Browsing by Author "Nathaniel Salawu"

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Performance Analysis of Path Loss Models for Wireless Communications at 3.5 GHz and 23 GHz in a Regular Urban Environment
(IEEEE, 2023) Farouq E. Shaibu; Elizabeth N. Onwuka; Nathaniel Salawu; Oyewobi S. Stephen
Performance of Path Loss Models over Mid-Band and High-Band Channels for 5G Communication Networks: A Review
(MDPI, 2023-11-07) Farooq E Shuaibu; Elizabeth N. Onwuka; Nathaniel Salawu; Oyewobi S. Stephen; Karim Djouani; Adnan M. Abu-Mahfouz
The rapid development of 5G communication networks has ushered in a new era of highspeed, low-latency wireless connectivity, as well as the enabling of transformative technologies. However, a crucial aspect of ensuring reliable communication is the accurate modeling of path loss, as it directly impacts signal coverage, interference, and overall network efficiency. This review paper critically assesses the performance of path loss models in mid-band and high-band frequencies and examines their effectiveness in addressing the challenges of 5G deployment. In this paper, we first present the summary of the background, highlighting the increasing demand for high-quality wireless connectivity and the unique characteristics of mid-band (1–6 GHz) and high-band (>6 GHz) frequencies in the 5G spectrum. The methodology comprehensively reviews some of the existing path loss models, considering both empirical and machine learning approaches. We analyze the strengths and weaknesses of these models, considering factors such as urban and suburban environments and indoor scenarios. The results highlight the significant advancements in path loss modeling for mid-band and high-band 5G channels. In terms of prediction accuracy and computing effectiveness, machine learning models performed better than empirical models in both mid-band and high-band frequency spectra. As a result, they might be suggested as an alternative yet promising approach to predicting path loss in these bands. We consider the results of this review to be promising, as they provide network operators and researchers with valuable insights into the state-of-the-art path loss models for mid-band and high-band 5G channels. Future work suggests tuning an ensemble machine learning model to enhance a stable empirical model with multiple parameters to develop a hybrid path loss model for the mid-band frequency spectrum.
Performance Study of Empirical Path Loss Models at 11 GHz in an Irregular Environment for Wireless Communications
(International Engineering Conference (IEC 2022), 2022) Farouq E. Shaibu; Elizabeth N. Onwuka; Nathaniel Salawu; Oyewobi S. Stephen
In this paper, we report the performance study of two of the most widely used empirical models, 3GPP and CI models at 11 GHz in an irregular environment for future communication networks. Large-scale fading simulation has been carried out under the line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios. An RF planning software package, Path Loss 5 (PL5) was used to carry out the simulation to reveal the expected receiver power, path loss, and terrain profile for the environment under consideration. From the simulated report, the simulated values were fitted with the path loss models. With the path loss exponent of 3.1, the results of the models' comparisons revealed that the CI model overestimated the path loss throughout its path in both LoS and NLoS scenarios with an MAE of 16.32 dB and 19.21 dB. The 3GPP model shows its best performance in LoS scenario but within a short distance (< ??? ?) in NLoS scenario with an MAE of 9.14 dB and 11.09 dB respectively. The simulations suggest that the 3GPP model is better for path loss prediction in an environment under consideration at mm-Wave frequency.