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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2015.4
- 수록면
- 89 - 101 (13page)
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초록· 키워드
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Next generation wireless networks are expected to provide thousand times higher capacity comparing to existing LTE (Long Term Evolution) networks. Increasing of network capacity can be achieved by combining both spatial and spectral network densification. Influence of spatial network densification on future tremendous capacity growth is very high due to limited spectral resources. Therefore, optimal network planning is an important challenge for future heterogeneous networks with high number of small cells. Network geometry modeling is the significant part of network design and analysis. Multi-tier heterogeneous networks are very complex in terms of topology that requires new advanced approaches to the network planning. In we study the most recent solutions on the stochastic network geometry and analyze their feasibility for different scenarios of heterogeneous network. Studied approached provides good tractability of the mobile network topology and behavior. Poisson point processes combining with Voronoi tessellation provides good approximation of network nodes deployment and coverage areas. We also study feasibility of stochastic models for different buildings environment, including hyper dense skyscrapers environment. Hybrid network model combining Poisson point process with K-means clustering method was developed for D2D (Device-to-Device) heterogeneous network. Proposed model reflects random user behavior and estimate available groups for D2D transmission. Performance simulation of single tier, multi-tier and D2D based heterogeneous network shows that heterogeneous network provides significantly higher performance in terms of throughput and signal-to-interference-plus-noise ratio. Future research directions for network geometry have been outlined in this paper including emerging hot topic of combing the stochastic and deterministic network modelling.
목차
Abstract
Introduction
Stochastic Geometry for Heterogeneous Mobile Networks
Study on the Stochastic Geometry Models Tractability for Different Scenarios of Heterogeneous Networks
Simulation and Performance Analysis of the Stochastically Designed NetNet
Conclusions
References
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UCI(KEPA) : I410-ECN-0101-2016-505-001393976