The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.

This paper examines the spatial variability of duty cycle in the GSM 900 and 1800 MHz bands within Kwara State, Nigeria. The results show spatial variance in the duty cycle with average occupancies of 1.67%, 17.76%, 10.55% and 0.39%, 11.00% and 5.11 in the rural, urban and all locations for 900 and 1800 MHz bands. Findings also show that there is very high positive correlation between rural 900/1800 MHz and urban 900/1800 MHz. But very high negative correlations exits between urban 900 and rural 1800, and urban 1800 and rural 1800. There is a weak and negative correlation between rural and urban 900 MHz, rural-urban 1800. These results clearly show the abundance of unutilised spectrum within the GSM bands. Therefore, regulatory commissions should adopt flexible spectrum reuse strategy to relax the regulatory bottlenecks to maximize the scarce radio resources in the licensed bands, especially for rural network deployments

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