Distributed rate and power control in DSRC

Jose, Jubin; Li, Chong; Wu, Xinzhou; Lü, Ying; Zhu, K. J.

doi:10.1109/isit.2015.7282971

Cited by 10 publications

(4 citation statements)

References 18 publications

(40 reference statements)

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“…While the majority of conventional DCC algorithms rely on CBR as the criterion for determining control parameters, a single-measurement approach is insufficient due to the myriad factors influencing channel load, which consequently leads to issues such as fairness. In [ 18 ], the authors introduce Rate-OPT and Power-OPT algorithms for dedicated short-range communication (DSRC), demonstrating that their coordinated and alternating application results in enhanced channel utilization and packet transmission rates. This integrated congestion control algorithm optimizes channel load usage by dynamically allocating transmission range and rate in response to vehicle density.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

Tian

Islam

et al. 2023

Sensors

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The accelerated growth of 5G technology has facilitated substantial progress in the realm of vehicle-to-everything (V2X) communications. Consequently, achieving optimal network performance and addressing congestion-related challenges have become paramount. This research proposes a unique hybrid power and rate control management strategy for distributed congestion control (HPR-DCC) focusing on 5G-NR-V2X sidelink communications. The primary objective of this strategy is to enhance network performance while simultaneously preventing congestion. By implementing the HPR-DCC strategy, a more fine-grained and adaptive control over the transmit power and transmission rate can be achieved. This enables efficient control by dynamically adjusting transmission parameters based on the network conditions. This study outlines the system model and methodology used to develop the HPR-DCC algorithm and investigates its characteristics of stability and convergence. Simulation results indicate that the proposed method effectively controls the maximum CBR value at 64% during high congestion scenarios, which leads to a 6% performance improvement over the conventional DCC approach. Furthermore, this approach enhances the signal reception range by 20 m, while maintaining the 90% packet reception ratio (PRR). The proposed HPR-DCC contributes to optimizing the quality and reliability of 5G-NR-V2X sidelink communication and holds great promise for advancing V2X applications in intelligent transportation systems.

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Section: Related Workmentioning

confidence: 99%

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

Tian

Islam

et al. 2023

Sensors

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“…Meanwhile, spectrum sharing and power allocation for D2D-enabled VCN is investigated in [11], where channel uncertainty, maximal sum capacity, and reliability of the V2V links were considered. Alternated and distributed optimization approaches for rate and power control are studied in [12] for utility maximization in DSRC systems.…”

Section: B State Of the Artmentioning

confidence: 99%

Distributed Utility Optimization in Vehicular Communication Systems

Diaz-Ibarra

Campos-Delgado

Gutiérrez

et al. 2020

IEEE Trans. Veh. Technol.

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In this paper, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network. Index Terms-Vehicular communications, transmission power, utility maximization, feedback control. I. INTRODUCTION A. Motivation V EHICULAR communication networks (VCN) are an emerging technology aimed at improving road safety and traffic management [1]-[3]. These networks will enable vehicles to share their driving information with other vehicles, and also with the infrastructure installed along the road in real-time. Two types of messages will be employed to transmit (broadcast) such Manuscript

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“…Nasiriani et al [34] perform similar power control mechanism and combine it with rate control based on channel utilization. Jose et al [35] defines power adaptation as a joint Lagrangian optimization and rate adaptation. These approaches as well as [36] combine power and rate adaptation without their combined operation.…”

Section: Introductionmentioning

confidence: 99%

ECPR: Environment-and context-aware combined power and rate distributed congestion control for vehicular communications

Aygün

Boban

Wyglinski

2016

Computer Communications

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Safety and efficiency applications in vehicular networks rely on the exchange of periodic messages between vehicles. These messages contain position, speed, heading, and other vital information that makes the vehicles aware of their surroundings. The drawback of exchanging periodic cooperative messages is that they generate significant channel load. Decentralized Congestion Control (DCC) algorithms have been proposed to minimize the channel load. However, while the rationale for periodic message exchange is to improve awareness, existing DCC algorithms do not use awareness as a metric for deciding when, at what power, and at what rate the periodic messages need to be sent in order to make sure all vehicles are informed. We propose an environment-and context-aware DCC algorithm combines power and rate control in order to improve cooperative awareness by adapting to both specific propagation environments (e.g., urban intersections, open highways, suburban roads) as well as application requirements (e.g., different target cooperative awareness range). Studying various operational conditions (e.g., speed, direction, and application requirement), ECPR adjusts the transmit power of the messages in order to reach the desired awareness ratio at the target distance while at the same time controlling the channel load using an adaptive rate control algorithm. By performing extensive simulations, * Corresponding author * * M. Boban carried out this work while at NEC Laboratories Europe.

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Distributed rate and power control in DSRC

Cited by 10 publications

References 18 publications

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

Distributed Utility Optimization in Vehicular Communication Systems

ECPR: Environment-and context-aware combined power and rate distributed congestion control for vehicular communications

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