Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications

Rung Hung Gau; Fu Ta Kuo

doi:10.1109/VTCFall.2016.7881009

Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications

Rung Hung Gau, Fu Ta Kuo

電信工程研究所

研究成果: Conference contribution › 同行評審

1 引文斯高帕斯（Scopus）

摘要

In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-tomachine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space-time predictive polling algorithm. In addition, we derive the a-priori prediction error that is essential for making an optimal polling decision. Simulation results show that the proposed space-time predictive polling algorithm could significantly outperform algorithms that use only temporal correlation.

原文	English
主出版物標題	2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9781509017010
DOIs	https://doi.org/10.1109/VTCFall.2016.7881009
出版狀態	Published - 2 7月 2016
事件	84th IEEE Vehicular Technology Conference, VTC Fall 2016 - Montreal, Canada 持續時間: 18 9月 2016 → 21 9月 2016

出版系列

名字	IEEE Vehicular Technology Conference
卷	0
ISSN（列印）	1550-2252

Conference

Conference	84th IEEE Vehicular Technology Conference, VTC Fall 2016
國家/地區	Canada
城市	Montreal
期間	18/09/16 → 21/09/16

存取文件

10.1109/VTCFall.2016.7881009

其它文件與鏈接

Link to publication in Scopus

引用此

@inproceedings{fa8c8aacd9a4427a9a43c3bfaf31890c,

title = "Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications",

abstract = "In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-tomachine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space-time predictive polling algorithm. In addition, we derive the a-priori prediction error that is essential for making an optimal polling decision. Simulation results show that the proposed space-time predictive polling algorithm could significantly outperform algorithms that use only temporal correlation.",

keywords = "Machine-to-machine communications, Medium access control, Statistical signal estimation, Stochastic processes",

author = "Gau, {Rung Hung} and Kuo, {Fu Ta}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 84th IEEE Vehicular Technology Conference, VTC Fall 2016 ; Conference date: 18-09-2016 Through 21-09-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/VTCFall.2016.7881009",

language = "English",

series = "IEEE Vehicular Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings",

address = "United States",

}

Gau, RH & Kuo, FT 2016, Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications. 於 2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings., 7881009, IEEE Vehicular Technology Conference, 卷 0, Institute of Electrical and Electronics Engineers Inc., 84th IEEE Vehicular Technology Conference, VTC Fall 2016, Montreal, Canada, 18/09/16. https://doi.org/10.1109/VTCFall.2016.7881009

TY - GEN

T1 - Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications

AU - Gau, Rung Hung

AU - Kuo, Fu Ta

PY - 2016/7/2

Y1 - 2016/7/2

N2 - In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-tomachine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space-time predictive polling algorithm. In addition, we derive the a-priori prediction error that is essential for making an optimal polling decision. Simulation results show that the proposed space-time predictive polling algorithm could significantly outperform algorithms that use only temporal correlation.

AB - In this paper, we propose a signal-centric medium access control scheme that simultaneously exploits spatial and temporal correlations among sensing results for machine-tomachine communications. To model sensing results with spatial and temporal correlations, we propose using a vector autoregressive process. To minimize the overall prediction error, we propose using the space-time predictive polling algorithm. In addition, we derive the a-priori prediction error that is essential for making an optimal polling decision. Simulation results show that the proposed space-time predictive polling algorithm could significantly outperform algorithms that use only temporal correlation.

KW - Machine-to-machine communications

KW - Medium access control

KW - Statistical signal estimation

KW - Stochastic processes

UR - http://www.scopus.com/inward/record.url?scp=85016973264&partnerID=8YFLogxK

U2 - 10.1109/VTCFall.2016.7881009

DO - 10.1109/VTCFall.2016.7881009

M3 - Conference contribution

AN - SCOPUS:85016973264

T3 - IEEE Vehicular Technology Conference

BT - 2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 84th IEEE Vehicular Technology Conference, VTC Fall 2016

Y2 - 18 September 2016 through 21 September 2016

ER -

Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications

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Conference

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