multicast group rate among all groups on all available subcarriers. This problem involves a joint power and subcarrier allocation optimization, and is non-convex. We apply an iterative scheme based on successive convex approximation (SCA) to find the locally optimal solution. Simulation results demonstrate the performance gain of the proposed scheme compared to the state-of-the-art transmission schemes.
Chu Zheng, Hao Wanming, Xiao Pei, Khalily Mohsen, Tafazolli Rahim (2020) Resource Allocations for Symbiotic Radio with Finite Block Length Backscatter Link,IEEE Internet of Things Journal Institute of Electrical and Electronic Engineers
This paper exploits a generic downlink symbiotic radio (SR) system, where a Base Station (BS) establishes a direct (primary) link with a receiver having an integrated backscatter device (BD). In order to accurately measure the backscatter link, the backscattered signal packets are designed to have ?nite block length. As such, the backscatter link in this SR system employs the ?nite block-length channel codes. According to different types of the backscatter symbol period and transmission rate, we investigate the non-cooperative and cooperative SR (i.e., NSR and CSR) systems, and derive their average achievable rate of the direct and backscatter links, respectively. We formulate two optimization problems, i.e., transmit power minimization and energy ef?ciency maximization. Due to the non-convex property of these formulated optimization problems, the semide?nite programming (SDP) relaxation and the successive convex approximation (SCA) are considered to design the transmit beamforming vector. Moreover, a low-complexity transmit beamforming structure is constructed to reduce the computational complexity of the SDP relaxed solution. Finally, the simulation results are demonstrated to validate the proposed schemes.
Chen Hongzhi, Mi De, Chu Zheng, Xiao Pei (2020) Link-Level Performance of Rate-splitting based Downlink Multiuser MISO Systems,IEEE International Symposium on Personal, Indoor and Mobile Radio Communications