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 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 Artificial-Noise-Aided Secure MIMO Wireless Communications via Intelligent Reflecting Surface

2020 ◽  
Vol 68 (12) ◽  
pp. 7851-7866 ◽  
Author(s):  
Sheng Hong ◽  
Cunhua Pan ◽  
Hong Ren ◽  
Kezhi Wang ◽  
Arumugam Nallanathan
Keyword(s):  
Wireless Communications ◽  
Artificial Noise ◽  
Reflecting Surface

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 Adaptive access-point and channel selection method using Markov approximation

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771876158
Author(s):  
Tomotaka Kimura ◽  
Kouji Hirata ◽  
Masahiro Muraguchi
Keyword(s):  
Markov Chain ◽  
Internet Of Things ◽  
Continuous Time ◽  
Optimization Problem ◽  
Access Point ◽  
Channel Selection ◽  
Selection Method ◽  
Markov Approximation ◽  
Continuous Time Markov Chain ◽  
Wireless Nodes

This article proposes an access-point and channel selection method for Internet of Things environments. Recently, the number of wireless nodes has increased with the growth of Internet of Things technologies. In order to accommodate traffic generated by the wireless nodes, we need to utilize densely placed wireless access-points. This article introduces a joint optimization problem of access-point and channel selection for such an environment. The proposed method deals with the optimization problem, using Markov approximation which adapts to dynamic changes in network conditions. Markov approximation is a distributed optimization framework, where a network is optimized by individual behavior of users forming a time-reversible continuous-time Markov chain. The proposed method searches optimal solution for the access-point and channel selection problem on the time-reversible continuous-time Markov chain. Simulation experiments demonstrate the effectiveness of the proposed method.

Network Performance Enhancement of Multi-sink Enabled Low Power Lossy Networks in SDN Based Internet of Things

2018 ◽  
Vol 48 (2) ◽  
pp. 367-398 ◽  
Author(s):  
Ghulam Shabbir ◽  
Adeel Akram ◽  
Muhammad Munwar Iqbal ◽  
Sohail Jabbar ◽  
Mai Alfawair ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Network Performance ◽  
Performance Enhancement ◽  
Lossy Networks
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