Predictive resource allocation in the LTE uplink for event based M2M applications

Brown, J; Khan, JY

Predictive resource allocation in the LTE uplink for event based M2M applications

Brown, J

Khan, JY

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Publication Type:: Conference Proceeding
Citation:: 2013 IEEE International Conference on Communications Workshops, ICC 2013, 2013, pp. 95 - 100
Issue Date:: 2013-12-27

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Field	Value	Language
dc.contributor.author	Brown, J https://orcid.org/0000-0002-0698-5758	en_US
dc.contributor.author	Khan, JY	en_US
dc.date.issued	2013-12-27	en_US
dc.identifier.citation	2013 IEEE International Conference on Communications Workshops, ICC 2013, 2013, pp. 95 - 100	en_US
dc.identifier.isbn	9781467357531	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120885
dc.description.abstract	For certain event based M2M applications, it is possible to predict when devices will or may need to send data on the LTE uplink. For example, in a wireless sensor network, the fact that one sensor has triggered may increase the probability that other sensors in the vicinity may also trigger in quick succession. The existing reactive LTE uplink access protocol, in which a device with pending data sends a scheduling request to the eNodeB at its next scheduled opportunity, and the eNodeB responds with an uplink grant, can lead to high latencies. This is particularly the case when the system utilizes a high scheduling request period (of up to 80ms) to support a large number of devices in a cell, which is characteristic of M2M deployments. In this paper, we introduce, analyze and simulate a new predictive/proactive resource allocation scheme for the LTE uplink for use with event based M2M applications. In this scheme, when one device in a group sends a scheduling request, the eNodeB identifies neighbor devices in the same group which may benefit from a predictive resource allocation in lieu of waiting for those neighbors to send a scheduling request at their next scheduled opportunity. We demonstrate how the minimum uplink latency can be reduced from 6ms to 5ms and how the mean uplink latency can be reduced by greater than 50% (in certain scenarios) using this method. © 2013 IEEE.	en_US
dc.relation.ispartof	2013 IEEE International Conference on Communications Workshops, ICC 2013	en_US
dc.relation.isbasedon	10.1109/ICCW.2013.6649208	en_US
dc.title	Predictive resource allocation in the LTE uplink for event based M2M applications	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

For certain event based M2M applications, it is possible to predict when devices will or may need to send data on the LTE uplink. For example, in a wireless sensor network, the fact that one sensor has triggered may increase the probability that other sensors in the vicinity may also trigger in quick succession. The existing reactive LTE uplink access protocol, in which a device with pending data sends a scheduling request to the eNodeB at its next scheduled opportunity, and the eNodeB responds with an uplink grant, can lead to high latencies. This is particularly the case when the system utilizes a high scheduling request period (of up to 80ms) to support a large number of devices in a cell, which is characteristic of M2M deployments. In this paper, we introduce, analyze and simulate a new predictive/proactive resource allocation scheme for the LTE uplink for use with event based M2M applications. In this scheme, when one device in a group sends a scheduling request, the eNodeB identifies neighbor devices in the same group which may benefit from a predictive resource allocation in lieu of waiting for those neighbors to send a scheduling request at their next scheduled opportunity. We demonstrate how the minimum uplink latency can be reduced from 6ms to 5ms and how the mean uplink latency can be reduced by greater than 50% (in certain scenarios) using this method. © 2013 IEEE.

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