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

Institute of Communications Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

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.

Original language	English
Title of host publication	2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509017010
DOIs	https://doi.org/10.1109/VTCFall.2016.7881009
State	Published - 2 Jul 2016
Event	84th IEEE Vehicular Technology Conference, VTC Fall 2016 - Montreal, Canada Duration: 18 Sep 2016 → 21 Sep 2016

Publication series

Name	IEEE Vehicular Technology Conference
Volume	0
ISSN (Print)	1550-2252

Conference

Conference	84th IEEE Vehicular Technology Conference, VTC Fall 2016
Country/Territory	Canada
City	Montreal
Period	18/09/16 → 21/09/16

Keywords

Machine-to-machine communications
Medium access control
Statistical signal estimation
Stochastic processes

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10.1109/VTCFall.2016.7881009

Cite this

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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.",

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Gau, RH & Kuo, FT 2016, Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications. in 2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings., 7881009, IEEE Vehicular Technology Conference, vol. 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

Exploiting spatial and temporal correlations for signal-centric MAC in M2M communications. / Gau, Rung Hung; Kuo, Fu Ta.
2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. 7881009 (IEEE Vehicular Technology Conference; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Kuo, Fu Ta

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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

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M3 - Conference contribution

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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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