Stochastic Geometry Modeling of Cellular V2X Communication Over Shared Channels

Sial, Muhammad Nadeem; Deng, Yansha; Ahmed, Junaid; Nallanathan, Arumugam; Dohler, Mischa

doi:10.1109/tvt.2019.2945481

Cited by 64 publications

(38 citation statements)

References 39 publications

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“…Recently, there have been a few works in which cellular-assisted vehicular networks were considered [22]- [24]. A comprehensive coverage analysis for two different types of users (planar and vehicular users) was provided in [22], where the locations of transmitting vehicular nodes were modeled by the Cox process and the locations of cellular base stations were modeled by 2D PPP.…”

Section: A Related Workmentioning

confidence: 99%

“…A comprehensive coverage analysis for two different types of users (planar and vehicular users) was provided in [22], where the locations of transmitting vehicular nodes were modeled by the Cox process and the locations of cellular base stations were modeled by 2D PPP. In [24], the authors have attempted to derive the uplink coverage probability for C-V2X communication. However, the effects of shadowing were ignored in these works because of the technical complications arising from the doubly stochastic nature of this Cox process.…”

Section: A Related Workmentioning

confidence: 99%

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Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication

Chetlur

Dhillon

2020

IEEE Trans. Wireless Commun.

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In this paper, we present the downlink coverage and rate analysis of a cellular vehicle-to-everything (C-V2X) communication network where the locations of vehicular nodes and road side units (RSUs) are modeled as Cox processes driven by a Poisson line process (PLP) and the locations of cellular macro base stations (MBSs) are modeled as a 2D Poisson point process (PPP). Assuming a fixed selection bias and maximum average received power based association, we compute the probability with which a typical receiver, an arbitrarily chosen receiving node, connects to a vehicular node or an RSU and a cellular MBS. For this setup, we derive the signal-to-interference ratio (SIR)-based coverage probability of the typical receiver. One of the key challenges in the computation of coverage probability stems from the inclusion of shadowing effects. As the standard procedure of interpreting the shadowing effects as random displacement of the location of nodes is not directly applicable to the Cox process, we propose an approximation of the spatial model inspired by the asymptotic behavior of the Cox process. Using this asymptotic characterization, we derive the coverage probability in terms of the Laplace transform of interference power distribution. Further, we compute the downlink rate coverage of the typical receiver by characterizing the load on the serving vehicular nodes or RSUs and serving MBSs. We also provide several key design insights by studying the trends in the coverage probability and rate coverage as a function of network parameters. We observe that the improvement in rate coverage obtained by increasing the density of MBSs can be equivalently achieved by tuning the selection bias appropriately without the need to deploy additional MBSs.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication

Chetlur

Dhillon

2020

IEEE Trans. Wireless Commun.

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“…However, integrating such sophisticated resource allocation schemes with geometric analysis over large vehicular networks is challenging. For ease of analysis, most of the existing works considered the simple random channel access for different applications in C-V2X communications [11], [12], [19]. Specifically, [11] presented the stochastic geometric analysis of maximumpower-based C-V2X networks, in which a vehicle receives information from either the nearest vehicle or the nearest eNodeB, based on the received power.…”

Section: Related Workmentioning

confidence: 99%

“…Specifically, [11] presented the stochastic geometric analysis of maximumpower-based C-V2X networks, in which a vehicle receives information from either the nearest vehicle or the nearest eNodeB, based on the received power. Reference [19] analyzed the uplink performance of C-V2X networks where the vehicles can deliver their information via eNodeBs or directly with the nearby vehicles via the sidelinks, based on the received power and bias factors. The coexistence of conventional planar base stations (BSs) and vehicular BSs, which are located on roadside, was considered in [12].…”

Section: Related Workmentioning

confidence: 99%

Cellular-V2X Communications With Weighted-Power-Based Mode Selection

Zeng

Guan

et al. 2020

IEEE Open J. Commun. Soc.

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Cellular-assisted vehicular-to-everything (C-V2X) communication is a promising technology to enhance the road safety and support various infortainment services in future vehicular networks. However, the integration of vehicular communication with the conventional cellular network faces many new design challenges, as vehicles typically use different spectrum band (5.9 GHz) from the cellular systems, and they usually follow different distributions and have more stringent reliability and latency requirements, as compared with the conventional cellular users. In this paper, we study C-V2X communication where the V2X resource pool is managed by the eNodeBs and reused in different cells, with the cells divided according to the Voronoi tessellation of the eNodeBs. We investigate three connection modes for a vehicle to receive safety/entertainment information, namely, from its associated eNodeB, from a neighboring vehicle on the same road, or from a neighboring vehicle on a different road. We propose a weighted-power-based mode selection scheme which offers great flexibility to balance the load of the cellular network and improve the coverage probability. By using stochastic geometry, we derive the analytical expressions for the mode selection and coverage probabilities, which are validated by extensive simulations. Furthermore, by optimizing the weighting factors, the proposed mode selection scheme leads to significantly better performance than the conventional distance-based and maximum-power-based mode selection schemes.

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“…In [8], the authors derived the coverage probability of a typical receiver in vehicular network, which roadways are modeled by Poisson line process (PLP) and the vehicles are modeled by 1D PPP. In [9], the authors proposed a tractable framework of performance analysis of CV2X network over shared cellular and V2V uplink channels and obtained the closed-form expressions for success probability in direct mode and network mode. In [10], the authors analyzed the characteristics of Poisson line Cox point process, which is helpful for network modeling in Internet of Vehicles (IoV).…”

Section: Introductionmentioning

confidence: 99%

Success Probability Analysis of C-V2X Communications on Irregular Manhattan Grids

Pan

2020

Wireless Communications and Mobile Computing

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To overcome the shortcomings of Dedicated Short Range Communications (DSRC), cellular vehicle-to-everything (C-V2X) communications have been proposed recently, which has a variety of advantages over traditional DSRC, including longer communication range, broader coverage, greater reliability, and smooth evolution path towards 5G. In this paper, we consider an LTE-based C-V2X communications network in irregular Manhattan grids. We model the macrobase stations (MBSs) as a 2D Poisson point process (PPP) and model the roads as a Manhattan Poisson line process (MPLP), with the roadside units (RSUs) modeled as a 1D PPP on each road. As an enhancement architecture to DSRC, C-V2X communications include vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, vehicle-to-pedestrian (V2P) communication, and vehicle-to-network (V2N) communication. Since the spectrum for PC5 interface in 5.9 GHz is quite limited, cellular networks could share some channels to V2I links to improve spectral efficiency. Thus, according to Maximum Power-based Scheme, we adopt the stochastic geometry approach to compute the signal-to-interference ratio- (SIR-) based success probability of a typical vehicle that connects to an RSU or an MBS and the area spectral efficiency of the whole network over shared V2I and V2N downlink channels. In addition, we study the asymptotic characteristics of success probability and provide some design insights according to the impact of several key parameters on success probability.

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Stochastic Geometry Modeling of Cellular V2X Communication Over Shared Channels

Cited by 64 publications

References 39 publications

Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication

Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication

Cellular-V2X Communications With Weighted-Power-Based Mode Selection

Success Probability Analysis of C-V2X Communications on Irregular Manhattan Grids

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