Name
Title | ||
|---|---|---|
A Computationally Efficient Adaptive Resource Allocation Scheme for M2M Communications |
Abstract | ||
|---|---|---|
Motivated by improving the number of successful access for machine-to-machine (M2M) communications, and realizing resource allocation for any number of active M2M UEs with less computation, a computationally efficient adaptive resource allocation scheme is given in this paper. eNB first learns the resource allocation for few active M2M UEs, which is adaptively changed with the number of uplink resource blocks. Then the resource allocation for other M2M UEs is derived from those active M2M UEs. In addition, the access barring scheme is incorporated to improve the number of successful access. Experimental simulations demonstrate our scheme can significantly improve the number of successful access and reduce resource allocation computation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/VTCFall.2016.7880847 | 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall) |
Keywords | Field | DocType |
access barring scheme,uplink resource blocks,active M2M UE,machine-to-machine communications,M2M communications,adaptive resource allocation scheme | Resource management,Computer science,Computer network,Resource allocation,Telecommunications link,Computation,Distributed computing | Conference |
ISSN | ISBN | Citations |
2577-2465 | 978-1-5090-1702-7 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yali Wu | 1 | 0 | 0.68 |
| Ningbo Zhang | 2 | 91 | 13.95 |
| Guixia Kang | 3 | 106 | 36.59 |
| Peizhi Liu | 4 | 0 | 0.68 |