TY - GEN
T1 - Towards Internet of Underground Things in smart lighting
T2 - 14th IEEE International Conference on Networking, Sensing and Control, ICNSC 2017
AU - Salam, Abdul
AU - Vuran, Mehmet C.
AU - Irmak, Suat
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - The Internet of Underground Things (IOUT) has many applications in the area of smart lighting. IOUT enables communications in smart lighting through underground (UG) and aboveground (AG) communication channels. In IOUT communications, an in-depth analysis of the wireless underground channel is important to design smart lighting solutions. In this paper, based on the empirical and the statistical analysis, a statistical channel model for the UG channel has been developed. The parameters for the statistical tapped-delay-line model are extracted from the measured power delay profiles (PDP). The PDP of the UG channel is represented by the exponential decay of the lateral, direct, and reflected waves. The developed statistical model can be used to generate the channel impulse response, and precisely predicts the UG channel RMS delay spread, coherence bandwidth, and propagation loss characteristics in different conditions. The statistical model also shows good agreement with the empirical data, and is useful for tailored IOUT solutions in the area of smart lighting.
AB - The Internet of Underground Things (IOUT) has many applications in the area of smart lighting. IOUT enables communications in smart lighting through underground (UG) and aboveground (AG) communication channels. In IOUT communications, an in-depth analysis of the wireless underground channel is important to design smart lighting solutions. In this paper, based on the empirical and the statistical analysis, a statistical channel model for the UG channel has been developed. The parameters for the statistical tapped-delay-line model are extracted from the measured power delay profiles (PDP). The PDP of the UG channel is represented by the exponential decay of the lateral, direct, and reflected waves. The developed statistical model can be used to generate the channel impulse response, and precisely predicts the UG channel RMS delay spread, coherence bandwidth, and propagation loss characteristics in different conditions. The statistical model also shows good agreement with the empirical data, and is useful for tailored IOUT solutions in the area of smart lighting.
UR - http://www.scopus.com/inward/record.url?scp=85028318723&partnerID=8YFLogxK
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U2 - 10.1109/ICNSC.2017.8000155
DO - 10.1109/ICNSC.2017.8000155
M3 - Conference contribution
AN - SCOPUS:85028318723
T3 - Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017
SP - 574
EP - 579
BT - Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017
A2 - Guerrieri, Antonio
A2 - Fortino, Giancarlo
A2 - Vasilakos, Athanasios V.
A2 - Zhou, MengChu
A2 - Lukszo, Zofia
A2 - Palau, Carlos
A2 - Liotta, Antonio
A2 - Vinci, Andrea
A2 - Basile, Francesco
A2 - Fanti, Maria Pia
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 May 2017 through 18 May 2017
ER -