A Study of LTE-V2X Mode 4 Performances in a Multiapplication Context

Ghodhbane, Chourouk; Kassab, Mohamed; Maaloul, Sassi; Aniss, Hasnaâ; Berbineau, Marion

doi:10.1109/access.2022.3182508

Cited by 13 publications

(6 citation statements)

References 23 publications

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“…However, in a specific case when (π iα = π * iα ) and (s −i = s −i ), the best and opposing strategies lead to a contradiction, as per Equation (17).…”

Section: Action Set and The Players' Strategiesmentioning

confidence: 99%

“…Variations in the number of vehicles, communication range of a UAV, and packet transmission frequency further impact the average end-to-end (E2E) latency and packet delivery ratio (PDR) [16]. A recent work has demonstrated that the parameters of the communication channel and the data traffic influence the LTE-V2X's performance in a realistic multiapplication environment [17].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Fernando,

Gupta

2024

Drones

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The paper studies a game theory model to ensure fairness and improve the communication efficiency in an unmanned aerial vehicle (UAV)-assisted cellular vehicle-to-everything (C-V2X) communication network using Markovian game theory in a federated learning (FL) environment. The UAV and each vehicle in a cluster utilized a strategy-based mechanism to maximize their model completion and transmission probability. We modeled a two-stage zero sum Markovian game with incomplete information to jointly study the utility maximization of the participating vehicles and the UAV in the FL environment. We modeled the aggregating process at the UAV as a mixed strategy game between the UAV and each vehicle. By employing Nash equilibrium, the UAV determined the probability of sufficient updates received from each vehicle. We analyzed and proposed decision-making strategies for several representative interactions involving gross data offloading and federated learning. When multiple vehicles enter a parameter transmission conflict, various strategy combinations are evaluated to decide which vehicles transmit their data to the UAV. The optimal payoff in a transmission window is derived using the Karush–Khun–Tucker (KKT) optimality conditions. We also studied the variation in optimal model parameter transmission probability, average packet delay, UAV transmit power, and the UAV–Vehicle optimal communication probabilities under different conditions.

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“…However, in a specific case when (π iα = π * iα ) and (s −i = s −i ), the best and opposing strategies lead to a contradiction, as per Equation (17).…”

Section: Action Set and The Players' Strategiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Fernando,

Gupta

2024

Drones

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“…Ghodhbane et al [30] emphasized the standardized technology for cooperative intelligent transport systems and the LTE-V2X mode 4, with particular attention to factors pertaining to traffic load, resource allocation, and Quality of Service (QoS). An analysis in comparison with ITS-G5 was also carried out.…”

Section: Literature Reviewmentioning

confidence: 99%

NR Sidelink Performance Evaluation for Enhanced 5G-V2X Services

Tabassum,

Bastos,

Oliveira

et al. 2023

Vehicles

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The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous vehicles, the advancement in radio access technologies that facilitate dependable and low-latency vehicular communications is becoming more significant. This is especially necessary when there are heavy traffic conditions and patterns. We thoroughly examined the New Radio (NR) sidelink’s performance based on 3GPP Releases 15–17 under various vehicle densities, speeds, and distance settings. Thus, by evaluating sidelink’s strengths and drawbacks, we are able to optimize resource allocation to obtain maximum coverage in urban areas. The performance evaluation was conducted on Network Simulator 3 (NS3.34/5G-LENA) utilizing various network metrics such as average packet reception rate, throughput, and latency.

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“…If the entity is present, there is mode 3. If not, there is mode 4 [24,[36][37][38]. Depending on the mode, which is used for the data transmission, the requirement for the latency is in the range between 20-100 ms [39].…”

Section: Transmission Modesmentioning

confidence: 99%

Vehicle-to-Everything Communication

Špitálová¹

2023

Communications

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With an increasing number of vehicles, there is a need for reliable and secure communication between subjects participating in the dynamic traffic environment. This kind of communication is called V2X (Vehicle-to-Everything). It can also contribute to higher level of autonomous driving. The V2X model operation is enabled by use of the newest technologies and standards, defined by 3GPP Organization. In this paper, a review of the V2X communication models, available technologies and standards are studied.

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A Study of LTE-V2X Mode 4 Performances in a Multiapplication Context

Cited by 13 publications

References 23 publications

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

NR Sidelink Performance Evaluation for Enhanced 5G-V2X Services

Vehicle-to-Everything Communication

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