Abstract
Abstract A good wireless network design depends on technical and financial viability and a number of other criteria that must be met. Following the emergence of new technologies and services, such as 5G transmission and the reuse of frequencies, new work is being carried out to ensure a better design for a particular area. This study examines a discrete radio propagation model which employs the K nearest neighbors classifier. The model takes into account the different characteristics of the environment. This article presents a case study for the optimum positioning of base stations in Federal University of Para (Belem – Brazil), representing a typical Amazon environment. The mentioned scenario is heterogeneous, presenting edifications and considerable forest area. Measurement campaigns were conducted in three different frequencies for the design features of the model: 521 MHz (Brazilian digital TV system), 2100 MHz (Enhanced Data Rates for GSM Evolution), and 2600 MHz (Long Term Evolution). A study of the fading phenomenon in these frequencies was carried out to generalize the frequencies of application for the propagation loss model. When this model was ready, tests (computing simulations) were conducted in two scenarios to optimize the positioning of the radio base stations being studied.
Highlights
Wireless network planning takes account of a number of factors such as: average/low radiation intensity, optimum positioning of new antenna transmitters and suitable models for signal intensity prediction. To meet all these requirements at the same time, the new antennas have less power which results in a lower coverage area; this requires new studies of signal propagation [1]
These models are not suitable for signal prediction in cities where there is a combination of buildings and urban afforestation, like the environment examined in this study
The main contributions made by this article are as follows: 1) Received signal strength prediction modelling in any area of a map through a generalized model and adapted to Amazon environments; 2) A methodology for finding the best positioning for transmitters with a view to maximizing the signal strength received by the network users
Summary
Wireless network planning takes account of a number of factors such as: average/low radiation intensity, optimum positioning of new antenna transmitters and suitable models for signal intensity prediction. To meet all these requirements at the same time, the new antennas have less power which results in a lower coverage area; this requires new studies of signal propagation [1]. These models are not suitable for signal prediction in cities where there is a combination of buildings and urban afforestation, like the environment examined in this study. The main contributions made by this article are as follows: 1) Received signal strength prediction modelling in any area of a map through a generalized model and adapted to Amazon environments; 2) A methodology for finding the best positioning for transmitters with a view to maximizing the signal strength received by the network users
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