Small Cells' Deployment Strategy and Self-Optimization for EMF Exposure Reduction in HetNets

The increasing densification of telecommunications mobile networks raises the compelling problem of exposure to electromagnetic fields (EMF). In this paper, we address the particular concept of heterogeneous networks, where small cells (SCs) are deployed to build up a second layer to the existing ma...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2016-09, Vol.65 (9), p.7184-7194
Main Authors: Sidi, Habib B. A., Altman, Zwi
Format: Article
Language:English
Subjects:
Bit rate
Coverage extension
electromagnetic field exposure
electromagnetic fields (EMF)
enhanced intercell interference coordination (eICIC)
exposure index (EI)
Fading
Health risk assessment
Interference
Mobile communication
Optimization
Power control
self-organization
small-cell planning
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Summary:The increasing densification of telecommunications mobile networks raises the compelling problem of exposure to electromagnetic fields (EMF). In this paper, we address the particular concept of heterogeneous networks, where small cells (SCs) are deployed to build up a second layer to the existing macrocell network. SC deployment is shown to be particularly effective in reducing EMF exposure, in addition to capacity enhancement. Previous studies on EMF have focused on the uplink (UL) and downlink (DL) components separately, although they are strongly correlated. Relying on the definition of the exposure index (EI) from the European FP7 Lexnet project, we evaluate the impact on EMF exposure due to SC deployment. Guidelines for EMF-efficient deployment of SCs are first presented and evaluated. Then, a new enhanced intercell interference coordination (eICIC) algorithm using UL and DL metrics to optimize capacity and exposure to EMF is proposed. Static and self-optimizing dynamic implementations of the solution are considered, using a utility function related to the sojourn time of the users. Time-domain and frequency-domain self-optimized eICIC are compared in terms of EMF exposure reduction and capacity enhancement. The eICIC algorithms are combined with a self-optimized coverage range expansion function leading to further reduction of the EI. The proposed solution for optimizing both capacity and exposure to EMF is compared with a capacity-driven solution based on the DL metrics only. Simulation results illustrate the performance gains obtained for the different SC deployment scenarios.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2015.2487038