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Optimal Model for Path Loss Predictions using Feed-Forward Neural Networks

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Optimal Model for Path Loss Predictions using Feed-Forward Neural Networks

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Popoola, SI.; Adetiba, E.; Atayero, AA.; Faruk, N.; Tavares De Araujo Cesariny Calafate, CM. (2018). Optimal Model for Path Loss Predictions using Feed-Forward Neural Networks. Cogent Engineering. 5:1-19. https://doi.org/10.1080/23311916.2018.1444345

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/119577

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Title: Optimal Model for Path Loss Predictions using Feed-Forward Neural Networks
Author: Popoola, Segun I. Adetiba, Emmanuel Atayero, Aderemi A. Faruk, Nasir Tavares De Araujo Cesariny Calafate, Carlos Miguel
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] In this paper, an optimal model is developed for path loss predictions using the Feed-Forward Neural Network (FFNN) algorithm. Drive test measurements were carried out in Canaanland Ota, Nigeria and Ilorin, Nigeria ...[+]
Subjects: Path loss , Received signal strength , Scale conjugate gradient , Radio network planning , Artificial Neural Network
Copyrigths: Reconocimiento (by)
Source:
Cogent Engineering. (eissn: 2331-1916 )
DOI: 10.1080/23311916.2018.1444345
Publisher:
Cogent OA
Publisher version: https://doi.org/10.1080/23311916.2018.1444345
Project ID:
info:eu-repo/grantAgreement/CUCRID//SMARTCU-000343/
Thanks:
This work was supported by Covenant University [grant number CUCRID-SMARTCU-000343].
Type: Artículo

References

Adetiba, E., Iweanya, V. C., Popoola, S. I., Adetiba, J. N., & Menon, C. (2017). Automated detection of heart defects in athletes based on electrocardiography and artificial neural network. Cogent Engineering, 4(1). doi:10.1080/23311916.2017.1411220

Adetiba, E., & Olugbara, O. O. (2015). Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features. The Scientific World Journal, 2015, 1-17. doi:10.1155/2015/786013

Adeyemo, Z. K., Ogunremi, O. K., & Ojedokun, I. A. (2016). Optimization of Okumura-Hata Model for Long Term Evolution Network Deployment in Lagos, Nigeria. International Journal on Communications Antenna and Propagation (IRECAP), 6(3), 146. doi:10.15866/irecap.v6i3.9012 [+]
Adetiba, E., Iweanya, V. C., Popoola, S. I., Adetiba, J. N., & Menon, C. (2017). Automated detection of heart defects in athletes based on electrocardiography and artificial neural network. Cogent Engineering, 4(1). doi:10.1080/23311916.2017.1411220

Adetiba, E., & Olugbara, O. O. (2015). Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features. The Scientific World Journal, 2015, 1-17. doi:10.1155/2015/786013

Adeyemo, Z. K., Ogunremi, O. K., & Ojedokun, I. A. (2016). Optimization of Okumura-Hata Model for Long Term Evolution Network Deployment in Lagos, Nigeria. International Journal on Communications Antenna and Propagation (IRECAP), 6(3), 146. doi:10.15866/irecap.v6i3.9012

Akhoondzadeh-Asl, L., & Noori, N. (2007). Modification and Tuning of the Universal Okumura-Hata Model for Radio Wave Propagation Predictions. 2007 Asia-Pacific Microwave Conference. doi:10.1109/apmc.2007.4554925

Al Salameh, M. S., & Al-Zu’bi, M. M. (2015). Prediction of radiowave propagation for wireless cellular networks in Jordan.Paper presented at the Knowledge and Smart Technology (KST), 2015 7th International Conference on.

Alamoud, M. A., & Schutz, W. (2012). Okumura-hata model tuning for TETRA mobile radio networks in Saudi Arabia. 2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA). doi:10.1109/ictea.2012.6462901

Armenta, A., Serrano, A., Cabrera, M., & Conte, R. (2011). The new digital divide: the confluence of broadband penetration, sustainable development, technology adoption and community participation. Information Technology for Development, 18(4), 345-353. doi:10.1080/02681102.2011.625925

Begovic, P., Behlilovic, N., & Avdic, E. (2012). Applicability evaluation of Okumura, Ericsson 9999 and winner propagation models for coverage planning in 3.5 GHZ WiMAX systems.

Erceg, V., Greenstein, L. J., Tjandra, S. Y., Parkoff, S. R., Gupta, A., Kulic, B., … Bianchi, R. (1999). An empirically based path loss model for wireless channels in suburban environments. IEEE Journal on Selected Areas in Communications, 17(7), 1205-1211. doi:10.1109/49.778178

Farhoud, M., El-Keyi, A., & Sultan, A. (2013). Empirical correction of the Okumura-Hata model for the 900 MHz band in Egypt. 2013 Third International Conference on Communications and Information Technology (ICCIT). doi:10.1109/iccitechnology.2013.6579585

Faruk, N., Adediran, Y. A., & Ayeni, A. A. (2013). Error bounds of empirical path loss models at VHF/UHF bands in Kwara State, Nigeria. Eurocon 2013. doi:10.1109/eurocon.2013.6625043

Faruk, N., Ayeni, A., & Adediran, Y. A. (2013). ON THE STUDY OF EMPIRICAL PATH LOSS MODELS FOR ACCURATE PREDICTION OF TV SIGNAL FOR SECONDARY USERS. Progress In Electromagnetics Research B, 49, 155-176. doi:10.2528/pierb13011306

Hata, M. (1980). Empirical formula for propagation loss in land mobile radio services. IEEE Transactions on Vehicular Technology, 29(3), 317-325. doi:10.1109/t-vt.1980.23859

Hufford, G. A. (1952). An integral equation approach to the problem of wave propagation over an irregular surface. Quarterly of Applied Mathematics, 9(4), 391-404. doi:10.1090/qam/44350

Ibhaze, A. E., Ajose, S. O., Atayero, A. A.-A., & Idachaba, F. E. (2016). Developing smart cities through optimal wireless mobile network.Paper presented at the emerging technologies and innovative business practices for the transformation of societies (EmergiTech), IEEE international conference on.

