Sparse message passing based preamble estimation for crowded M2M communications

Zhaoji Zhang; Ying Li; Lei Liu; Huimei Han

doi:10.1109/ICC.2018.8422285

Sparse message passing based preamble estimation for crowded M2M communications

Zhaoji Zhang
, Ying Li^*
, Lei Liu
, Huimei Han

^*Corresponding author for this work

Department of Electrical Engineering

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

1 Citation (Scopus)

Abstract

Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems, a novel sparse message passing (SMP) algorithm is proposed, based on a factor graph on which Bernoulli messages are updated. The SMP enables an accurate estimation on the activity of the devices and the identity of the preamble chosen by each active device. Aided by the estimation, the RB efficiency for the uplink data transmission can be improved, especially among the collided devices. In addition, an analytical tool is derived to analyze the iterative evolution and convergence of the SMP algorithm. Finally, numerical simulations are provided to verify the validity of our analytical results and the significant improvement of the proposed SMP on estimation error rate even when preamble collision occurs.

Original language	English
Title of host publication	2018 IEEE International Conference on Communications (ICC) - Proceedings
Publisher	IEEE
ISBN (Electronic)	978-1-5386-3180-5
DOIs	https://doi.org/10.1109/ICC.2018.8422285
Publication status	Published - May 2018
Event	2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States Duration: 20 May 2018 → 24 May 2018

Conference

Conference	2018 IEEE International Conference on Communications, ICC 2018
Place	United States
City	Kansas City
Period	20/05/18 → 24/05/18

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

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@inproceedings{34b841e0ed334801a3a059ccb8ee85da,

title = "Sparse message passing based preamble estimation for crowded M2M communications",

abstract = "Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems, a novel sparse message passing (SMP) algorithm is proposed, based on a factor graph on which Bernoulli messages are updated. The SMP enables an accurate estimation on the activity of the devices and the identity of the preamble chosen by each active device. Aided by the estimation, the RB efficiency for the uplink data transmission can be improved, especially among the collided devices. In addition, an analytical tool is derived to analyze the iterative evolution and convergence of the SMP algorithm. Finally, numerical simulations are provided to verify the validity of our analytical results and the significant improvement of the proposed SMP on estimation error rate even when preamble collision occurs.",

author = "Zhaoji Zhang and Ying Li and Lei Liu and Huimei Han",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).; 2018 IEEE International Conference on Communications, ICC 2018 ; Conference date: 20-05-2018 Through 24-05-2018",

year = "2018",

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language = "English",

booktitle = "2018 IEEE International Conference on Communications (ICC) - Proceedings",

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Sparse message passing based preamble estimation for crowded M2M communications. / Zhang, Zhaoji; Li, Ying; Liu, Lei et al.
2018 IEEE International Conference on Communications (ICC) - Proceedings. IEEE, 2018. 8422285.

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

TY - GEN

T1 - Sparse message passing based preamble estimation for crowded M2M communications

AU - Zhang, Zhaoji

AU - Li, Ying

AU - Liu, Lei

AU - Han, Huimei

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2018/5

Y1 - 2018/5

N2 - Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems, a novel sparse message passing (SMP) algorithm is proposed, based on a factor graph on which Bernoulli messages are updated. The SMP enables an accurate estimation on the activity of the devices and the identity of the preamble chosen by each active device. Aided by the estimation, the RB efficiency for the uplink data transmission can be improved, especially among the collided devices. In addition, an analytical tool is derived to analyze the iterative evolution and convergence of the SMP algorithm. Finally, numerical simulations are provided to verify the validity of our analytical results and the significant improvement of the proposed SMP on estimation error rate even when preamble collision occurs.

AB - Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems, a novel sparse message passing (SMP) algorithm is proposed, based on a factor graph on which Bernoulli messages are updated. The SMP enables an accurate estimation on the activity of the devices and the identity of the preamble chosen by each active device. Aided by the estimation, the RB efficiency for the uplink data transmission can be improved, especially among the collided devices. In addition, an analytical tool is derived to analyze the iterative evolution and convergence of the SMP algorithm. Finally, numerical simulations are provided to verify the validity of our analytical results and the significant improvement of the proposed SMP on estimation error rate even when preamble collision occurs.

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DO - 10.1109/ICC.2018.8422285

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

BT - 2018 IEEE International Conference on Communications (ICC) - Proceedings

PB - IEEE

T2 - 2018 IEEE International Conference on Communications, ICC 2018

Y2 - 20 May 2018 through 24 May 2018

ER -

Sparse message passing based preamble estimation for crowded M2M communications

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