scholarly journals Optimal Beamforming for IRS-Assisted SWIPT System with an Energy-Harvesting Eavesdropper

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2536
Author(s):  
Zhixiang Deng ◽  
Yan Pan
Keyword(s):  
Energy Transfer ◽  
Phase Shift ◽  
Energy Harvesting ◽  
Optimization Problem ◽  
Access Point ◽  
Secrecy Rate ◽  
Convex Optimization Problem ◽  
Alternating Optimization ◽  
Reflecting Surface ◽  
Optimal Beamforming

In this paper, we study a simultaneous wireless information and power transfer (SWIPT) system aided by the intelligent reflecting surface (IRS) technology, where an AP transmits confidential information to the legitimate information receiver (IR) in the presence of an energy harvesting (EH) receiver that could be a potential eavesdropper. We aim to maximize the secrecy rate at the legitimate IR by jointly optimizing the information beamforming vector and the energy transfer beamforming vector at the access point (AP), and the phase shift matrix at the IRS, subject to the minimum harvested power required by the EH receiver. The semi-definite relaxation (SDR) approach and the alternating optimization (AO) method are proposed to convert the original non-convex optimization problem to a series of semi-definite programs (SDPs), which are solved iteratively. Numerical results show that the achievable secrecy rate of the proposed IRS-assisted SWIPT system is higher than that of the SWIPT system without the assistance of the IRS.

scholarly journals Optimal Energy-Delay in Energy Harvesting Wireless Sensor Networks with Interference Channels

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 785 ◽  
Author(s):  
Dongbin Jiao ◽  
Liangjun Ke ◽  
Shengbo Liu ◽  
Felix Chan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Transfer ◽  
Energy Harvesting ◽  
Convex Optimization ◽  
Optimization Problem ◽  
Time Slot ◽  
Wireless Sensor ◽  
Interference Channels ◽  
Total Delay ◽  
Convex Optimization Problem

In this work, we investigate the capacity allocation problem in the energy harvesting wireless sensor networks (WSNs) with interference channels. For the fixed topologies of data and energy, we formulate the optimization problem when the data flow remains constant on all data links and each sensor node harvests energy only once in a time slot. We focus on the optimal data rates, power allocations and energy transfers between sensor nodes in a time slot. Our goal is to minimize the total delay in the network under two scenarios, i.e., no energy transfer and energy transfer. Furthermore, since the optimization problem is non-convex and difficult to solve directly, by considering the network with the relatively high signal-to-interference-plus-noise ratio (SINR), the non-convex optimization problem can be transformed into a convex optimization problem by convex approximation. We attain the properties of the optimal solution by Lagrange duality and solve the convex optimization problem by the CVX solver. The experimental results demonstrate that the total delay of the energy harvesting WSNs with interference channels is more than that in the orthogonal channel; the total network delay increases with the increasing data flow for the fixed energy arrival rate; and the energy transfer can help to decrease the total delay.

scholarly journals Secrecy Wireless-Powered Sensor Networks for Internet of Things

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Junxia Li ◽  
Hui Zhao ◽  
Xueyan Chen ◽  
Zheng Chu ◽  
Li Zhen ◽  
...  
Keyword(s):  
Time Allocation ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Access Point ◽  
Case Scenario ◽  
Secrecy Rate ◽  
Global Optimal Solution ◽  
Worst Case ◽  
Sdp Relaxation ◽  
Global Optimal

This paper investigates a secure wireless-powered sensor network (WPSN) with the aid of a cooperative jammer (CJ). A power station (PS) wirelessly charges for a user equipment (UE) and the CJ to securely transmit information to an access point (AP) in the presence of multiple eavesdroppers. Also, the CJ are deployed, which can introduce more interference to degrade the performance of the malicious eavesdroppers. In order to improve the secure performance, we formulate an optimization problem for maximizing the secrecy rate at the AP to jointly design the secure beamformer and the energy time allocation. Since the formulated problem is not convex, we first propose a global optimal solution which employs the semidefinite programming (SDP) relaxation. Also, the tightness of the SDP relaxed solution is evaluated. In addition, we investigate a worst-case scenario, where the energy time allocation is achieved in a closed form. Finally, numerical results are presented to confirm effectiveness of the proposed scheme in comparison to the benchmark scheme.

scholarly journals Aerial Intelligent Reflecting Surface Enabled Terahertz Covert Communications in Beyond-5G Internet of Things

2021 ◽  
Author(s):  
Milad Tatar Mamaghani ◽  
Yi Hong
Keyword(s):  
Wireless Communications ◽  
Internet Of Things ◽  
Optimization Problem ◽  
Data Dissemination ◽  
Performance Enhancement ◽  
Average Energy ◽  
Access Point ◽  
Artificial Noise ◽  
User Scheduling ◽  
Reflecting Surface

<div>Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in Internet of Things (IoT). </div><div>On the other hand, terahertz (THz) enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G wireless communications that promise a broad range of data-demand applications. In this paper, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) towards multiple ground user equipments (UEs) in IoT networks. Specifically, the AP intends to send data to the scheduled UE, while unscheduled UEs may behave as potential adversaries. To protect information messages and the privacy of the scheduled UE, we aim to devise an energy-efficient multi-UAV covert communication scheme, where the UIRS is for reliable data transmissions, and an extra UAV is utilized as a cooperative jammer generating artificial noise (AN) to degrade unscheduled UEs detection, improving communication covertness.</div><div>This poses a novel max-min optimization problem in terms of minimum average energy efficiency (mAEE), targetting to improve covert throughput and reduce UAVs' propulsion energy consumption subject to some practical constraints such as covertness which is determined analytically. Since the optimization problem is non-convex, we tackle it via the block successive convex approximation (BSCA) approach to iteratively solve a sequence of approximated convex sub-problems, designing the binary user scheduling, AP's power allocation, maximum AN jamming power, IRS beamforming, and both UAVs' trajectory and velocity planning. Finally, we present a low-complex overall algorithm for system performance enhancement with complexity and convergence analysis. Numerical results are provided to verify our analysis and demonstrate significant outperformance of our design over other existing benchmark schemes.</div>

scholarly journals Energy Efficiency Maximization with Optimal Beamforming in Secure MISO CRNs with SWIPT

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Liang Xue ◽  
Yao Ma ◽  
Miao Zhang ◽  
Wanqiang Qin ◽  
Jin-Long Wang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Optimization Problem ◽  
Type Inequality ◽  
Optimal Solution ◽  
Maximization Problem ◽  
Subtraction Problem ◽  
Channel State ◽  
Convex Optimization Problem ◽  
Single Output ◽  
Optimal Beamforming

In this paper, the optimal beamforming problem of multi-input single-output (MISO) cognitive radio (CR) downlink networks with simultaneous wireless information and power transfer is studied. Due to the nonconvexity of the objective function, the considered nonconvex optimization problem is firstly transformed to an equivalent subtraction problem and then an approximated convex optimization problem is obtained by using the successive convex approximation (SCA). When the instantaneous channel state information (CSI) of the eavesdropping link is unknown to the legitimate transmitter, another interruption-constrained energy efficiency optimization problem is proposed and the Bernstein-type inequality (BTI) is used to conservatively approximate the probability constraint. The paper proposes a two-level iterative algorithm based on Dinkelbach to find the optimal solution of the EE maximization problem. Numerical results validate the effectiveness and convergence of the proposed algorithm.

scholarly journals Time Allocation and Optimization in Time-Reversal Wireless Powered Communication Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Fangwei Li ◽  
Yue Wu ◽  
Yifang Nie ◽  
Ce Shi
Keyword(s):  
Convex Optimization ◽  
Communication Networks ◽  
Time Reversal ◽  
Time Allocation ◽  
Optimization Problem ◽  
Access Point ◽  
Convex Optimization Problem ◽  
Space Division Multiple Access ◽  
Optimal Resource ◽  
Special Space

