4.4 Article

Analysis of coverage-oriented small base station deployment in heterogeneous cellular networks

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PHYSICAL COMMUNICATION
卷 38, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.phycom.2019.100908

关键词

Heterogeneous cellular networks; Poisson point process; Poisson hole process; Stienen's model; Coverage probability; Reverse frequency allocation

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In heterogeneous cellular networks (HetNets), dense small base station deployment (SBSD) offers a scalable and low-cost mechanism to meet the fifth generation (5G) needs of ubiquitous coverage and high throughput. However, due to high transmit power of macro base station (MBS), small base station (SBS) users experience severe MBS interference (MBS-I), and additionally, SBS coverage is significantly reduced when it is located near MBS. Furthermore, MBS edge users (MBS-EUs) experience signal-to-interference ratio (SIR) degradation due to their distant locations. To overcome such limitations, we propose Stienen's cell based coverage-oriented SBS deployment (CO-SBSD) model. According to Stienen's model, SBSD is avoided near MBS due to strong SIR reception from MBS and limited SBS coverage. However, in MBS edge area, SBSD enhances MBS-EUs coverage. Due to locations and density dependencies, performance characterization under Stienen's model remains a challenging task as compared with the traditional Poisson point process (PPP) based models. Nevertheless, we demonstrate that the performance can be approximated in a tractable manner. Furthermore, we use spectrally efficient and effective interference abating scheme known as reverse frequency allocation (RFA) in conjunction with CO-SBSD, to mitigate MBS-I. Based on stochastic geometry framework, expressions for coverage probabilities are derived. The proposed CO-SBSD results in enhanced coverage performance as opposed to uniform-SBSD model. Moreover, RFA compliment the network performance gain by abating interference. Analytical and simulation results show that the proposed CO-SBSD, using Stienen's model along with RFA employment, outperforms all other methods. (C) 2019 Elsevier B.V. All rights reserved.

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