DSpace Repository

Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks

Show simple item record

dc.contributor.author Qiu, Junfei
dc.contributor.author Ding, Guoru
dc.contributor.author Wu, Qihui
dc.contributor.author Qian, Zuping
dc.contributor.author Tsiftsis, Theodoros A.
dc.contributor.author Du, Zhiyong
dc.contributor.author Sun, Youming
dc.date.accessioned 2017-11-20T03:19:55Z
dc.date.available 2017-11-20T03:19:55Z
dc.date.issued 2016-11-29
dc.identifier.citation Qiu Junfei et al.(>6), 2016(November 29), Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks, IEEE Access , vol.4 ru_RU
dc.identifier.issn 2169-3536
dc.identifier.uri DOI:10.1109/ACCESS.2016.2633434
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/2835
dc.description.abstract This paper considers joint power control and subchannel allocation for co-tier interference mitigation in extremely dense small cell networks, which is formulated as a combinatorial optimization problem. Since it is intractable to obtain the globally optimum assignment policy for existing techniques due to the huge computation and communication overheads in ultra-dense scenario, in this paper, we propose a hierarchical resource allocation framework to achieve a desirable solution. Speci cally, the solution is obtained by dividing the original optimization problem into four stages in partially distributed manner. First, we propose a divide-and-conquer strategy by invoking clustering technique to decompose the dense network into smaller disjoint clusters. Then, within each cluster, one of the small cell access points is elected as a cluster head to carry out intra-cluster subchannel allocation with a low-complexity algorithm. To tackle the issue of inter-cluster interference, we further develop a distributed learning-base coordination mechanism. Moreover, a local power adjustment scheme is also presented to improve the system performance. Numerical results verify the ef ciency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks. ru_RU
dc.language.iso en ru_RU
dc.publisher IEEE Access ru_RU
dc.rights Open Access - the content is available to the general public ru_RU
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject hyper-dense networks ru_RU
dc.subject small cells ru_RU
dc.subject hierarchical resource allocation ru_RU
dc.subject clustering ru_RU
dc.subject Research Subject Categories::TECHNOLOGY::Engineering physics ru_RU
dc.title Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks ru_RU
dc.type Article ru_RU


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Open Access - the content is available to the general public Except where otherwise noted, this item's license is described as Open Access - the content is available to the general public