Parameter Estimation of Cellular Communication Systems Models in Computational MATLAB Environment: A Systematic Solver-based Numerical Optimization Approaches

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Joseph Isabona 1,2 Sayo A. Akinwumi 3 Theophilus E. Arijaje 3 Odesanya Ituabhor 4 Agbotiname Lucky Imoize 5,6

1. Department of Physics, Covenant University, Ota, Nigeria

2. Federal University Lokoja/Department of Physics, Lokoja, 260101, Nigeria

3. Department of Physics, Covenant University, Ota, 1023, Nigeria

4. Department of Physics, Federal University Lokoja, Lokoja, 260101, Nigeria

5. Department of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Lagos 100213, Nigeria

6. Department of Electrical Engineering and Information Technology, Institute of Digital Communication, Ruhr University, 44801 Bochum, Germany.

* Corresponding author.


Received: 19 Apr. 2023 / Revised: 9 Jun. 2023 / Accepted: 7 Aug. 2023 / Published: 8 Jun. 2024

Index Terms

Numerical Optimisation, Model-based Parameter Estimation, Convergence Criteria, Precision Accuracy, Propagation Model, Radio Frequency, Attenuation


Model-based parameter estimation, identification, and optimisation play a dominant role in many aspects of physical and operational processes in applied sciences, engineering, and other related disciplines. The intricate task involves engaging and fitting the most appropriate parametric model with nonlinear or linear features to experimental field datasets priori to selecting the best optimisation algorithm with the best configuration. Thus, the task is usually geared towards solving a clear optimsation problem. In this paper, a systematic-stepwise approach has been employed to review and benchmark six numerical-based optimization algorithms in MATLAB computational Environment. The algorithms include the Gradient Descent (GRA), Levenberg-Marguardt (LEM), Quasi-Newton (QAN), Gauss-Newton (GUN), Nelda-Meald (NEM), and Trust-Region-Dogleg (TRD). This has been accomplished by engaging them to solve an intricate radio frequency propagation modelling and parametric estimation in connection with practical spatial signal data. The spatial signal data were obtained via real-time field drive test conducted around six eNodeBs transmitters, with case studies taken from different terrains where 4G LTE transmitters are operational. Accordingly, three criteria in connection with rate of convergence Results show that the approximate hessian-based QAN algorithm, followed by the LEM algorithm yielded the best results in optimizing and estimating the RF propagation models parameters. The resultant approach and output of this paper will be of countless assets in assisting the end-users to select the most preferable optimization algorithm to handle their respective intricate problems.

Cite This Paper

Joseph Isabona, Sayo A. Akinwumi, Theophilus E. Arijaje, Odesanya Ituabhor, Agbotiname Lucky Imoize, "Parameter Estimation of Cellular Communication Systems Models in Computational MATLAB Environment: A Systematic Solver-based Numerical Optimization Approaches", International Journal of Computer Network and Information Security(IJCNIS), Vol.16, No.3, pp.70-83, 2024. DOI:10.5815/ijcnis.2024.03.06


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