Luebbers, R. (1984). Propagation prediction for hilly terrain using GTD wedge diffraction. IEEE Transactions on Antennas and Propagation, 32(9), 951-955. doi:10.1109/tap.1984.1143449

Matthews, V. O., Osuoyah, Q., Popoola, S. I., Adetiba, E., & Atayero, A. A. (2017, July 5–7). C-BRIG: A network architecture for real-time information exchange in smart and connected campuses. In Lecture notes in engineering and computer science: Proceedings of the world congress on engineering 2017 (pp. 398–401). London.

Medeisis, A., & Kajackas, A. (s. f.). On the use of the universal Okumura-Hata propagation prediction model in rural areas. VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026). doi:10.1109/vetecs.2000.851585

Mohtashami, V., & Shishegar, A. A. (2012). Modified wavefront decomposition method for fast and accurate ray-tracing simulation. IET Microwaves, Antennas & Propagation, 6(3), 295. doi:10.1049/iet-map.2011.0264

Nimavat, V. D., & Kulkarni, G. (2012). Simulation and performance evaluation of GSM propagation channel under the urban, suburban and rural environments.Paper presented at the communication, information & computing technology (ICCICT), 2012 international conference on.

. O. F. O. (2014). RADIO FREQUENCY OPTIMIZATION OF MOBILE NETWORKS IN ABEOKUTA, NIGERIA FOR IMPROVED QUALITY OF SERVICE. International Journal of Research in Engineering and Technology, 03(08), 174-180. doi:10.15623/ijret.2014.0308027

Phillips, C., Sicker, D., & Grunwald, D. (2013). A Survey of Wireless Path Loss Prediction and Coverage Mapping Methods. IEEE Communications Surveys & Tutorials, 15(1), 255-270. doi:10.1109/surv.2012.022412.00172

Popoola, S. I., Atayero, A. A., Badejo, J. A., John, T. M., Odukoya, J. A., & Omole, D. O. (2018). Learning analytics for smart campus: Data on academic performances of engineering undergraduates in Nigerian private university. Data in Brief, 17, 76-94. doi:10.1016/j.dib.2017.12.059

Popoola, S. I., Atayero, A. A., & Faruk, N. (2018). Received signal strength and local terrain profile data for radio network planning and optimization at GSM frequency bands. Data in Brief, 16, 972-981. doi:10.1016/j.dib.2017.12.036

Popoola, S. I., Atayero, A. A., Faruk, N., & Badejo, J. A. (2018). Data on the key performance indicators for quality of service of GSM networks in Nigeria. Data in Brief, 16, 914-928. doi:10.1016/j.dib.2017.12.005

Popoola, S. I., Atayero, A. A., Faruk, N., Calafate, C. T., Adetiba, E., & Matthews, V. O. (2017, July 5–7). Calibrating the standard path loss model for urban environments using field measurements and geospatial data.Paper presented at the Lecture notes in engineering and computer science: Proceedings of the world congress on engineering 2017 (pp. 513–518). London.

Popoola, S. I., Atayero, A. A., Faruk, N., Calafate, C. T., Olawoyin, L. A., & Matthews, V. O. (2017). Standard propagation model tuning for path loss predictions in built-up environments.Paper presented at the International Conference on Computational Science and Its Applications.

Popoola, S. I., Atayero, A. A., Okanlawon, T. T., Omopariola, B. I., & Takpor, O. A. (2018). Smart campus: Data on energy consumption in an ICT-driven university. Data in Brief, 16, 780-793. doi:10.1016/j.dib.2017.11.091

Popoola, S. I., Badejo, J. A., Ojewande, S. O., & Atayero, A. (2017, October 25–27). Statistical evaluation of quality of service offered by GSM network operators in Nigeria. In Lecture notes in engineering and computer science: Proceedings of the world congress on engineering and computer science 2017 (pp. 69–73). San Francisco.

Popoola, S. I., Misra, S., & Atayero, A. A. (2018). Outdoor path loss predictions based on extreme learning machine. Wireless Personal Communications, 1–20.

Rath, H. K., Verma, S., Simha, A., & Karandikar, A. (2016). Path Loss model for Indian terrain-empirical approach.Paper presented at the communication (NCC), 2016 twenty second national conference on.

Salman, M. A., Popoola, S. I., Faruk, N., Surajudeen-Bakinde, N., Oloyede, A. A., & Olawoyin, L. A. (2017). Adaptive neuro-fuzzy model for path loss prediction in the VHF band.Paper presented at the computing networking and informatics (ICCNI), 2017 international conference on.

Schneider, I., Lambrecht, F., & Baier, A. (s. f.). Enhancement of the Okumura-Hata propagation model using detailed morphological and building data. Proceedings of PIMRC ’96 - 7th International Symposium on Personal, Indoor, and Mobile Communications. doi:10.1109/pimrc.1996.567508

Sotiroudis, S. P., & Siakavara, K. (2015). Mobile radio propagation path loss prediction using Artificial Neural Networks with optimal input information for urban environments. AEU - International Journal of Electronics and Communications, 69(10), 1453-1463. doi:10.1016/j.aeue.2015.06.014

Zelley, C. A., & Constantinou, C. C. (1999). A three-dimensional parabolic equation applied to VHF/UHF propagation over irregular terrain. IEEE Transactions on Antennas and Propagation, 47(10), 1586-1596. doi:10.1109/8.805904

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