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EN
Propagation is an essential factor ensuring good coverage of wireless communications systems. Propagation models are used to predict losses in the path between transmitter and receiver nodes. They are usually defined for general conditions. Therefore, their results are not always adapted to the behavior of real signals in a specific environment. The main goal of this work is to propose a new model adjusting the loss coefficients based on empirical data, which can be applied in an indoor university campus environment. The Oneslope, Log-distance and ITU models are described to provide a mathematical base. An extensive measurement campaign is performed based on a strict methodology considering different cases in typical indoor scenarios. New loss parameter values are defined to adjust the mathematical model to the behavior of real signals in the campus environment. The experimental results show that the model proposed offers an attenuation average error of 2.5% with respect to the losses measured. In addition, comparison of the proposed model with existing solutions shows that it decreases the average error significantly for all scenarios under evaluation.
PL
W artykule zaprezentowano prototyp dwuzakresowej, wieloprotokołowej stacji bazowej do zastosowań w systemach inteligentnego opomiarowania zużycia mediów. Wykorzystując takie techniki jak: automatyczna adaptacja warstwy fizycznej, wielopasmowość (169 MHz i 868 MHz), technikę SDR oraz autorski, wąskopasmowy protokół transmisji danych, uzyskano poprawienie zasięgu łącza radiowego bez zwiększenia kosztów liczników mediów. Dzięki autonomicznemu systemowi odczytu możliwy jest ciągły monitoring zużycia mediów oraz instalacji do ich przesyłu.
EN
This paper presents a designed prototype of a two-band multi-protocol base station for smart-metering applications. Using such techniques as the automatic physical layer adaptation, multi band design (169 MHz and 868 MHz), SDR technique and custom radio protocol, we have increased radio coverage without increasing cost of smart meters. Thanks to the autonomous readouts, constant monitoring of smart-metering system is allowed.
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tom Vol. 22
261--270
EN
This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed.The output of this research helps finding an optimised and accurate model for coverage prediction.
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