Quantification of Scenario Distance within Generic WINNER Channel Model
Starting from the premise that stochastic properties of a radio environment can be abstracted by defining scenarios, a generic MIMO channel model is built by the WINNER project. The parameter space of the WINNER model is, among others, described by normal probability distributions and correlation co...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2013/176704 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849412496047210496 |
|---|---|
| author | Milan Narandžić Christian Schneider Wim Kotterman Reiner S. Thomä |
| author_facet | Milan Narandžić Christian Schneider Wim Kotterman Reiner S. Thomä |
| author_sort | Milan Narandžić |
| collection | DOAJ |
| description | Starting from the premise that stochastic properties of a radio environment can be abstracted by defining scenarios, a generic MIMO channel model is built by the WINNER project. The parameter space of the WINNER model is, among others, described by normal probability distributions and correlation coefficients that provide a suitable space for scenario comparison. The possibility to quantify the distance between reference scenarios and measurements enables objective comparison and classification of measurements into scenario classes. In this paper we approximate the WINNER scenarios with multivariate normal distributions and then use the mean Kullback-Leibler divergence to quantify their divergence. The results show that the WINNER scenario groups (A, B, C, and D) or propagation classes (LoS, OLoS, and NLoS) do not necessarily ensure minimum separation within the groups/classes. Instead, the following grouping minimizes intragroup distances: (i) indoor-to-outdoor and outdoor-to-indoor scenarios (A2, B4, and C4), (ii) macrocell configurations for suburban, urban, and rural scenarios (C1, C2, and D1), and (iii) indoor/hotspot/microcellular scenarios (A1, B3, and B1). The computation of the divergence between Ilmenau and Dresden measurements and WINNER scenarios confirms that the parameters of the C2 scenario are a proper reference for a large variety of urban macrocell environments. |
| format | Article |
| id | doaj-art-6492902284ad4049b992bf62dfd39744 |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-6492902284ad4049b992bf62dfd397442025-08-20T03:34:25ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772013-01-01201310.1155/2013/176704176704Quantification of Scenario Distance within Generic WINNER Channel ModelMilan Narandžić0Christian Schneider1Wim Kotterman2Reiner S. Thomä3Department for Power, Electronic and Communication Engineering, Faculty of Technical Sciences, Trg D. Obradovića 6, 2100 Novi Sad, SerbiaElectronic Measurement Research Lab, Ilmenau University of Technology, PSF 100565, 98684 Ilmenau, GermanyDigital Broadcasting Research Laboratory, Ilmenau University of Technology, PSF 100565, 98684 Ilmenau, GermanyElectronic Measurement Research Lab, Ilmenau University of Technology, PSF 100565, 98684 Ilmenau, GermanyStarting from the premise that stochastic properties of a radio environment can be abstracted by defining scenarios, a generic MIMO channel model is built by the WINNER project. The parameter space of the WINNER model is, among others, described by normal probability distributions and correlation coefficients that provide a suitable space for scenario comparison. The possibility to quantify the distance between reference scenarios and measurements enables objective comparison and classification of measurements into scenario classes. In this paper we approximate the WINNER scenarios with multivariate normal distributions and then use the mean Kullback-Leibler divergence to quantify their divergence. The results show that the WINNER scenario groups (A, B, C, and D) or propagation classes (LoS, OLoS, and NLoS) do not necessarily ensure minimum separation within the groups/classes. Instead, the following grouping minimizes intragroup distances: (i) indoor-to-outdoor and outdoor-to-indoor scenarios (A2, B4, and C4), (ii) macrocell configurations for suburban, urban, and rural scenarios (C1, C2, and D1), and (iii) indoor/hotspot/microcellular scenarios (A1, B3, and B1). The computation of the divergence between Ilmenau and Dresden measurements and WINNER scenarios confirms that the parameters of the C2 scenario are a proper reference for a large variety of urban macrocell environments.http://dx.doi.org/10.1155/2013/176704 |
| spellingShingle | Milan Narandžić Christian Schneider Wim Kotterman Reiner S. Thomä Quantification of Scenario Distance within Generic WINNER Channel Model International Journal of Antennas and Propagation |
| title | Quantification of Scenario Distance within Generic WINNER Channel Model |
| title_full | Quantification of Scenario Distance within Generic WINNER Channel Model |
| title_fullStr | Quantification of Scenario Distance within Generic WINNER Channel Model |
| title_full_unstemmed | Quantification of Scenario Distance within Generic WINNER Channel Model |
| title_short | Quantification of Scenario Distance within Generic WINNER Channel Model |
| title_sort | quantification of scenario distance within generic winner channel model |
| url | http://dx.doi.org/10.1155/2013/176704 |
| work_keys_str_mv | AT milannarandzic quantificationofscenariodistancewithingenericwinnerchannelmodel AT christianschneider quantificationofscenariodistancewithingenericwinnerchannelmodel AT wimkotterman quantificationofscenariodistancewithingenericwinnerchannelmodel AT reinersthoma quantificationofscenariodistancewithingenericwinnerchannelmodel |