Toward 6G Internet of Things and the Convergence With RoF System

Chen, Na; Okada, Minoru

doi:10.1109/jiot.2020.3047613

Cited by 59 publications

(35 citation statements)

References 130 publications

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“…The logistics mode is optimised and improved, and the agricultural e-commerce common delivery method is presented in two publications [196,197] based on an examination of the distribution efficiency of the current mainstream agricultural goods logistics distribution mode. RoF is one of the most promising enablers for 6G IoT systems due to its excellent flexibility and efficiency.…”

Section: Resource Allocationmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard.

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Section: Resource Allocationmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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“…Eventually, the dream of smart homes will become a reality because any device in a remote location will be controlled by using a command given from a smart device. Internet of Things (IoT) is the undoubted combination of smart cities to coordination among a very large number of computing elements and sensors, objects or devices, people, processes, and data using the internet infrastructure [3]. The CR enabled 6G system will provide full IoT support to every type of devices which require any data rate constraints or latency issues.…”

Section: Introductionmentioning

confidence: 99%

Non-Cooperative Learning Based Routing for 6G-IoT Cognitive Radio Network

Malik¹,

Malik²,

Sanaullah³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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Cognitive Radio Network (CRN) has turn up to solve the issue of spectrum congestion occurred due to the wide spread usage of wireless applications for 6G based Internet of Things (IoT) network. The Secondary Users (SUs) are allowed to access dynamically the frequency channels owned by the Primary Users (PUs). In this paper, we focus the matter of contention of routing in multi hops setup by the SUs for a known destination in the presence of PUs. The traffic model for routing is generated on the basis of Poison Process of Markov Model. Every SU requires to reduce the end-to-end delay and packet loss of its transmission simultaneously to improve the data rate for the Quality of Service (QoS) of the Secondary Users. The issue of routing is formulated as stochastic learning process of non-cooperative games for the transformation of routing decisions of SUs. We propose a distributed non-cooperated reinforcement learning based solution for solving the issue of dynamic routing that can avert user interferences and channel interferences between the competing Sus in 6G-IoT network. The proposed solution combines and simulate the results to show the effectiveness and working of the proposed solution in decreasing the end-to-end delay, packet loss while meeting the average data rate requirement of QoS for SUs.

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“…IoT contains various types of devices, like sensors, microcontrollers, and transceivers that can be applied for an effective system. If we make comparison of the IoT services offered under the 5G (5th generation mobile network) deployment, 6G (6th generation mobile network) IoT has the capability to offer high-density heterogeneous types of smart devices which are involved for high capacity, more robust system architecture support and smart algorithms using the Artificial Intelligence (AI) [1]. Due to huge deployment of IoT smart devices, while the Big data analytics become more essential, at the same time maintaining the security among the IoT devices and the deployed gateway nodes is also becoming challenging task.…”

Section: Introductionmentioning

confidence: 99%

On the Security of a Secure and Lightweight Authentication Scheme for Next Generation IoT Infrastructure

et al. 2021

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In recent years, the Internet of things (IoT) has become an encouraging communication paradigm that has numerous applications including smart city, smart home and intelligent transportation system. The information sensed by several IoT smart devices can be security stored at the (cloud) servers. An external user, being a client, can access the services from a server for the sensing information, provided that a mutual authentication happens among them. Using the established session key among the user and the server, encrypted information with the help of session key can be delivered to the user by the server securely. Recently, Rana et al. proposed a smart-card based remote user authentication scheme using user password. In this comment paper, we carefully analyzed the scheme of Rana et al. and tracked down that their scheme is insecure against serious attacks, including stolen smart card attack, privileged-insider attack, user impersonation attack, password change attack and Ephemeral Secret Leakage (ESL) attack. Furthermore, their scheme does not preserve untraceability feature. To remedy these security pitfalls, we also provide some remedies that can help in building more secure and effective user authentication scheme to apply in securing next generation IoT infrastructure.INDEX TERMS Internet of Things (IoT), cryptanalysis, authentication, key agreement, security.

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Toward 6G Internet of Things and the Convergence With RoF System

Cited by 59 publications

References 130 publications

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Non-Cooperative Learning Based Routing for 6G-IoT Cognitive Radio Network

On the Security of a Secure and Lightweight Authentication Scheme for Next Generation IoT Infrastructure

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