Secrecy Rate Maximization in Virtual-MIMO Enabled SWIPT for 5G Centric IoT Applications

Jaiswal, Ajay; Kumar, Sushil; Kaiwartya, Omprakash; Kumar, Neeraj; Song, Houbing; Lloret, Jaime

doi:10.1109/jsyst.2020.3036417

Cited by 22 publications

(11 citation statements)

References 29 publications

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“…As an example, the "ultra-low latency" will extremely enhance the applications in industry by providing real-time interactivity for services, such as industrial IoT (IIoT), smart grid, self-driving cars, vehicle intelligence, etc. The main requirements in industry include (Notes, 2018;Jaiswal et al, 2020):…”

Section: Introductionmentioning

confidence: 99%

Future Industry Internet of Things with Zero-trust Security

2022

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The emerging techniques, such as the fifth-generation communications (5G), Internet of Things (IoT), blockchain, artificial intelligence, etc., are operating in unison will drive the transformation of global business forward. The 5G technology is expected to unleash a massive IoT ecosystems by providing massive connectivity for huge number of IoT devices with faster data rate, ultra-low latency, and low-cost access. The 5G networks will be designed to bring the level of performance needed for massive IoT and will enable a perceived fully ubiquitous connected world. Meanwhile, the blockchain being promoted as the fundamental for new business model in Future IoT (FIoT). This paper attempts to provide a set of new directions and ideas for research in 5G/6G enabled IoT and new technique trends in IoT. The current IoT are facing a number of challenges, such as massive IoT devices access, network performances, security, standardization, and critical applications. This paper investigates new technologies, such as 5G, zero-trust, and blockchain will catalyse the innovation in IoT. Specifically, a zero-trust security architecture for FIoT is proposed and a blockchain-based device authentication in IoT environment (BasIoT) is proposed that can provide massive secure device access in FIoT.

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Section: Introductionmentioning

confidence: 99%

Future Industry Internet of Things with Zero-trust Security

2022

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“…Since V2X communication relies on RSU, physical layer security is potential. Therefore, in [24], the authors propose a secure and energy-efficient virtual multiple-input multiple-output framework that supports simultaneous wireless information and power transmission. This framework can effectively improve the security rate of the Internet of Things system.…”

Section: Introductionmentioning

confidence: 99%

Sparse Bayes Tensor and DOA Tracking Inspired Channel Estimation for V2X Millimeter Wave Massive MIMO System

Luo

Zhou

Wang

et al. 2021

Sensors

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Efficient vehicle-to-everything (V2X) communications improve traffic safety, enable autonomous driving, and help to reduce environmental impacts. To achieve these objectives, accurate channel estimation in highly mobile scenarios becomes necessary. However, in the V2X millimeter-wave massive MIMO system, the high mobility of vehicles leads to the rapid time-varying of the wireless channel and results in the existing static channel estimation algorithms no longer applicable. In this paper, we propose a sparse Bayes tensor and DOA tracking inspired channel estimation for V2X millimeter wave massive MIMO system. Specifically, by exploiting the sparse scattering characteristics of the channel, we transform the channel estimation into a sparse recovery problem. In order to reduce the influence of quantization errors, both the receiving and transmitting angle grids should have super-resolution. We obtain the measurement matrix to increase the resolution of the redundant dictionary. Furthermore, we take the low-rank characteristics of the received signals into consideration rather than singly using the traditional sparse prior. Motivated by the sparse Bayes tensor, a direction of arrival (DOA) tracking method is developed to acquire the DOA at the next moment, which equals the sum of the DOA at the previous moment and the offset. The obtained DOA is expected to provide a significant angle information update for tracking fast time-varying vehicular channels. The proposed approach is evaluated over the different speeds of the vehicle scenarios and compared to the other methods. Simulation results validated the theoretical analysis and demonstrate that the proposed solution outperforms a number of state-of-the-art researches.

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“…In the next generation stochastic wireless network, it is critical to have information about channel gain, energy harvesting capability, and neighboring systems interference in future for choosing an optimal relay and transmit power [8]. To solve the aforementioned problem, reinforcement learning (RL) approach has been used for optimal decision making [9]. For example, channel aware RL based Multi-path Adaptive routing has been suggested for optimal relay selection in WSN [10].…”

Section: Introductionmentioning

confidence: 99%

Quantum Learning-Enabled Green Communication for Next-Generation Wireless Systems

Jaiswal

Kumar

Kaiwartya

et al. 2021

IEEE Trans. on Green Commun. Netw.

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Next generation wireless systems have witnessed significant R&D attention from academia and industries to enable wide range of applications for connected environment around us. The technical design of next generation wireless systems in terms of relay and transmit power control is very critical due to the ever-reducing size of these sensor enabled systems. The growing demand of computation capability in these systems for smart decision making further diversified the significance of relay and transmit power control. Towards harnessing the benefits of Quantum Reinforcement Leaning (QRL) in the design of next generation wireless systems, this paper presents a framework for joint optimal Relay and transmit Power Selection (QRL-RPS). In QRL-RPS, each sensor node learns using its present and past local state's knowledge to take optimal decision in relay and transmit power selection. Firstly, RPS problem is modelled as a Markov Decision Process (MDP), and then QRL optimization aspect of the MDP problem is formulated focusing on joint optimization of energy consumption and throughput as network utility. Secondly, a QRL-RPS algorithm is developed based on Grover's iteration to solve the MDP problem. The comparative performance evaluation attests the benefit of the proposed framework as compared to the stateof-the-art techniques.

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Secrecy Rate Maximization in Virtual-MIMO Enabled SWIPT for 5G Centric IoT Applications

Cited by 22 publications

References 29 publications

Future Industry Internet of Things with Zero-trust Security

Future Industry Internet of Things with Zero-trust Security

Sparse Bayes Tensor and DOA Tracking Inspired Channel Estimation for V2X Millimeter Wave Massive MIMO System

Quantum Learning-Enabled Green Communication for Next-Generation Wireless Systems

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