Performance Analysis of Dynamic Re-Clustering and Resource Allocation in Ultra Dense Network
Author(s) -
Wenle Bai,
Yaomin Li,
Tong Yao,
Haijun Zhang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2870868
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Coordinated multi-point (CoMP) is a key technology to mitigate inter-cell interference, which can significantly improve the cell edge performance and system throughput. In addition, the choice of the cells within cluster will directly affect the effect of CoMP, and especially, it may cause the increase of the number of dissatisfied users in the system. To minimize dissatisfied users in the ultra-dense network (UDN) application scenario, based on the control-data separation architecture model, a clustering algorithm is studied to improve the SINR and throughout. Then, load balancing is developed and the overall percentage of unsatisfied users are reduced obviously. Furthermore, a dynamic resource allocation scheme is proposed by defining a factor α and applied to optimize the performance of system, which is compared with load balancing under the conditions of a different clustered size and density of users. The experiments prove that the performance of load balancing is more sensitive to the change of clustered size than resource allocation, and the load balancing has overwhelming advantage compared with resource allocation in the dense deployment scenario. However, when the density of users becomes sparser, resource allocation performs better, which gives important meanings for future UDN.
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