DocumentCode :
3753597
Title :
Cloud Assisted Resource Management for Hyper-Dense Small Cell Networks
Author :
Amila Tharaperiya Gamage;Qinghua Shen;Xuemin Shen
Author_Institution :
Dept. of Electr. &
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
Hyper-dense deployment of small cells and reuse of available spectrum resources within a wireless cellular network are two promising techniques that can enhance network capacity to satisfy the ever increasing demand for high volumes of mobile data traffic. With the use of these techniques in a network, the network is prone to severe co-channel interference (CCI), due to short distances between the densely deployed small cells. Therefore, to avoid degradation of the network capacity, it is necessary to manage CCI by jointly allocating resources of the small cells. Further, the resource allocation scheme should minimize the computational burden for low-cost small cell base stations (BSs), be able to adapt to time-varying network load conditions, and reduce signaling overhead in the small cell backhauls with limited capacity. To this end, in this paper we present a resource allocation scheme which operates on two time-scales and utilizes cloud computing to determine resource allocation decisions. The resource allocation decisions are made at the cloud in a slow time-scale, and are further optimized at the BSs in a fast time-scale in order to adapt the decisions to fast varying wireless channel conditions. Achievable network capacity enhancements using the proposed scheme are demonstrated through simulation results.
Keywords :
"Resource management","Cloud computing","Delays","Throughput","Wireless communication","Servers","Macrocell networks"
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2015 IEEE
Type :
conf
DOI :
10.1109/GLOCOM.2015.7417494
Filename :
7417494
Link To Document :
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