An adaptive neuro-fuzzy propagation model for LoRaWAN

This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the training complexity of artificial neural network (ANN)-based models. Therefore, the size of the training dataset is reduced by 70% compared to an ANN model. The proposed model consists of an efficient clustering method to identify the optimum number of the fuzzy nodes to avoid overfitting, and a hybrid training algorithm to train and optimize the ANFIS parameters. Finally, the proposed model is benchmarked with extensive practical data, where superior accuracy is achieved compared to deterministic models, and better generalization is attained compared to ANN models. The proposed model outperforms the nondeterministic models in terms of accuracy, has the flexibility to account for new modeling parameters, is easier to use as it does not require a model for propagation environment, is resistant to data collection inaccuracies and uncertain environmental information, has excellent generalization capability, and features a knowledge-based implementation that alleviates the training process. This work will facilitate network planning and propagation prediction in complex scenarios

Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion

With increasing population growth, the Harare Metropolitan Province has experienced accelerated land use and land cover (LULC) changes, influencing the city’s growth. This study aims to assess spatiotemporal urban LULC changes, the axis, and patterns of growth as well as drivers influencing urban growth over the past three decades in the Harare Metropolitan Province. The analysis was based on remotely sensed Landsat Thematic Mapper and Operational Land Imager data from 1984–2018, GIS application, and binary logistic regression. Supervised image classification using support vector machines was performed on Landsat 5 TM and Landsat 8 OLI data combined with the soil adjusted vegetation index, enhanced built-up and bareness index and modified difference water index. Statistical modelling was performed using binary logistic regression to identify the influence of the slope and the distance proximity characters as independent variables on urban growth. The overall mapping accuracy for all time periods was over 85%. Built-up areas extended from 279.5 km2 (1984) to 445 km2 (2018) with high-density residential areas growing dramatically from 51.2 km2 (1984) to 218.4 km2 (2018). The results suggest that urban growth was influenced mainly by the presence and density of road networks

Capacity Dimensioning of HSDPA Urban Network

To launch a cellular network, prelaunch capacity dimensioning is performed which includes coverage estimation and throughput prediction. Cellular companies in developing countries like Pakistan are only providing 2G services, while 3G services are yet to be launched. Although a lot of research has been done on 3G services in developed countries but there is very little knowledge regarding practical aspects of planning and optimization of 3G networks in third world countries like Pakistan. This research paper includes a thorough analysis of factors that affect capacity of 3G networks, including radio propagation models. Various propagation models are studied and propagation constants of Standard Propagation Model are tuned according to topography of Islamabad. The performance analysis of these propagation models is done using Matlab and results are verified through planning tool Atoll and field measurements. Based on analysis of these results capacity dimensioning, in terms of number of sites, is carried out for an urban network of Islamabad

Mehanizmi prostiranja radio vala i empirijski modeli za fiksne radijske pristupne sustave

This paper provides a survey of the basic mechanisms which influence the propagation of electromagnetic waves at most. It also deals with features of empirical models often used in a process of fixed wireless access network planning and implementation. Four empirical models, SUI, COST 231-Hata, Macro and Ericsson, which are most suitable for path loss prediction for such a system, are presented. By using these propagation models the receiving signal levels are predicted for different types of environment for a WiMAX (Worldwide Interoperability for Microwave Access) system installed in the city Osijek, Croatia. Measurement results of receiving WiMAX power at 3,5 GHz are also presented and compared with the results predicted by using the propagation models.Ovaj rad daje pregled osnovnih mehanizama koji najviše utječu na prostiranje elektromagnetskih valova. Također se bavi značajkama empirijskih modela koji se često koriste u procesu planiranja i implementacije fiksnih radijskih pristupnih mreža. Predstavljena su četiri empirijska modela koja najbolje odgovaraju za predviđanje gubitaka za ove sustave: SUI, COST 231- Hata, Macro i Ericsson model. Korištenjem ovih modela prostiranja napravljena je predikcija razine prijemnog signala za različite tipove okruženja za WiMAX (eng. Worldwide Interoperability for Microwave Access) sustav postavljen u gradu Osijeku, u Hrvatskoj. Predstavljeni su i rezultati mjerenja prijemne snage WiMAX sustava na 3,5 GHz te su uspoređeni s rezultatima predviđenim uporabom modela prostiranja

Radio Frequency Propagation Mechanisms and Empirical Models for Hilly Areas

Achieving better network performance is a paramount concern in wireless networks. This paper provides a survey of the basic mechanisms which influence the propagation of electromagnetic waves in hilly areas. Three empirical models: COST231-Hata, Okumura-Hata and Egli which are suitable for path loss prediction for such area are presented. By using these propagation models the broadcast signal strength are predicted for this type of environment. Measurement results of signal strength in UHF band obtained in Idanre Town of Ondo State Nigeria are presented and compared with the results predicted by using the propagation models. A modified COST231-Hata radiowave propagation model was developed and implemented with Matlab GUI (Graphical User Interface) for simulation. The model developed has 93.8% accuracy.DOI:http://dx.doi.org/10.11591/ijece.v3i3.251