An urban expressway forwarding scheme for cognitive Internet of vehicles

The Internet of vehicles is an essential component for building smart cities that can improve traffic safety and provide multimedia entertainment services. The cognitive radio–enabled Internet of vehicles was proposed to resolve the conflict between the increasing demand of Internet of vehicles applications and the limited spectrum resources. The multi-hop transmission is one of the most important issues in cognitive radio–enabled Internet of vehicles networks. Nevertheless, most existing forwarding solutions designed for the cognitive radio–enabled Internet of vehicles did not consider the urban expressway scenario, where primary base stations are densely installed with small coverage areas. In this case, it is difficult to ensure that the sender and the receiver of the same cognitive radio link have similar channel availability statistics, which makes cognitive radio links more likely to be interrupted. To address this challenge, we develop a multi-hop forwarding scheme to minimize the end-to-end delay for such networks. We first formulate the delay minimization problem as a non-linear integer optimization problem. Then, we propose an approach to select the relay candidates by jointly considering the high mobility of vehicles and the unique cognitive radio spectrum usage distributions in urban expressway scenarios. Finally, we propose the low-latency forwarding strategies by considering the channel availability and the delay cost of different situations of relay candidates. Simulations show the advantages of our proposed scheme, compared with state-of-art methods.

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Integrating Cognitive Radio with Unmanned Aerial Vehicles: An Overview

Sensors ◽

10.3390/s21030830 ◽

2021 ◽

Vol 21 (3) ◽

pp. 830

Author(s):

Guilherme Marcel Dias Santana ◽

Rogers Silva de Cristo ◽

Kalinka Regina Lucas Jaquie Castelo Branco

Keyword(s):

Cognitive Radio ◽

Unmanned Aerial Vehicles ◽

Smart Cities ◽

Low Cost ◽

Real Data ◽

Base Stations ◽

Communication Performance ◽

Transmission Frequency ◽

Aerial Vehicles ◽

Future Challenges

Unmanned Aerial Vehicles (UAVs) demand technologies so they can not only fly autonomously, but also communicate with base stations, flight controllers, computers, devices, or even other UAVs. Still, UAVs usually operate within unlicensed spectrum bands, competing against the increasing number of mobile devices and other wireless networks. Combining UAVs with Cognitive Radio (CR) may increase their general communication performance, thus allowing them to execute missions where the conventional UAVs face limitations. CR provides a smart wireless communication which, instead of using a transmission frequency defined in the hardware, uses software transmission. CR smartly uses free transmission channels and/or chooses them according to application’s requirements. Moreover, CR is considered a key enabler for deploying technologies that require high connectivity, such as Smart Cities, 5G, Internet of Things (IoT), and the Internet of Flying Things (IoFT). This paper presents an overview on the field of CR for UAV communications and its state-of-the-art, testbed alternatives for real data experiments, as well as specifications to build a simple and low-cost testbed, and indicates key opportunities and future challenges in the field.

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Opportunistic Channel Allocation Model in Collocated Primary Cognitive Network

International Journal of Mathematical Engineering and Management Sciences ◽

10.33889/ijmems.2020.5.5.076 ◽

2020 ◽

Vol 5 (5) ◽

pp. 995-1012

Author(s):

Mangala Prasad Mishra ◽

Sunil Kumar Singh ◽

Deo Prakash Vidyarthi

Keyword(s):

Cognitive Radio ◽

Channel Allocation ◽

Radio Spectrum ◽

Base Stations ◽

Spectrum Utilization ◽

Secondary Users ◽

Primary Users ◽

Proposed Model ◽

Radio Resources ◽

Primary Base

The growing demand of radio spectrum to facilitate the primary/secondary users in a cellular network is a challenging task. Many channel allocation models, applying cognition, have been proposed to increase the radio spectrum utilization. The proposed model peruses three types of users: primary users (PUs), opportunistic primary users (OPUs), and secondary users (SUs) that use the radio resources in collocated primary base stations. Out of these users, the opportunistic primary users and secondary users may request for handover as per their requirements. The objective of the model is to enhance the radio spectrum utilization by the opportunistic utilization of radio resources by OPUs and by enabling cognitive radio base stations to collect free channel information dynamically. The cognitive radio base station maintains the centralized free channel at collocated primary base stations to facilitate the SUs opportunistically. The proposed channel allocation technique maintains the Quality of Experience (QoE) of the users as well. The performance analysis of the model is done by simulation which diversifies the importance of the proposed model in the view of minimum blocked services.

