Azimuth Variable-Path Loss Fitting with Received Signal Power Data for White Space Boundary Estimation

Kenshi HORIHATA; Issei KANNO; Akio HASEGAWA; Toshiyuki MAEYAMA; Yoshio TAKEUCHI

doi:10.1587/transcom.2015ISP0014

Azimuth Variable-Path Loss Fitting with Received Signal Power Data for White Space Boundary Estimation

Kenshi HORIHATA, Issei KANNO, Akio HASEGAWA, Toshiyuki MAEYAMA, Yoshio TAKEUCHI

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This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.

Publication: IEICE TRANSACTIONS on Communications Vol.E99-B No.1 pp.87-94

Publication Date: 2016/01/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2015ISP0014

Type of Manuscript: Special Section PAPER (Special Section on Recent Progress in Antennas, Propagation and Wireless Systems Related to Topics in ISAP2014)

Category: Wireless Communication Technologies

Authors

Kenshi HORIHATA
  Advanced Telecommunications Research Institute International (ATR)
Issei KANNO
  Advanced Telecommunications Research Institute International (ATR)
Akio HASEGAWA
  Advanced Telecommunications Research Institute International (ATR)
Toshiyuki MAEYAMA
  Advanced Telecommunications Research Institute International (ATR),Takushoku University
Yoshio TAKEUCHI
  Advanced Telecommunications Research Institute International (ATR)

Keyword

spectrum database, radio environment map, spectrum sharing, pathloss fitting, azimuth variable

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Kenshi HORIHATA, Issei KANNO, Akio HASEGAWA, Toshiyuki MAEYAMA, Yoshio TAKEUCHI, "Azimuth Variable-Path Loss Fitting with Received Signal Power Data for White Space Boundary Estimation" in IEICE TRANSACTIONS on Communications, vol. E99-B, no. 1, pp. 87-94, January 2016, doi: 10.1587/transcom.2015ISP0014.
Abstract: This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2015ISP0014/_p

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@ARTICLE{e99-b_1_87,
author={Kenshi HORIHATA, Issei KANNO, Akio HASEGAWA, Toshiyuki MAEYAMA, Yoshio TAKEUCHI, },
journal={IEICE TRANSACTIONS on Communications},
title={Azimuth Variable-Path Loss Fitting with Received Signal Power Data for White Space Boundary Estimation},
year={2016},
volume={E99-B},
number={1},
pages={87-94},
abstract={This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.},
keywords={},
doi={10.1587/transcom.2015ISP0014},
ISSN={1745-1345},
month={January},}

Copy

TY - JOUR
TI - Azimuth Variable-Path Loss Fitting with Received Signal Power Data for White Space Boundary Estimation
T2 - IEICE TRANSACTIONS on Communications
SP - 87
EP - 94
AU - Kenshi HORIHATA
AU - Issei KANNO
AU - Akio HASEGAWA
AU - Toshiyuki MAEYAMA
AU - Yoshio TAKEUCHI
PY - 2016
DO - 10.1587/transcom.2015ISP0014
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2016
AB - This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.
ER -