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Mobility-Based Cell and Resource Allocation for Heterogeneous Ultra-Dense Cellular Networks
Author(s) -
Masoud Farokhi,
Alireza Zolghadrasli,
Nader Mokari Yamchi
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.2018.2877695
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
Heterogeneous ultra-dense network (HUDN) is a promising network structure, which increases network efficiency in 4G and 5G networks. However, it faces the new challenges regarding interference and mobility management. To overcome these challenges, joint of resource allocation (RA) and mobility management is necessary, which, to the best of our knowledge, has not been sufficiently investigated. This paper represents a solution to this issue. First, analytical investigation and numerical analysis are carried out to model and justify the behavior of expectation of handover (HO) success rate ( $\mathrm {E}_{R}\{HSR\}$ ) versus coverage probability. This paper provides more insight and tools for mobility-based RA researches and design of the network as well. Then, a new approach of hybrid cell-resource allocation is introduced. It is noteworthy that this is a practical structure that is adaptable to dynamic network changes in parameters, such as traffic distribution, mobility pattern, network topology, and different tiers’ acceptable signal-to-interference-plus-noise ratio. The advantage of this new proposed approach is demonstrated by a numerical analysis. The results are compared with traditional approaches with and without HO priority consideration called hybrid-partial CRA (HP-CRA) and traditional CRA (T-CRA), respectively. The results show a considerable improvement of $\mathrm {E}_{R}\{HSR\}$ about 20% and 80% compared with HP-CRA and T-CRA, respectively, under the loaded situations, while the network sum rate is kept near the optimal solution.

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