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Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device

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Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device. / Guo, Tianhao; Schormans, John; Xu, Lexi et al.
In: IEEE Access, Vol. 8, 10.02.2020, p. 31562 - 31573.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Guo T, Schormans J, Xu L, Wu J, Cao Y. Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device. IEEE Access. 2020 Feb 10;8:31562 - 31573. doi: 10.1109/ACCESS.2020.2972938

Author

Guo, Tianhao ; Schormans, John ; Xu, Lexi et al. / Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device. In: IEEE Access. 2020 ; Vol. 8. pp. 31562 - 31573.

Bibtex

@article{2076ed3533654e1ca0c847059f918553,
title = "Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device",
abstract = "Device-to-Device (D2D) communication is a way to treat the User Equipments (UEs) not as terminals, but as a part of the network (helpers) for service provisioning. We propose a generic framework, namely Proximity as a Service (PaaS), formulate the helper selection problem, and design and prove a heuristic helper selection policy, ContAct based Proximity (CAP), which increases the service connectivity and continuity. Design Of Experiment (DOE) is a statistical methodology that rigorously designs and conducts an experiment, and maximizes the information obtained from that experiment. We apply DOE to explore the relationship (analytic expression) between four inputs (factors) and four metrics (responses). Since different factors have different regression levels, a unified four level full factorial experiment and cubic multiple regression analysis have been carried out. Multiple regression equations are provided to estimate the different contributions and the interactions between factors. Results show that transmission range and user density are dominant and monotonically increasing, but transmission range should be restricted because of interference and energy-efficiency. After obtaining the explicit close form expressions between factors and responses, optimal values of key factors are derived. A methodology (the e-constraint method) to solve the multiple-objective optimization problem has been provided and a Pareto-Optimal set of factors has been found through iteration. The fluctuation of the iterations is small and a specific solution can be chosen based on the particular scenarios (city center or countryside with different user density). The methodology of optimization informs the design rules of the operator, helping to find the optimal networking solution.",
author = "Tianhao Guo and John Schormans and Lexi Xu and Jinze Wu and Yue Cao",
note = "{\textcopyright}2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ",
year = "2020",
month = feb,
day = "10",
doi = "10.1109/ACCESS.2020.2972938",
language = "English",
volume = "8",
pages = "31562 -- 31573",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Proximity as a Service for the Use Case of Access Enhancement via Cellular Network-Assisted Mobile Device-to-Device

AU - Guo, Tianhao

AU - Schormans, John

AU - Xu, Lexi

AU - Wu, Jinze

AU - Cao, Yue

N1 - ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2020/2/10

Y1 - 2020/2/10

N2 - Device-to-Device (D2D) communication is a way to treat the User Equipments (UEs) not as terminals, but as a part of the network (helpers) for service provisioning. We propose a generic framework, namely Proximity as a Service (PaaS), formulate the helper selection problem, and design and prove a heuristic helper selection policy, ContAct based Proximity (CAP), which increases the service connectivity and continuity. Design Of Experiment (DOE) is a statistical methodology that rigorously designs and conducts an experiment, and maximizes the information obtained from that experiment. We apply DOE to explore the relationship (analytic expression) between four inputs (factors) and four metrics (responses). Since different factors have different regression levels, a unified four level full factorial experiment and cubic multiple regression analysis have been carried out. Multiple regression equations are provided to estimate the different contributions and the interactions between factors. Results show that transmission range and user density are dominant and monotonically increasing, but transmission range should be restricted because of interference and energy-efficiency. After obtaining the explicit close form expressions between factors and responses, optimal values of key factors are derived. A methodology (the e-constraint method) to solve the multiple-objective optimization problem has been provided and a Pareto-Optimal set of factors has been found through iteration. The fluctuation of the iterations is small and a specific solution can be chosen based on the particular scenarios (city center or countryside with different user density). The methodology of optimization informs the design rules of the operator, helping to find the optimal networking solution.

AB - Device-to-Device (D2D) communication is a way to treat the User Equipments (UEs) not as terminals, but as a part of the network (helpers) for service provisioning. We propose a generic framework, namely Proximity as a Service (PaaS), formulate the helper selection problem, and design and prove a heuristic helper selection policy, ContAct based Proximity (CAP), which increases the service connectivity and continuity. Design Of Experiment (DOE) is a statistical methodology that rigorously designs and conducts an experiment, and maximizes the information obtained from that experiment. We apply DOE to explore the relationship (analytic expression) between four inputs (factors) and four metrics (responses). Since different factors have different regression levels, a unified four level full factorial experiment and cubic multiple regression analysis have been carried out. Multiple regression equations are provided to estimate the different contributions and the interactions between factors. Results show that transmission range and user density are dominant and monotonically increasing, but transmission range should be restricted because of interference and energy-efficiency. After obtaining the explicit close form expressions between factors and responses, optimal values of key factors are derived. A methodology (the e-constraint method) to solve the multiple-objective optimization problem has been provided and a Pareto-Optimal set of factors has been found through iteration. The fluctuation of the iterations is small and a specific solution can be chosen based on the particular scenarios (city center or countryside with different user density). The methodology of optimization informs the design rules of the operator, helping to find the optimal networking solution.

U2 - 10.1109/ACCESS.2020.2972938

DO - 10.1109/ACCESS.2020.2972938

M3 - Journal article

VL - 8

SP - 31562

EP - 31573

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -