Spatial channel model with clustered delay line (CDL) for advanced MIMO systems

Understanding the behavior of wireless channels is critical to the design of efficient and reliable communication systems. Research by communication system designers has identified the need for reduced complexity channel models that can be used for rapid modeling to make channel-level comparisons between alternative systems (e.g., modulation and coding choices). Such models can be referred to as reduced complexity models. They have the character of the well-known class of channel models with delay line fading. The Clustered Delay Line (CDL) channel model uses a statistical approach that accurately characterizes the time-varying and frequency-selective nature of the wireless communication channel, especially in environments with clustered multipath components [1]. The CDL model turns out to be a valuable tool for the design of modern wireless communication systems, since it allows, through statistical modeling, to obtain characteristics close enough to real conditions. In this paper the study of radio channel model with clustered delay line is carried out. The description of the channel model and parameters of the radio channel model is given. The description of Matlab 5G Toolbox package is given, using which it is possible to carry out modeling of communication system with MIMO channel taking into account directional properties of antenna system and propagation conditions in CDL channel model. The paper also presents the results of modeling the MIMO communication system with different variants of the CDL model, as well as a comparative analysis of these results with similar characteristics of the MIMO system operating with a traditional channel model with spatially uncorrelated fading.

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Publication Details

Journal
T-Comm
Published
2025-01-01
DOI
https://doi.org/10.36724/2072-8735-2025-19-8-38-48
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Spatial channel model with clustered delay line (CDL) for advanced MIMO systems

Taoufik Ben Rejeb, Aleksei E. Smirnov, Denis Pankratov, Vitaly Kreyndelin et al.
T-Comm
Advanced MIMO Systems Optimization
article

Spatial channel model with clustered delay line (CDL) for advanced MIMO systems

Taoufik Ben Rejeb, Aleksei E. Smirnov, Denis Pankratov, Vitaly Kreyndelin, М. Г. Бакулин
article en

Abstract

Understanding the behavior of wireless channels is critical to the design of efficient and reliable communication systems. Research by communication system designers has identified the need for reduced complexity channel models that can be used for rapid modeling to make channel-level comparisons between alternative systems (e.g., modulation and coding choices). Such models can be referred to as reduced complexity models. They have the character of the well-known class of channel models with delay line fading. The Clustered Delay Line (CDL) channel model uses a statistical approach that accurately characterizes the time-varying and frequency-selective nature of the wireless communication channel, especially in environments with clustered multipath components [1]. The CDL model turns out to be a valuable tool for the design of modern wireless communication systems, since it allows, through statistical modeling, to obtain characteristics close enough to real conditions. In this paper the study of radio channel model with clustered delay line is carried out. The description of the channel model and parameters of the radio channel model is given. The description of Matlab 5G Toolbox package is given, using which it is possible to carry out modeling of communication system with MIMO channel taking into account directional properties of antenna system and propagation conditions in CDL channel model. The paper also presents the results of modeling the MIMO communication system with different variants of the CDL model, as well as a comparative analysis of these results with similar characteristics of the MIMO system operating with a traditional channel model with spatially uncorrelated fading.

T-CommVol. 19(8)
Openalex Percentile: Top 73%
Advanced MIMO Systems Optimization
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