Adaptation of Propagation Model Parameters toward Efficient Cellular Network Planning using Robust LAD Algorithm

Abstract

All new mobile radio communication systems undergo a cautious cellular network planning and re-planning process in order to resourcefully utilize the allotted frequency band and also ensure that the geographical area of focus is adequately fortified with integrated base stations transmitters. To this end, efficient radio propagation model prediction and tuning is of huge importance, as it assists radio network engineers to effectively assess and plan the cellular network signal coverage area. In this research work, an adaptive least absolute deviation approach is proposed and verified to fine-tune the parameters of Ericsson propagation model. The adaptive tuning technique have been verified experimentally with field propagation loss data acquired over three different suburban locations of a recently deployed LTE radio cellular network in Waterlines area of Port Harcourt City. In terms of the mean absolute percentage error and coefficient of efficiency, the outcomes of the proposed adaptive tuning approach show a higher degree of prediction performance accuracy on the measured loss data compared to the commonly applied least squares regression tuning technique.

Application of Levenberg-Marguardt Algorithm for Prime Radio Propagation Wave Attenuation Modelling in Typical Urban, Suburban and Rural Terrains

“…To code and implement the Levenberg-Marquardt and Gauss-Newton algorithms for the propagation loss approximation modelling, we explore the MATLAB 2018a software platform. Similar to the works by [2,14,19,26], engaged different performance evaluation indicators such as RMSE, MSE, MAE and MABE to ascertain the level of the proposed algorithm. Shown in tables 1 are the Log-distance propagation path loss models and their parameters gotten using Levenberg-Marquardt algorithms and the bench-marking Gauss-Newton algorithms.…”

“…The factors include transmission frequency, transmission distance, transmitter antenna heights, receiver antenna heights, engineering parameters of the antenna, terrain type (e.g. urban, suburban, and rural), earth's spherical shape, the transmission medium and the different man-made/structures obstructions that appear in the transmission path [1,2]. The maximum distances the radio signals can attain as they travels through a multifarious environment comprising of numerous streets paths, street widths, buildings walls, building roofs, tree leaves, rain drops, etc., could varies significantly [1,3,4].…”

Career Orientations and Professional Responsibility of Ukrainian Women with Different Sexual Orientations. Are Sexual Minorities Worse Adapted to Professional Activities?

“…Purpose of the article: to identify and compare career orientations and professional responsibility peculiarities in women with different sexual orientations to determine whether the representatives of SM in Ukraine are less adapted to professional activity than the representatives of the heterosexual majority. According to our hypotheses, career orientations and the level of responsibility, which differ significantly, disharmonious profiles of career orientations with very low scores on some orientations will indicate difficulties in the professional adaptation of SM representatives [8][9][10]. As D. M. Kaplan emphasizes: «In a perfect world, one free of discrimination and stigma, Gay, Lesbian, and Bisexual (GLB) workers would be expected to pursue careers no differently than anyone else.…”

Implementation of Quasi-Newton Method Based on BFGS Algorithm for Identification and Optimization of Signal Propagation Loss Model Parameters

“…In literature, numerous techniques and efforts abound that have been utilized by several researchers toward carrying out effective predictive propagation loss modelling, but not without one or two limitations. The least absolute deviation algorithm has been applied to tune and identify of Ericsson propagation model toward a realistic estimation of propagation losses in cellular networks [1]. The authors realized up to 40% root mean square error reduction in the targeted urban environment.…”