This paper studies optimal resource allocation in the wireless powered communication networks (WPCN) combined with time reversal (TR) in which one hybrid access point (H-AP) broadcasts constant wireless energy to a set of distributed users in the downlink (DL) and receives information from the users via space division multiple access (SDMA) in the uplink (UL). Inevitable interferences will occur when users transmit information in the UL simultaneously and the special space-time focusing of TR is used to suppress the interferences. An efficient protocol is proposed to support wireless energy transfer (WET) and TR in the DL and wireless information transmission in the UL for the proposed TR-WPCN. We optimize the time allocations to the H-AP for DL WET, DL TR, and UL WIT to maximize the sum throughput. Due to the nonconvexity of the studied optimization problem, we optimize variables successively, where the nonconvex optimization problem is transformed into the convex optimization problem. The approximate convex optimization problem can then be solved iteratively combined with the dichotomy method. Simulation results show that the proposed scheme can effectively suppress interferences and improve system performance.

scholarly journals Aerial Intelligent Reflecting Surface Enabled Terahertz Covert Communications in Beyond-5G Internet of Things

2021 ◽  
Author(s):  
Milad Tatar Mamaghani ◽  
Yi Hong
Keyword(s):  
Wireless Communications ◽  
Internet Of Things ◽  
Optimization Problem ◽  
Data Dissemination ◽  
Performance Enhancement ◽  
Average Energy ◽  
Access Point ◽  
Artificial Noise ◽  
User Scheduling ◽  
Reflecting Surface

<div>Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in Internet of Things (IoT). </div><div>On the other hand, terahertz (THz) enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G wireless communications that promise a broad range of data-demand applications. In this paper, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) towards multiple ground user equipments (UEs) in IoT networks. Specifically, the AP intends to send data to the scheduled UE, while unscheduled UEs may behave as potential adversaries. To protect information messages and the privacy of the scheduled UE, we aim to devise an energy-efficient multi-UAV covert communication scheme, where the UIRS is for reliable data transmissions, and an extra UAV is utilized as a cooperative jammer generating artificial noise (AN) to degrade unscheduled UEs detection, improving communication covertness.</div><div>This poses a novel max-min optimization problem in terms of minimum average energy efficiency (mAEE), targetting to improve covert throughput and reduce UAVs' propulsion energy consumption subject to some practical constraints such as covertness which is determined analytically. Since the optimization problem is non-convex, we tackle it via the block successive convex approximation (BSCA) approach to iteratively solve a sequence of approximated convex sub-problems, designing the binary user scheduling, AP's power allocation, maximum AN jamming power, IRS beamforming, and both UAVs' trajectory and velocity planning. Finally, we present a low-complex overall algorithm for system performance enhancement with complexity and convergence analysis. Numerical results are provided to verify our analysis and demonstrate significant outperformance of our design over other existing benchmark schemes.</div>

scholarly journals Online joint power control for cooperative jamming systems with energy harvesting

2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988811
Author(s):  
Weijia Lei ◽  
Ziwei Wang ◽  
Hongjiang Lei
Keyword(s):  
Energy Harvesting ◽  
Power Control ◽  
Optimization Problem ◽  
Source Node ◽  
Artificial Noise ◽  
Secrecy Rate ◽  
Cooperative Jamming ◽  
Optimization Framework ◽  
Lyapunov Optimization

To maximize the long-term time-averaged secrecy rate of an energy harvesting wireless communication system, an online power control algorithm based on the Lyapunov optimization framework is proposed. The system is composed of a source node, a cooperative jamming node, and two destination nodes. The source node and the jamming node are powered by the energy harvesting device. Information sent to the two destination nodes is mutually confidential. Using the Lyapunov optimization framework, the original stochastic optimization problem is transformed into a per-time-slot optimization problem, and the power of the signal and that of the artificial noise are determined based on the current system state such as the power level of the batteries and channel coefficients. The fairness between the two destination nodes is considered too. Simulation results demonstrate that the proposed algorithm can effectively utilize the harvested energy and significantly improve the long-term averaged secrecy rate.

Joint power and duty-cycle design using alternating optimization algorithm under energy harvesting architectures

2020 ◽  
Vol 17 (12) ◽  
pp. 139-155
Author(s):  
Tong Wang ◽  
Xiang Yang ◽  
Feng Deng ◽  
Lin Gao ◽  
Yufei Jiang ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Optimization Algorithm ◽  
Duty Cycle ◽  
Joint Power ◽  
Alternating Optimization
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