Configuration of the C-V2X Mode 4 Sidelink PC5 Interface for Vehicular Communication

Molina-Masegosa, Rafael; Gozálvez, Javier; Sepulcre, Miguel

doi:10.1109/msn.2018.00014

Cited by 77 publications

(55 citation statements)

References 6 publications

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“…In this work we are aiming to provide a new pointof-view, compared to the existing studies which study the performance of C-V2X communication. These works mainly evaluate the performance [10], [15], [22] and scalability [14] of V2X systems in terms of network-level key performance indicators (KPIs), e.g., packet error rate, inter-packet gap, network throughput, and information age. However, in the context of vehicular safety applications we are specifically interested to investigate how fast the nodes are able to adapt to a dynamic environment and how reliable is the communication with vehicles in their close proximity.…”

Section: Analysis and Resultsmentioning

confidence: 99%

Spatio-Temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networks

Toghi

Saifuddin

Mughal

et al. 2019

2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS)

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Cellular Vehicle-to-everything (C-V2X) communication is a major V2X solution proposed and developed by the 3rd Generation Partnership Project (3GPP). Our previous work has studied scalability aspects of C-V2X and demonstrated its potential for accommodating large numbers of vehicles in dense vehicular scenarios. However, existing studies in the scientific literature mostly have a network-level approach to the problem and do not assess the temporal and spatial dynamics of C-V2X networks in heavy network load situations. In this work we shed light on the spatio-temporal characteristics of these networks and investigate the effectiveness of the congestion control algorithm in dense vehicular ad-hoc networks (VANETs) in terms of settling time, stability, and reliability to be employed for the purpose of safety-critical vehicular applications, where latency plays a major role.

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Section: Analysis and Resultsmentioning

confidence: 99%

Spatio-Temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networks

Toghi

Saifuddin

Mughal

et al. 2019

2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS)

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“…The algorithm presents several parameters, although it has been shown in [22,23] that its performance is mostly determined by the setting of p k . The choice of p k in most scenarios leads to a trade-off between reliability and latency: on the one hand, a low value makes reservations changing often and thus the sensing procedure fail to correctly estimate the occupancy in the next future; on the other, a high value makes possible incorrect selections to last for long intervals, causing longer bursts of errors.…”

Section: Sidelink Lte-v2xmentioning

confidence: 99%

Survey and Perspectives of Vehicular Wi-Fi versus Sidelink Cellular-V2X in the 5G Era

et al. 2019

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The revolution of cooperative connected and automated vehicles is about to begin and a key milestone is the introduction of short range wireless communications between cars. Given the tremendous expected market growth, two different technologies have been standardized by international companies and consortia, namely IEEE 802.11p, out for nearly a decade, and short range cellular-vehicle-to-anything (C-V2X), of recent definition. In both cases, evolutions are under discussion. The former is only decentralized and based on a sensing before transmitting access, while the latter is based on orthogonal resources that can be also managed by an infrastructure. Although studies have been conducted to highlight advantages and drawbacks of both, doubts still remain. In this work, with a reference to the literature and the aid of large scale simulations in realistic urban and highway scenarios, we provide an insight in such a comparison, also trying to isolate the contribution of the physical and medium access control layers.

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“…As a result, (40) needs to be modified by removing p LF in order to compute the probability that v i interferes v t when v t is in random mode and transmits a LF packet:   The probability of packet loss due to collisions (δ COL ) is then computed with (22) and (23)-(41). Finally, the PDR is computed using (10) where δ HD , δ SEN , δ PRO and δ COL are obtained from (12), (16), (17) and (22), respectively.…”

Section: D1 Probability That Interference Is Higher Than Thresholdmentioning

confidence: 99%

Geo-Based Scheduling for C-V2X Networks

Molina-Masegosa

Sepulcre

Gozálvez

2019

IEEE Trans. Veh. Technol.

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Abstract-Cellular Vehicle-to-Everything (C-V2X) networks can operate without cellular infrastructure support. Vehicles can autonomously select their radio resources using the sensing-based Semi-Persistent Scheduling (SPS) algorithm specified by the Third Generation Partnership Project (3GPP). The sensing nature of the SPS scheme makes C-V2X communications prone to the wellknown hidden-terminal problem. To address this problem, this paper proposes a novel geo-based scheduling scheme that allows vehicles to autonomously select their radio resources based on the location and ordering of neighboring vehicles on the road. The proposed scheme results in an implicit resource selection coordination between vehicles (even with those outside the sensing range) that reduces packet collisions. This paper evaluates analytically and through simulations the proposed scheduling scheme. The obtained results demonstrate that it reduces packet collisions and significantly increases the C-V2X performance compared to when using the sensing-based SPS scheme. -C-V2X, V2X, 5G V2X, LTE-V, scheduling, PC5, sidelink, V2V, hidden-terminal, radio resource management. Index Terms

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Configuration of the C-V2X Mode 4 Sidelink PC5 Interface for Vehicular Communication

Cited by 77 publications

References 6 publications

Spatio-Temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networks

Spatio-Temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networks

Survey and Perspectives of Vehicular Wi-Fi versus Sidelink Cellular-V2X in the 5G Era

Geo-Based Scheduling for C-V2X Networks

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