Data Freshness Performance Analysis in NOMA-enabled Green Mobile Crowdsensing

Yaoqi Yang; Bangning Zhang; Daoxing Guo; Renhui Xu; Lin Ge; Weizheng Wang; Xiaokang Zhou

doi:10.1109/ICC45041.2023.10278558

Data Freshness Performance Analysis in NOMA-enabled Green Mobile Crowdsensing

Yaoqi Yang, Bangning Zhang, Daoxing Guo^*, Renhui Xu^*, Lin Ge, Weizheng Wang, Xiaokang Zhou

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario. © 2023 IEEE

Original language	English
Title of host publication	ICC 2023 - IEEE International Conference on Communications
Publisher	IEEE
Pages	6132-6137
ISBN (Electronic)	978-1-5386-7462-8
ISBN (Print)	978-1-5386-7463-5
DOIs	https://doi.org/10.1109/ICC45041.2023.10278558
Publication status	Published - 2023
Event	58th IEEE International Conference on Communications (ICC 2023): Sustainable Communications for Renaissance - La Nuvola Convention Center, Rome, Italy Duration: 28 May 2023 → 1 Jun 2023 https://icc2023.ieee-icc.org/

Publication series

Name
ISSN (Electronic)	1938-1883

Conference

Conference	58th IEEE International Conference on Communications (ICC 2023)
Abbreviated title	IEEE ICC 2023
Country/Territory	Italy
City	Rome
Period	28/05/23 → 1/06/23
Internet address	https://icc2023.ieee-icc.org/

Research Keywords

Stochastic Geometry
Age of Information
non-orthogonal multiple access
mobile crowdsensing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICC45041.2023.10278558

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Cite this

@inproceedings{1c8c66981ff34307b99333a13039aebb,

title = "Data Freshness Performance Analysis in NOMA-enabled Green Mobile Crowdsensing",

abstract = "Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario. {\textcopyright} 2023 IEEE",

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author = "Yaoqi Yang and Bangning Zhang and Daoxing Guo and Renhui Xu and Lin Ge and Weizheng Wang and Xiaokang Zhou",

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doi = "10.1109/ICC45041.2023.10278558",

language = "English",

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booktitle = "ICC 2023 - IEEE International Conference on Communications",

address = "United States",

note = "58th IEEE International Conference on Communications (ICC 2023) : Sustainable Communications for Renaissance, IEEE ICC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",

url = "https://icc2023.ieee-icc.org/",

}

TY - GEN

T1 - Data Freshness Performance Analysis in NOMA-enabled Green Mobile Crowdsensing

AU - Yang, Yaoqi

AU - Zhang, Bangning

AU - Guo, Daoxing

AU - Xu, Renhui

AU - Ge, Lin

AU - Wang, Weizheng

AU - Zhou, Xiaokang

PY - 2023

Y1 - 2023

N2 - Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario. © 2023 IEEE

AB - Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario. © 2023 IEEE

KW - Stochastic Geometry

KW - Age of Information

KW - non-orthogonal multiple access

KW - mobile crowdsensing

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M3 - RGC 32 - Refereed conference paper (with host publication)

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BT - ICC 2023 - IEEE International Conference on Communications

PB - IEEE

T2 - 58th IEEE International Conference on Communications (ICC 2023)

Y2 - 28 May 2023 through 1 June 2023

ER -

Data Freshness Performance Analysis in NOMA-enabled Green Mobile Crowdsensing

Abstract

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Research Keywords

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