Predictive allocation of resources in the LTE uplink based on maximum likelihood estimation of event propagation characteristics for M2M applications
Paper
Brown, Jason and Khan, Jamil Y. 2015. "Predictive allocation of resources in the LTE uplink based on maximum likelihood estimation of event propagation characteristics for M2M applications
." IEEE Global Communications Conference (GLOBECOM 2014). Austin, United States 08 - 12 Dec 2014 United States. https://doi.org/10.1109/GLOCOM.2014.7037592
| Paper/Presentation Title | Predictive allocation of resources in the LTE uplink based on maximum likelihood estimation of event propagation characteristics for M2M applications |
|---|---|
| Presentation Type | Paper |
| Authors | Brown, Jason and Khan, Jamil Y |
| Journal or Proceedings Title | Proceedings of the IEEE Global Communications Conference (GLOBECOM 2014) |
| Journal Citation | pp. 4965-4970 |
| Number of Pages | 6 |
| Year | 2015 |
| Place of Publication | United States |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/GLOCOM.2014.7037592 |
| Web Address (URL) of Paper | https://ieeexplore.ieee.org/abstract/document/7037592 |
| Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/7008954/proceeding |
| Conference/Event | IEEE Global Communications Conference (GLOBECOM 2014) |
| Event Details | IEEE Global Communications Conference (GLOBECOM 2014) Parent IEEE Global Telecommunications Conference Delivery In person Event Date 08 to end of 12 Dec 2014 Event Location Austin, United States |
| Abstract | We propose a predictive resource allocation scheme for the LTE uplink based upon Maximum Likelihood Estimation of event propagation characteristics for M2M/Smart Grid applications. The LTE eNodeB estimates the inter-sensor propagation time of a disturbance using the pattern and timing of received Scheduling Requests (SRs) from sensors and then proceeds to predict the time at which the disturbance will reach downstream sensors, facilitating predictive uplink grants for these sensors in order to reduce the mean latency of their uplink data packets by up to 50% (according to a performance analysis) compared to the existing standard reactive LTE uplink resource allocation scheme. A further benefit is that when a predictive resource allocation is successful, the sensor does not need to send an SR, thereby freeing up uplink resources which can be critical with M2M communications. We consider various transition strategies from the estimation to prediction phases which reflect the compromise between estimation speed and accuracy, and also examine the concept of early and late prediction. |
| Keywords | LTE; M2M; Smart Grid; predictive scheduling; proactive scheduling; OPNET |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 400902. Digital electronic devices |
| Public Notes | The accessible file is the accepted version of the paper. Please refer to the URL for the published version. |
| Byline Affiliations | University of Newcastle |
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