Cognitive radio-enabled Internet of Vehicles (IoVs): a cooperative spectrum sensing and allocation for vehicular communication

Internet of Things (IoTs) era is expected to empower all aspects of Intelligent Transportation System (ITS) to improve transport safety and reduce road accidents. US Federal Communication Commission (FCC) officially allocated 75MHz spectrum in the 5.9GHz band to support vehicular communication which many studies have found insufficient. In this paper, we studied the application of Cognitive Radio (CR) technology to IoVs in order to increase the spectrum resource opportunities available for vehicular communication, especially when the officially allocated 75MHz spectrum in 5.9GHz band is not enough due to high demands as a result of increasing number of connected vehicles as already foreseen in the near era of IoTs. We proposed a novel CR Assisted Vehicular NETwork (CRAVNET) framework which empowers CR enabled vehicles to make opportunistic usage of licensed spectrum bands on the highways. We also developed a novel co-operative three-state spectrum sensing and allocation model which makes CR vehicular secondary units (SUs) aware of additional spectrum resources opportunities on their current and future positions and applies optimal sensing node allocation algorithm to guarantee timely acquisition of the available channels within a limited sensing time. The results of the theoretical analyses and simulation experiments have demonstrated that the proposed model can significantly improve the performance of a cooperative spectrum sensing and provide vehicles with additional spectrum opportunities without harmful interference against the Primary Users (PUs) activities

Visible Light Communication Cyber Security Vulnerabilities For Indoor And Outdoor Vehicle-To-Vehicle Communication

Light fidelity (Li-Fi), developed from the approach of Visible Light Communication (VLC), is a great replacement or complement to existing radio frequency-based (RF) networks. Li-Fi is expected to be deployed in various environments were, due to Wi-Fi congestion and health limitations, RF should not be used. Moreover, VLC can provide the future fifth generation (5G) wireless technology with higher data rates for device connectivity which will alleviate the traffic demand. 5G is playing a vital role in encouraging the modern applications. In 2023, the deployment of all the cellular networks will reach more than 5 billion users globally. As a result, the security and privacy of 5G wireless networks is an essential problem as those modern applications are in people\u27s life everywhere. VLC security is as one of the core physical-layer security (PLS) solutions for 5G networks. Due to the fact that light does not penetrate through solid objects or walls, VLC naturally has higher security and privacy for indoor wireless networks compared to RF networks. However, the broadcasting nature of VLC caused concerns, e.g., eavesdropping, have created serious attention as it is a crucial step to validate the success of VLC in wild. The aim of this thesis is to properly address the security issues of VLC and further enhance the VLC nature security. We analyzed the secrecy performance of a VLC model by studying the characteristics of the transmitter, receiver and the visible light channel. Moreover, we mitigated the security threats in the VLC model for the legitimate user, by 1) implementing more access points (APs) in a multiuser VLC network that are cooperated, 2) reducing the semi-angle of LED to help improve the directivity and secrecy and, 3) using the protected zone strategy around the AP where eavesdroppers are restricted. According to the model\u27s parameters, the results showed that the secrecy performance in the proposed indoor VLC model and the vehicle-to-vehicle (V2V) VLC outdoor model using a combination of multiple PLS techniques as beamforming, secure communication zones, and friendly jamming is enhanced. The proposed model security performance was measured with respect to the signal to noise ratio (SNR), received optical power, and bit error rate (BER) Matlab simulation results