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Coverage and Capacity Optimization Analysis in Heterogeneous Cellular Networks Based on Truncated Function

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Abstract

This paper presents a framework for coverage and capacity optimization (CCO) in HCNs from stochastic geometry theory. Unlike conventional approaches, we propose a concept of effective capacity as the optimization objective, which involves implicit index of coverage in the form of truncation function. The main idea is to model the coverage probability, average rate and joint objective considering noise where the location of base stations are spatially distributed as a Poisson Point Process. Under an adaptive power allocation assumption, we improve iterative approach with percentile level to find an effective increasing direction of transmit power. The simulation shows that the theoretical analysis and optimization objective are feasible and the adjustment of percentile level serves as a flexible solution for CCO.

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Acknowledgments

This work by supported in part by the National Natural Science Foundation of China under Grant 61302081, the State Major Science and Technology Special Projects (Grant No. 2013ZX03003005).

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Authors and Affiliations

  1. Department of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Xiaojuan Wang, Mei Song, Yinglei Teng, Anqi Xing & Deyu Yuan

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  1. Xiaojuan Wang
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  2. Mei Song
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  3. Yinglei Teng
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  5. Deyu Yuan
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Correspondence to Xiaojuan Wang.

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Wang, X., Song, M., Teng, Y. et al. Coverage and Capacity Optimization Analysis in Heterogeneous Cellular Networks Based on Truncated Function. Wireless Pers Commun 89, 385–403 (2016). https://doi.org/10.1007/s11277-016-3271-3

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