Outdoor-To-Indoor Power Prediction for 768 MHZ Wireless Mobile Transmission Using Multilayer Perceptron

Moura, Matheus B.; Vidal, Daniel; Schueler, Carla; Matos, Leni; Ferreira, Tadeu N.

doi:10.1109/ijcnn.2018.8489221

Cited by 7 publications

(9 citation statements)

References 7 publications

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“…Moura et. al [5] applied artificial neural networks to narrowband data measured on a wireless indoor mobile communications scenario for 768 MHz outdoor transmission, in which the vegetation effect was embedded, confirming the advantage of using multilayer perceptron (MLP) neural networks for predicting coverage. With the same data of [5], Ribeiro et.…”

Section: Introductionmentioning

confidence: 90%

“…al [5] applied artificial neural networks to narrowband data measured on a wireless indoor mobile communications scenario for 768 MHz outdoor transmission, in which the vegetation effect was embedded, confirming the advantage of using multilayer perceptron (MLP) neural networks for predicting coverage. With the same data of [5], Ribeiro et. al [6] analyzed the signal variability in this channel and besides this, with data obtained through wideband measurements in the same scenario and carrier, results for time dispersion parameters as average delay and RMS delay spread for the indoor channel in several floors with outdoor transmission are provided.…”

Section: Introductionmentioning

confidence: 90%

“…The metric used for the error between the experimental (f(x)) and the theoretical (g(x)) probability density function (p.d.f.) of the small-scale signal is L 1 , defined as [5]:…”

Section: B Narrowband Characterizationmentioning

confidence: 99%

“…An omnidirectional antenna was installed on a mobile stand and a RG213 cable led the received signal to the input of a low noise amplifier (LNA), polarized by the 5 V source. The LNA was connected to the MS 2692A, which was used as a spectrum analyzer acquiring 123 samples/second (= 40 v/[5]) of the received CW for the narrowband sounding, and as a signal analyzer capturing "I" (in-phase) and "Q" (quadrature) samples…”

mentioning

confidence: 99%

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Influence of Vegetation on the Outdoor-to-Indoor Mobile Radio Propagation in 700 MHz Band

Ribeiro

Matos

Castellanos

et al. 2019

J. Microw. Optoelectron. Electromagn. Appl.

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Starting from outdoor transmission, crossing vegetation, the wideband and narrowband characterization of the indoor mobile radio channel in the 700 MHz band is obtained from experiments carried out in the indoor environment of the Engineering building at Fluminense Federal University, and from the processed data, respectively, the power-delay profiles obtained permitted to calculate the time dispersion parameters and the envelope of the signal permitted to adjust probability density functions to the signal variability, concluding about the influence of vegetation on those characteristics.

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Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 90%

“…The metric used for the error between the experimental (f(x)) and the theoretical (g(x)) probability density function (p.d.f.) of the small-scale signal is L 1 , defined as [5]:…”

Section: B Narrowband Characterizationmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Influence of Vegetation on the Outdoor-to-Indoor Mobile Radio Propagation in 700 MHz Band

Ribeiro

Matos

Castellanos

et al. 2019

J. Microw. Optoelectron. Electromagn. Appl.

Self Cite

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“…It is shown that ANNs are, in general, performing better in comparison with other regression methods [37] and it can be considered as a more flexible method [38] that is acceptable from time standpoint. MLP can be considered as the most used type of ANN [39] due to high performance from the standpoint of regression [40,41] and classification [42,43]. Because of these reasons, the aim of this research is to find a suitable solution to MLP model selection problem, that is applicable to prediction of CCPP electrical power output.…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation

et al. 2019

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In this paper a genetic algorithm (GA) approach to design of multi-layer perceptron (MLP) for combined cycle power plant power output estimation is presented. Dataset used in this research is a part of publicly available UCI Machine Learning Repository and it consists of 9568 data points (power plant operating regimes) that is divided on training dataset that consists of 7500 data points and testing dataset containing 2068 data points. Presented research was performed with aim of increasing regression performances of MLP in comparison to ones available in the literature by utilizing heuristic algorithm. The GA described in this paper is performed by using mutation and crossover procedures. These procedures are utilized for design of 20 different chromosomes in 50 different generations. MLP configurations that are designed with GA implementation are validated by using Bland - Altman (B-A) analysis. By utilizing GA, MLP with five hidden layers of 80,25,65,75 and 80 nodes, respectively, is designed. For aforementioned MLP, k - fold cross-validation is performed in order to examine its generalization performances. The Root Mean Square Error ( R M S E ) value achieved with aforementioned MLP is 4.305 , that is significantly lower in comparison with MLP presented in available literature, but still higher than several complex algorithms such as KStar and tree based algorithms.

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Self-learning Constellation Mapping Method Based on Neural Networks

Luo

2020

2020 7th International Conference on Information Science and Control Engineering (ICISCE)

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Outdoor-To-Indoor Power Prediction for 768 MHZ Wireless Mobile Transmission Using Multilayer Perceptron

Cited by 7 publications

References 7 publications

Influence of Vegetation on the Outdoor-to-Indoor Mobile Radio Propagation in 700 MHz Band

Influence of Vegetation on the Outdoor-to-Indoor Mobile Radio Propagation in 700 MHz Band

Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation

Self-learning Constellation Mapping Method Based on Neural Networks

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