The integration of Visible-Light Communications technology (VLC) in Intelligent Transportation Systems (ITS) is a very promising platform for a cost-effective implementation of revolutionary ITS and cooperative ITS protocols. In this paper, we propose an infrastructure-to-vehicle-to-vehicle (I2V2V) VLC system for ITS, implementing it through a regular LED traffic light serving as a transmitter and a digital Active Decodeand-Relay (ADR) stage for decoding and relaying the received information towards further incoming units. The proposed VLC system targets the challenging and important case of ultra-low latency ADR transmission of short packets, as this is needed for emerging applications of automatic braking, car platooning and other critical automatic and/or assisted driving applications. The experimental validation of the ADR VLC chain, as well as a thorough statistical analysis of errors distribution in the transmission, has been performed for short to medium distances, up to 50 meters. The performances of the designed system are evaluated by measuring the packet error rate (PER) and latency in the whole ADR transmission chain. Our analysis shows that our system attains ultra-low, sub-ms latencies at 99.9% confidence level for PER as high as 5 × 10 −3 , yet granting a latency below 10 ms even for distances of 50 m. The demonstrated system prototype is compatible with IEEE 802.15.7 standard.

This paper reports a detailed experimental characterization of non Line-of-Sight (LoS) optical performances of a Visible Light Communication (VLC) system using a real traffic light for ultra-low latency, infrastructure-to-vehicle (I2V) communications for intelligent transportation systems (ITS) protocols. Despite the implementation of long-sought ITS protocols poses the crucial need to detail how the features of optical stages influence the overall performances of a VLC system in realistic configurations, such characterization has rarely been addressed at present. We carried out an experimental investigation in a realistic configuration where a regular traffic light (TX), enabled for VLC transmission, sends digital information towards a receiving stage (RX), composed by an optical condenser and a dedicated amplified photodiode stage. We performed a detailed measurements campaign of VLC performances encompassing a broad set of optical condensers, and for TX-RX distances in the range 3-50 m, in terms of both effective Field of View (EFOV) and Packet Error Rate (PER). The results show several angle-dependent nontrivial behaviors for different lens sets as a function of position on the measurement grid, highlighting critical aspects for ITS applications as well as identifying most suitable optical configurations depending on the specific application and on the required EFOV. We also provide a theoretical model for both the signal intensity and the EFOV as a function of several parameters, such as distance, RX orientation and focal length of the specific condenser. To our best knowledge, there are no optical and EFOV experimental analyses for VLC systems in ITS applications in literature. Our results could be very relevant in the near future to assess a most suited solution in terms of acceptance angle when designing a VLC system for real applications, where angle-dependent misalignment effects play a non-negligible role, and we argue that they could have more general implications with respect to the pristine I2V case mentioned here.

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One of the main revolutionary features of 5G networks is the ultra-low latency that will enable new services such as those for the future smart vehicles. The 5G technology will be able to support extreme-low latency thanks to new technologies and the wide flexible architecture that integrates new spectra and access technologies. In particular, visible light communication (VLC) is envisaged as a very promising technology for vehicular communications, since the information provided can flow by using the lights (as traffic-lights and car lights). This paper describes one of the first experiments on the joint use of 5G and VLC networks to provide real-time information to cars. The applications span from road safety to emergency alarm.

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Cognitive radio (CR) is a promising technology for future wireless spectrum allocation to improve the use of licensed bands. However, security challenges faced by cognitive radio technology are still a hot research topic. One of prevailing challenges is the radio frequency jamming attack, where adversaries are able to exploit on-the-fly reconfigurability potentials and learning mechanism of cognitive radios in order to devise and deploy advanced jamming tactics. Jamming attacks can significantly impact the performance of wireless communication systems and lead to significant overheads in terms of retransmission and increment of power consumption. In this context, a novel jammer detection algorithm is proposed using cyclic spectral analysis and artificial neural networks (ANN) for wide-band (WB) cognitive radios. The proposed approach assumes a WB spectrum occupied by various narrow-band (NB) signals, which can be either legitimate or jamming signals. The second order statistics, namely, the spectral correlation function (SCF) and ANN are used to classify each NB signal as a legitimate or jamming signal. The algorithm performance is shown with the help of simulations

This work presents a characterization of a low-cost, low-latency Visible Light Communication (VLC) prototype for infrastructure-to-vehicle (I2V) communication for future Intelligent Transportation Systems (ITS). The system consists of a regular traffic light as a transmitter (the red light is modulated with the information), and a photodetector as a receiver. The latter is equipped with low-cost Fresnel lenses as condensers, namely, 1 ′ ′ Fresnel and 2 ′ ′ Fresnel, to increase the optical gain of the system at the receiver. The system is capable of Active Decode and Relay (ADR) of information to further incoming units. The experimental characterization of amplitude and Packet Error Rate (PER) for the proposed system has been performed for distances up to 50 m. The results show that by incorporating the 2 ′ ′ Fresnel lens in the photodetector, an error free ( PER ≤ 10 − 5 ) I2V communication is established up to 50 m. Furthermore, the prototype can be used for both broadcast and beaconing transmission modes. This low-cost VLC-based system could offer sub-millisecond latency in the full ADR process for distances up to 36 m, which makes it suitable for integration in Cellular-V2X (C-V2X) and 5G platforms.

A new algorithm for jammer detection is proposed in this work for wide-band (WB) cognitive radio networks. First, the received WB signal, which is comprised of multiple narrow-band (NB) signals, is recovered from sub-Nyquist rate samples using compressed sensing. Compressed sensing allows us to alleviate Nyquist rate sampling requirements at the receiver A/D converter. After the Nyquist rate signal has been recovered, a cyclostationary feature detector is employed on this estimated signal to compute the cyclic features. Finally, the proposed algorithm uses the second order statistics, namely, the spectral correlation function (SCF), to classify each NB signal as a legitimate signal or a jamming signal. In the end, performance of the proposed algorithm is shown with the help of Monte-Carlo simulations under different empirical setups