Cross-Correlation of Large-Scale Parameters in Multi-Link Systems : Analysis using the Box-Cox Transformation
(2018) In IEEE Access 6. p.13555-13564- Abstract
Spatially distributed transmission points connected to the same source, known as distributed antenna systems, can improve system performance compared to single-link traditional systems. However, the anticipated gain depends heavily on the cross-correlation properties of the large-scale parameters (LSPs) of the different links. Usually, measured LSPs—except the large-scale fading—have non-Gaussian distributions. Therefore, in order to study their multi-link cross-correlation properties, scenario- and parameter-specific adhoc transformations are applied such that the LSPs have Gaussian distributions in the transform domain [1], [2]. In this work, we propose using the... (More)
Spatially distributed transmission points connected to the same source, known as distributed antenna systems, can improve system performance compared to single-link traditional systems. However, the anticipated gain depends heavily on the cross-correlation properties of the large-scale parameters (LSPs) of the different links. Usually, measured LSPs—except the large-scale fading—have non-Gaussian distributions. Therefore, in order to study their multi-link cross-correlation properties, scenario- and parameter-specific adhoc transformations are applied such that the LSPs have Gaussian distributions in the transform domain [1], [2]. In this work, we propose using the Box-Cox transformation as a general framework for homogenizing this conversion step. The Box-Cox transformation is by nature not distribution specific; therefore, it can be used regardless of the empirical distributions of the studied LSPs. We demonstrate the applicability of the proposed framework by studying multi-link fully-coherent propagation measurements of four base stations and one mobile station in a suburban microcell environment at 2.6 GHz. The inter- and intra-link crosscorrelation of four LSPs—the large-scale fading, and the delay, azimuth, and elevation spreads—are analyzed and their distributions are modeled. Based on our analysis, it is found that, for the investigated environment: 1) the LSPs of the different links can be modeled using unimodal and bimodal Gaussian distributions, and 2) the inter- and intra-link cross-correlation coefficients of the different studied LSPs can be modeled using the Truncated Gaussian distribution. The proposed models are validated using the Kolmogorov-Smirnov test and their parameters are provided.
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- author
- Dahman, Ghassan LU ; Flordelis, Jose LU and Tufvesson, Fredrik LU
- organization
- publishing date
- 2018-01-24
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Distributed antenna systems, inter-link cross-correlation, intra-link cross-correlation, large-scale parameters, multi-link systems
- in
- IEEE Access
- volume
- 6
- pages
- 13555 - 13564
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85040977940
- ISSN
- 2169-3536
- DOI
- 10.1109/ACCESS.2018.2797418
- language
- English
- LU publication?
- yes
- id
- ab3a621f-604a-4707-b8ea-d25d5a3927ba
- date added to LUP
- 2018-02-05 13:49:51
- date last changed
- 2022-05-10 21:42:48
@article{ab3a621f-604a-4707-b8ea-d25d5a3927ba, abstract = {{<p>Spatially distributed transmission points connected to the same source, known as distributed antenna systems, can improve system performance compared to single-link traditional systems. However, the anticipated gain depends heavily on the cross-correlation properties of the large-scale parameters (LSPs) of the different links. Usually, measured LSPs&#x2014;except the large-scale fading&#x2014;have non-Gaussian distributions. Therefore, in order to study their multi-link cross-correlation properties, scenario- and parameter-specific adhoc transformations are applied such that the LSPs have Gaussian distributions in the transform domain &#x005B;1&#x005D;, &#x005B;2&#x005D;. In this work, we propose using the Box-Cox transformation as a general framework for homogenizing this conversion step. The Box-Cox transformation is by nature not distribution specific; therefore, it can be used regardless of the empirical distributions of the studied LSPs. We demonstrate the applicability of the proposed framework by studying multi-link fully-coherent propagation measurements of four base stations and one mobile station in a suburban microcell environment at 2.6 GHz. The inter- and intra-link crosscorrelation of four LSPs&#x2014;the large-scale fading, and the delay, azimuth, and elevation spreads&#x2014;are analyzed and their distributions are modeled. Based on our analysis, it is found that, for the investigated environment: 1) the LSPs of the different links can be modeled using unimodal and bimodal Gaussian distributions, and 2) the inter- and intra-link cross-correlation coefficients of the different studied LSPs can be modeled using the Truncated Gaussian distribution. The proposed models are validated using the Kolmogorov-Smirnov test and their parameters are provided.</p>}}, author = {{Dahman, Ghassan and Flordelis, Jose and Tufvesson, Fredrik}}, issn = {{2169-3536}}, keywords = {{Distributed antenna systems; inter-link cross-correlation; intra-link cross-correlation; large-scale parameters; multi-link systems}}, language = {{eng}}, month = {{01}}, pages = {{13555--13564}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Access}}, title = {{Cross-Correlation of Large-Scale Parameters in Multi-Link Systems : Analysis using the Box-Cox Transformation}}, url = {{http://dx.doi.org/10.1109/ACCESS.2018.2797418}}, doi = {{10.1109/ACCESS.2018.2797418}}, volume = {{6}}, year = {{2018}}, }