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EMW Publishing, Progress In Electromagnetics Research, (139), p. 445-478

DOI: 10.2528/pier13013003

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Exposure optimization in indoor wireless networks by heuristic network planning

Journal article published in 2013 by David Plets, Wout Joseph ORCID, Kris Vanhecke, Luc Martens
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: policy unknown
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Postprint: policy unknown
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Data provided by SHERPA/RoMEO

Abstract

Due to the increased use of indoor wireless networks and the concern about human exposure to radio-frequency sources, exposure awareness has increased during recent years. However, current-day network planners rarely take into account electric-field strengths when designing networks. Therefore, in this paper, a heuristic indoor network planner for exposure calculation and optimization of wireless networks is developed, jointly optimizing coverage and exposure, for homogeneous or heterogeneous networks. The implemented exposure models are validated by simulations and measurements. As a first novel optimization feature, networks are designed that do not exceed a user-defined electric-field strength value in the building. The influence of the maximally allowed field strength, based on norms in different countries, and the assumed minimal separation between the access point and the human are investigated for a typical office building. As a second feature, a novel heuristic exposure minimization algorithm is presented and applied to a wireless homogeneous WiFi and a heterogeneous WiFi-LTE femtocell network, using a new metric that is simple but accurate. Field strength reductions of a factor 3 to 6 compared to traditional network deployments are achieved and a more homogeneous distribution of the observed field values on the building floor is obtained. Also, the influence of the throughput requirement on the field strength distribution on the building floor is assessed. Moreover, it is shown that exposure minimization is more effective for high than for low throughput requirements and that high field values are more reduced than low field values.