**6.2 Effects of vehicle speed ratio in VANETs**

The simulation results presented in Figs. 4-5 are obtained using *K* = 0, *f*<sup>2</sup> = 50*Hz*, *f*<sup>1</sup> = 0, 10 and 50*Hz* when the corresponding value of speed ratio *a* equals to 0, 0.2 and 1. The imaginary part of the auto-correlation of the complex envelope for the proposed two SoS models is always equal to 0, which is in line with the ideal situation and shows better performance compared with the reference model.

Fig. 4 shows the real part of correlation properties of the above models with different *a* in VANETs. It is observed that the proposed models provide a better approximation to the desired auto-correlation when *a* increases. From Figs. 5a-5c, we found that the variances of the auto-correlation of our models tend to be lower with a larger value of *a*. So the proposed models perform better with a smaller relative speed difference. A physical interpretation

remote sensing are pushing ITS towards a major leap forward. Vehicles become sophisticated computing systems, with several computers and sensors onboard, each dedicated to certain car operations. Interconnected vehicles do not only collect information about themselves and their environments, but they also exchange the information in real time with other nearby vehicles. As radio-communication-based solutions can operate beyond the line-of-sight constraints, they can enable cooperative approaches. Vehicles and infrastructure cooperate to perceive potentially dangerous situations in an extended space and time horizon. Appropriate vehicular communication architectures are necessary to create reliable and extended driving

<sup>171</sup> Sum-of-Sinusoids-Based Fading Channel Models

A number of technical challenges need to be resolved in order to deploy vehicular networks and to provide related services for drivers and passengers in such networks. Scalability and interoperability are two important issues that should be addressed. The employed protocols and mechanisms should be scalable to numerous vehicles and interoperable with different wireless technologies, such as reliable link performance and MAC protocols, routing and dissemination, IP configuration and mobility management, security etc. As a key component of the ITS, vehicular wireless networks, has attracted research attention from both the academia and industry of US, EU, and Japan. Although many works have been done on communication and routing protocol, only few models have been developed to characterize

In this chapter, we proposed a new statistical and deterministic SoS model for IVC fading channels with a LOS component in VANETs. The properties of the proposed models were derived and verified in terms of the auto-correlation and the cross-correlation by comparison between theoretical and simulation results. The statistics of them match those of the reference model for a large range of normalized time delays (0 ≤ *f*1*TS* ≤ 4). When the *K* factor increases, the proposed SoS models show an improved approximation of the desired auto-correlation and faster convergence. And then we described the curves of the statistics for the simulation models with different vehicle speed ratios, which indicates that the smaller relative speed difference of two vehicle speeds in VANETs contribute to the better performance of the proposed models. More importantly, Based on our models, we provided more comprehensive performance analysis and comparison compared to existing models. It is observed that the the variances in the cross-correlation for the statistical model and the MEDS model are considerably lower than those of reference model. Meanwhile, For the same time delay *τ*, the statistical model shows better performance and faster convergence than the MEDS model. Hence, the statistical model may be more suitable for IVC fading channels with

The authors would like to thank the Cognitive Radio Sensor Network research group in Electronic Information Engineering of Nanchang University for continuous support and lively discussions. The authors are also grateful to the anonymous reviewers for their helpful

This work has been supported by the National Natural Science Foundation of China (No.60762 005), the Natural Science Foundation of Jiangxi Province for Youth (No.2010GQS0153 and No.2009GQS0070) and the Graduate Student Innovation Foundation of Jiangxi Province

support systems for road safety and transportation efficiency.

with Rician K-factor and Vehicle Speed Ratio in Vehicular Ad Hoc Networks

the fading effect in vehicular wireless network.

a LOS component in VANETs.

**8. Acknowledgments**

comments.

(No.YC10A032).

Fig. 5. Variance of the auto-correlation and cross-correlation function with different *a*

should be like this: smaller relative difference means that the transmitter and the receiver are in a relatively closer static state, so the randomness of channel tends to be smaller. As plotted in Fig. 5d, the variances of the cross-correlation of the proposed models are considerably lower than the reference model.

It should also be mentioned that our simulation results of variance of the correlation when *a* = 0 represent the case of I2V channels, which shows the comprehensiveness of our models and performance analysis as well.
