Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks
| 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.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.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.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 |