ANFIS Model for Path Loss Prediction in the GSM and WCDMA Bands in Urban Area


  • Nasir Faruk Department of Telecommunication Science, University of Ilorin, Ilorin, Nigeria
  • N. T. Surajudeen-Bakinde Department of Electrical and Electronics Engineering, University of Ilorin, Nigeria
  • Abubakar Abdulkarim Dept of Electrical Engineering Faculty of Engineering Ahmadu Bello University Zaria.
  • Segun I. Popoola Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria
  • A. Abdulkarim Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria
  • Lukman A. Olawoyin Department of Telecommunication Science, University of Ilorin, Ilorin, Nigeria
  • Aderemi A. Atayero Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria



Path loss propagation is a vital concern when designing and planning networks in mobile communication systems. Propagation models such as the empirical, deterministic and theoretical models, which possess complex, inconsistent, time-consuming and non-adaptable features, have proven to be inefficient in designing of wireless systems, thereby resulting in the need for a more reliable model. Artificial Intelligence methods seem to overcome the drawbacks of the propagation models for predicting path loss. In this paper, the ANFIS approach to path loss prediction in the GSM and WCDMA bands is presented for selected urban areas in Nigeria. Furthermore, the effects of the number of Membership Functions (MFs) are investigated. The prediction results indicated that the ANFIS model outperformed the Hata, Cost-231, Egli and ECC-33 models in both Kano and Abuja urban areas. In addition, an increase in the number of MFs conceded an improved RMSE result for the generalized bell-shaped MF. The general performance and outcome of this research work show the efficiency and usefulness of the ANFIS model in improving prediction accuracy over propagation models

Author Biography

Abubakar Abdulkarim, Dept of Electrical Engineering Faculty of Engineering Ahmadu Bello University Zaria.


Senior Lecturer ,

Dept of Electrical Engineering
Faculty of Engineering
Ahmadu Bello University Zaria.


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How to Cite

Faruk, N., Surajudeen-Bakinde, N. T., Abdulkarim, A., I. Popoola, S., Abdulkarim, A., A. Olawoyin, L., & A. Atayero, A. (2019). ANFIS Model for Path Loss Prediction in the GSM and WCDMA Bands in Urban Area. ELEKTRIKA- Journal of Electrical Engineering, 18(1), 1–10.