Research on the construction of radio environment map based on revised spatial interpolation
Radio Environment Map(REM) provides accurate or comprehensive information support to dynamic spectrum access of cognitive radio networks. Practically, the sample size always fails to reach the application requirements due to the limitation of environments, devices or human factors in the measurement...
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National Computer System Engineering Research Institute of China
2018-03-01
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doaj-915c12e22a1645f0af7d659b7a873e8f2020-11-25T01:30:21ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982018-03-0144310310710.16157/j.issn.0258-7998.1725133000079468Research on the construction of radio environment map based on revised spatial interpolationZi Ran0Chang Jun1Zong Rong2Wang Ruonan3Liao Guiwen4School of Information Science and Engineering,Yunnan University,Kunming 650500,ChinaSchool of Information Science and Engineering,Yunnan University,Kunming 650500,ChinaSchool of Information Science and Engineering,Yunnan University,Kunming 650500,ChinaSchool of Information Science and Engineering,Yunnan University,Kunming 650500,ChinaSchool of Information Science and Engineering,Yunnan University,Kunming 650500,ChinaRadio Environment Map(REM) provides accurate or comprehensive information support to dynamic spectrum access of cognitive radio networks. Practically, the sample size always fails to reach the application requirements due to the limitation of environments, devices or human factors in the measurement of field data. Hence, research on the technique of Spatial Interpolation, which can expand the discrete data into surface data, is great of application value. Comparing to the traditional MSM algorithm, this paper presents the RMSM algorithm, which is improved by modifying the weights, flexibly using the local data features, and efficiently neighbor searching. Experiments are conducted in a 15 m×20 m area,showing the obvious improvement of RMSM algorithm which reduces its error by 1.96 dB and enhances the robustness by 55.37%.http://www.chinaaet.com/article/3000079468REMcognitive radiospatial interpolation |
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zho |
format |
Article |
sources |
DOAJ |
author |
Zi Ran Chang Jun Zong Rong Wang Ruonan Liao Guiwen |
spellingShingle |
Zi Ran Chang Jun Zong Rong Wang Ruonan Liao Guiwen Research on the construction of radio environment map based on revised spatial interpolation Dianzi Jishu Yingyong REM cognitive radio spatial interpolation |
author_facet |
Zi Ran Chang Jun Zong Rong Wang Ruonan Liao Guiwen |
author_sort |
Zi Ran |
title |
Research on the construction of radio environment map based on revised spatial interpolation |
title_short |
Research on the construction of radio environment map based on revised spatial interpolation |
title_full |
Research on the construction of radio environment map based on revised spatial interpolation |
title_fullStr |
Research on the construction of radio environment map based on revised spatial interpolation |
title_full_unstemmed |
Research on the construction of radio environment map based on revised spatial interpolation |
title_sort |
research on the construction of radio environment map based on revised spatial interpolation |
publisher |
National Computer System Engineering Research Institute of China |
series |
Dianzi Jishu Yingyong |
issn |
0258-7998 |
publishDate |
2018-03-01 |
description |
Radio Environment Map(REM) provides accurate or comprehensive information support to dynamic spectrum access of cognitive radio networks. Practically, the sample size always fails to reach the application requirements due to the limitation of environments, devices or human factors in the measurement of field data. Hence, research on the technique of Spatial Interpolation, which can expand the discrete data into surface data, is great of application value. Comparing to the traditional MSM algorithm, this paper presents the RMSM algorithm, which is improved by modifying the weights, flexibly using the local data features, and efficiently neighbor searching. Experiments are conducted in a 15 m×20 m area,showing the obvious improvement of RMSM algorithm which reduces its error by 1.96 dB and enhances the robustness by 55.37%. |
topic |
REM cognitive radio spatial interpolation |
url |
http://www.chinaaet.com/article/3000079468 |
work_keys_str_mv |
AT ziran researchontheconstructionofradioenvironmentmapbasedonrevisedspatialinterpolation AT changjun researchontheconstructionofradioenvironmentmapbasedonrevisedspatialinterpolation AT zongrong researchontheconstructionofradioenvironmentmapbasedonrevisedspatialinterpolation AT wangruonan researchontheconstructionofradioenvironmentmapbasedonrevisedspatialinterpolation AT liaoguiwen researchontheconstructionofradioenvironmentmapbasedonrevisedspatialinterpolation |
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1725091902846402560 |