2004•IEEE Transactions on Wireless CommunicationsRequires access

A Generalized Space–Time Multiple-Input Multiple-Output (MIMO) Channel Model

Hao Xu, Dmitry Chizhik, Haiyang Huang, Reinaldo A. Valenzuela

Open publisher page 81 citations

Abstract

This paper presents a generalized multiple-input multiple-output (MIMO) channel modeling technique for link level and system level simulations. The model combines the correlation approach and wave superposition approach to achieve both accuracy and efficiency. The spatial, temporal, and frequency dispersions of the MIMO channels are implicitly modeled based on any given statistics. Polarizations, channel transitions, uplink and downlink channels, and keyhole-pinhole channels are modeled as optional modules. Theoretical justifications as well as experimental verification of the model are also presented. The proposed model can be applied to system simulations for MIMO as well as other adaptive antenna applications.

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What this paper is about

This paper presents a generalized multiple-input multiple-output (MIMO) channel modeling technique for link level and system level simulations. The model combines the correlation approach and wave superposition approach to achieve both accuracy and efficiency. The spatial, temporal, and frequency dispersions of the MIMO channels are implicitly modeled based on any given statistics. Polarizations, channel transitions, uplink and downlink channels, and keyhole-pinhole channels are modeled as optional modules. Theoretical justifications as well as experimental verification of the model are also presented. The proposed model can be applied to system simulations for MIMO as well as other adaptive antenna applications.

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OpenAlex reports 81 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents a generalized multiple-input multiple-output (MIMO) channel modeling technique for link level and system level simulations. The model combines the correlation approach and wave superposition approach to achieve both accuracy and efficiency. The spatial, temporal, and frequency dispersions of the MIMO channels are implicitly modeled based on any given statistics. Polarizations, channel transitions, uplink and downlink channels, and keyhole-pinhole channels are modeled as optional modules. Theoretical justifications as well as experimental verification of the model are also presented. The proposed model can be applied to system simulations for MIMO as well as other adaptive antenna applications.

Key concepts: MIMO, Computer science, Telecommunications link, Channel (broadcasting), 3G MIMO, Algorithm, Superposition principle, Antenna (radio)

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