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Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks

Junfei Qiu (Coll. of Commun. Eng., PLA Univ. of Sci. & Technol., Nanjing, China ); Guoru Ding (Coll. of Commun. Eng., PLA Univ. of Sci. & Technol., Nanjing, China ); Qihui Wu (Sch. of Eng., Nazarbayev Univ., Astana, Kazakhstan ); Zuping Qian (Technol. Educ. Inst. of Central Greece, Lamia, Greece ); Tsiftsis, Theodoros A. (Nat. Digital Switching Syst. Eng. & Technol. Res. Center, Zhengzhou, China ); Zhiyong Du ( ); Youming Sun ( );
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    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. Specifically, 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 efficiency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks.


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