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Spectrum Sensing and Identification Techniques of Cognitive Radio Networks

Advances in Wireless Technologies and Telecommunication - Sensing Techniques for Next Generation Cognitive Radio Networks ◽

10.4018/978-1-5225-5354-0.ch011 ◽

2019 ◽

pp. 189-202

Author(s):

Rashmi M. Kittali ◽

Ashok V. Sutagundar

Keyword(s):

Cognitive Radio ◽

Spectrum Sensing ◽

Cognitive Radio Networks ◽

Dynamic Spectrum Access ◽

Radio Spectrum ◽

Radio Networks ◽

Radio Link ◽

Radio Systems ◽

Key Enabling Technologies ◽

Identification Techniques

Cognitive radio emerged as one of the key enabling technologies of dynamic spectrum access, addressing the problem of inefficient usage of the available radio spectrum. It aims at providing more effective and convenient communication capabilities. Cognitive radio which is considered as the key technology for future mobile computing and wireless communications can form cognitive radio networks (CRN) by extending the features of radio link to network layer functions and above. The cognitive radio systems have the ability to exploit the spectrum holes by detecting and using them in an opportunistic manner through spectrum sensing. This chapter will brief the various architectures of cognitive radio networks, terminal capabilities of cognitive radio as nodes of CRN highlighting the spectrum sensing ability and different methods of it, and some applications of CRN.

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Blockchain-based Internet of Vehicles (BIoV): An Approach Towards Smart Cities Development

2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) ◽

10.1109/icraie51050.2020.9358355 ◽

2020 ◽

Author(s):

Shahirah Mohamed Hatim ◽

Shamsul Jamel Elias ◽

Razizul Mohamad Ali ◽

Jamaluddin Jasmis ◽

Azlan Abdul Aziz ◽

...

Keyword(s):

Smart Cities ◽

Internet Of Vehicles

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Blockchain-Based Solutions for UAV-Assisted Connected Vehicle Networks in Smart Cities: A Review, Open Issues, and Future Perspectives

Telecom ◽

10.3390/telecom2010008 ◽

2021 ◽

Vol 2 (1) ◽

pp. 108-140

Author(s):

Paulo Álvares ◽

Lion Silva ◽

Naercio Magaia

Keyword(s):

Traffic Congestion ◽

Resource Constraints ◽

Smart Cities ◽

The Internet ◽

Connected Vehicle ◽

Sensitive Data ◽

Internet Of Vehicles ◽

Smart Vehicles ◽

Security Properties ◽

Vehicle Networks

It had been predicted that by 2020, nearly 26 billion devices would be connected to the Internet, with a big percentage being vehicles. The Internet of Vehicles (IoVa) is a concept that refers to the connection and cooperation of smart vehicles and devices in a network through the generation, transmission, and processing of data that aims at improving traffic congestion, travel time, and comfort, all the while reducing pollution and accidents. However, this transmission of sensitive data (e.g., location) needs to occur with defined security properties to safeguard vehicles and their drivers since attackers could use this data. Blockchain is a fairly recent technology that guarantees trust between nodes through cryptography mechanisms and consensus protocols in distributed, untrustful environments, like IoV networks. Much research has been done in implementing the former in the latter to impressive results, as Blockchain can cover and offer solutions to many IoV problems. However, these implementations have to deal with the challenge of IoV node’s resource constraints since they do not suffice for the computational and energy requirements of traditional Blockchain systems, which is one of the biggest limitations of Blockchain implementations in IoV. Finally, these two technologies can be used to build the foundations for smart cities, enabling new application models and better results for end-users.

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Multi-Winner Spectrum Allocation in Cognitive Radio Networks: A Single-Sided Auction Theoretic Modelling Approach with Sequential Bidding

Electronics ◽

10.3390/electronics10050602 ◽

2021 ◽

Vol 10 (5) ◽

pp. 602

Author(s):

Monisha Devi ◽

Nityananda Sarma ◽

Sanjib K. Deka

Keyword(s):

Cognitive Radio ◽

Communication Networks ◽

Spectrum Sharing ◽

Single Channel ◽

Group Formation ◽

Radio Spectrum ◽

Spectrum Allocation ◽

Allocation Mechanism ◽

Sealed Bid ◽

Sequential Bidding

Cognitive radio (CR) has evolved as a novel technology for overcoming the spectrum-scarcity problem in wireless communication networks. With its opportunistic behaviour for improving the spectrum-usage efficiency, CR enables the desired secondary users (SUs) to dynamically utilize the idle spectrum owned by primary users. On sensing the spectrum to identify the idle frequency bands, proper spectrum-allocation mechanisms need to be designed to provide an effectual use of the radio resource. In this paper, we propose a single-sided sealed-bid sequential-bidding-based auction framework that extends the channel-reuse property in a spectrum-allocation mechanism to efficiently redistribute the unused channels. Existing auction designs primarily aim at maximizing the auctioneer’s revenue, due to which certain CR constraints remain excluded in their models. We address two such constraints, viz. the dynamics in spectrum opportunities and varying availability time of vacant channels, and formulate an allocation problem that maximizes the utilization of the radio spectrum. The auctioneer strategises winner determination based on bids collected from SUs and sequentially leases the unused channels, while restricting the channel assignment to a single-channel-multi-user allocation. To model the spectrum-sharing mechanism, we initially developed a group-formation algorithm that enables the members of a group to access a common channel. Furthermore, the spectrum-allocation and pricing algorithms are operated under constrained circumstances, which guarantees truthfulness in the model. An analysis of the simulation results and comparison with existing auction models revealed the effectiveness of the proposed approach in assigning the unexploited spectrum.

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