2011•Unpublished venueRequires access

A semi-stochastic radio propagation model for wireless MIMO channels

Xiang Hong Xu, Michael Reyer, Florian Schröder, Alexander Engels, Rudolf Mathar

Open publisher page 5 citations

Abstract

Among current physical channel models, deterministic models, such as ray-launching, are accurate but site-specific. Geometry-based stochastic models are flexible, however, cannot benefit if site information is available. In this work, a semi-stochastic MIMO channel model is proposed. It integrates results from deterministic models into stochastic models, merging the advantages of both approaches.

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What this paper is about

Among current physical channel models, deterministic models, such as ray-launching, are accurate but site-specific. Geometry-based stochastic models are flexible, however, cannot benefit if site information is available. In this work, a semi-stochastic MIMO channel model is proposed. It integrates results from deterministic models into stochastic models, merging the advantages of both approaches.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Among current physical channel models, deterministic models, such as ray-launching, are accurate but site-specific. Geometry-based stochastic models are flexible, however, cannot benefit if site information is available. In this work, a semi-stochastic MIMO channel model is proposed. It integrates results from deterministic models into stochastic models, merging the advantages of both approaches.

Key concepts: MIMO, Stochastic modelling, Computer science, Wireless, Channel (broadcasting), Stochastic process, Radio channel, Stochastic geometry

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