Name
Title | ||
|---|---|---|
Proactive Resource Scheduling with Time and Frequency Domain Coordination in Heterogeneous Networks |
Abstract | ||
|---|---|---|
User and network behavior prediction by big data makes the traditional heterogeneous networks (HetNets) a learning and knowledgeable network. However, how much and under what conditions that prediction can benefit the upcoming 5G HetNets have not been comprehensively studied. Furthermore, how to use the quantified conditions to guide network operation is still under investigation. In term of resource allocation, this paper proposes a mobility-based proactive resource scheduling (MPRS) strategy and explores the above questions. Taking advantage of predicted information of user mobility, network residual frequency bandwidth and channel gains, MPRS aims at a) minimizing service delay and enhancing successful scheduling probability, and b) adapting to users' mobility intensity together with quality of service requirements, in long term. Comparing with the reactive strategy, fair scheduling (FS), simulation results show that with accurate prediction, MPRS achieves about 20% performance gain. And when the proportion of average residual frequency bandwidth is less than 50%, FS can be performed instead for it achieves similar performance with MPRS and its computational simplicity. With imperfect prediction, the tolerable upper bound of prediction error becomes tighter as the residual frequency bandwidth decreases. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/PIMRC.2018.8580802 | 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) |
Keywords | Field | DocType |
network behavior prediction,HetNets,knowledgeable network,quantified conditions,network operation,resource allocation,mobility-based proactive resource scheduling strategy,MPRS,user mobility,network residual frequency bandwidth,channel gains,service requirements,reactive strategy,fair scheduling,average residual frequency bandwidth,imperfect prediction,prediction error,Big Data,heterogeneous networks,service delay minimization,performance gain,scheduling probability,time and frequency domain coordination | Frequency domain,Residual,Computer science,Scheduling (computing),Quality of service,Computer network,Communication channel,Bandwidth (signal processing),Resource allocation,Heterogeneous network | Conference |
ISSN | ISBN | Citations |
2166-9570 | 978-1-5386-6010-2 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Li | 1 | 0 | 0.68 |
| Xing Zhang | 2 | 603 | 41.16 |
| Shuo Wang | 3 | 18 | 1.82 |
| Weiwen Yi | 4 | 0 | 0.68 |