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Journal ArticleDOI

Delay-Sensitive Secure NOMA Transmission for Hierarchical HAP–LAP Medical-Care IoT Networks

- 01 Aug 2022 - 
- Vol. 18, Iss: 8, pp 5561-5572
TLDR
In this paper , a delay-sensitive secure nonorthogonal multiple access (NOMA) transmission scheme with the high-altitude platform (HAP) and low altitude platforms (LAPs) cooperated to securely provide delay sensitive medical-care services was proposed.
Abstract
Medical-care Internet of Things enables rapid medical assistance by providing comprehensive and clear healthy information. However, due to the limited infrastructure, it is difficult to quickly and securely transmit medical-care information in poverty-stricken or disaster-stricken areas. To tackle the above situation, in this article, we propose a delay-sensitive secure nonorthogonal multiple access (NOMA) transmission scheme with the high-altitude platform (HAP) and low-altitude platforms (LAPs) cooperated to securely provide delay-sensitive medical-care services. In the proposed scheme, we first design a novel HAP–LAP secure transmission framework to provide NOMA communication services to multiple hotspots. Constrained by the limited power and spectrum, we formulate an optimization problem, such that the privacy information delay is minimized. For thisnonconvex optimization problem, we design an alternating optimization framework, where the power, spectrum, and LAPs’ location are tackled in turn. In addition, we theoretically analyze the performance superiority compared with the orthogonal multiple access scheme and derive the secrecy outage probability closed-form expression. Finally, numerical results show the performance superiority of the proposed scheme compared with the current works with respect to the secure information delay.

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Citations
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Journal ArticleDOI

An HAP and UAVs Collaboration Framework for Uplink Secure Rate Maximization in NOMA-Enabled IoT Networks

TL;DR: Simulation results verify that the proposed network architecture can achieve a higher secure rate, faster convergence evolution, and lower complexity in comparison with the current works.
Journal ArticleDOI

Enhanced Lorenz-Chaotic Encryption Method for Partial Medical Image Encryption and Data Hiding in Big Data Healthcare

TL;DR: The Improved Chaos Encryption (ICE) is applied to improve the security based on randomness in the image encryption and image hiding and shows that the proposed ICE model has the PSNR value of 104.7 dB compared to the LSB-ROI method which has 97.61 dB PSNR.
Journal ArticleDOI

Trajectory Optimization and Channel Allocation for Delay Sensitive Secure Transmission in UAV-Relayed VANETs

TL;DR: In this article , the authors investigated the delay sensitive secure transmission problem in unmanned aerial vehicle (UAV)-relayed vehicular ad hoc networks (VANETs) and formulated this problem as a total information delay minimization problem by optimizing the UAV relay trajectory and channel allocation.
Journal ArticleDOI

Energy-Efficient Cluster Formation in IoT-Enabled Wireless Body Area Network

TL;DR: An enhanced version of the well-known algorithm MT-MAC is proposed, namely DT-MAC, to ensure successful message delivery and it considers node handover mechanism among virtual clusters to ensure network integrity and also uses the concept of minimum connected dominating set for network formation to achieve efficient energy utilization.
Journal ArticleDOI

Smart industrial IoT empowered crowd sensing for safety monitoring in coal mine

TL;DR: Wang et al. as mentioned in this paper proposed a Particle Swarm Optimization-Elman Neural Network (PE) algorithm for the mobile human position prediction and an ADI-LSTM neural network prediction algorithm for pressure values of machines supports in underground mines.
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Intelligent Resource Management Based on Reinforcement Learning for Ultra-Reliable and Low-Latency IoV Communication Networks

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TL;DR: A privacy-preserving medical record searching scheme based on ElGamal Blind Signature that achieves bilateral security, that is, whether the abstracts match or not, both of the privacy of the case-database and the private information of the current patient are well protected.
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