Measurement and Prediction of Short-Range Path Loss between 27 and 40 GHz in University Campus Scenarios

Ramos, Glaucio Lopes; Vargas, Carlos; Mello, Luiz da Silva; Pereira, Paulo; Vieira, Robson D.; Gonçalves, Sandro; Rego, C.G.

doi:10.14209/jcis.2021.20

Cited by 2 publications

(4 citation statements)

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“…We propose two extended empirical models based on the ABG and CIF using the vegetation profile and heigth difference between the transmitter and receiver as predictors for comparison with the ML models. We also compare the results of the obtained models with the study proposed in [150] based on the Fuzzy technique derived from the measurement campaign employed in this chapter. Finally, we analyze the generalization capacity of the model to assess the performance of the ML and empirical models.…”

Section: Chapter 4 Path Loss Prediction For Mmwave Outdoor Communicat...mentioning

confidence: 99%

“…Table 4.5 shows the final model comparison for both the training and testing sets. In the last row in Table 4.5, we include the results for the Fuzzy clustering model reported in [150] for comparison.…”

Section: Final Models Comparisonmentioning

confidence: 99%

“…The work in [150] presents a Fuzzy technique based on the subtracting clustering algorithm to predict the PL. The approach uses data from the same measurement campaign described in this chapter.…”

Section: Final Models Comparisonmentioning

confidence: 99%

“…However, the authors did not provide detailed information about the train-test split technique employed and the allocation of samples to each set. The Fuzzy model in [150] an RMSE of 2.20 dB for the PL prediction on the testing set for the multifrequency case. The RMSE value is very similar compared to the proposed ABG∆ h , v depth and CIF∆ h , v depth models, with values of 2.52 dB and 2.54 dB, respectively.…”

Section: Final Models Comparisonmentioning

confidence: 99%

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On Machine Learning Techniques Toward Path Loss Modeling in 5g and Beyond Wireless Systems

ELEDUVITH NUNEZ RUIZ

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I would like to express my sincere gratitude to my co-advisor, Professor Lisandro Lovisolo, for his insightful suggestions, enthusiasm, and always being there when I needed his support. This work would not have been possible without his guidance.I would like to acknowledge and thank my family, my parents, my brother, and his wife. They always encouraged me and believed in me.I would like to thank my colleagues at PUC-Rio and CETUC, especially Johnes Ricardo, for their sincere friendship and assistance. A special appreciation to Prof. Guilherme Temporão, Marcelo Balisteri, and Marta Pudwell for their valuable support in the final stage of this journey.I would like to thank my colleagues from the Radio-Propagation Laboratory, CETUC, Carlos Orihuela, Marcelo Molina, Carlos Rodriguez, and Professor Glaucio Lopes, for helping me process the datasets from the measurement campaigns used in this research and always being there when I needed their support.A special appreciation and dedication to my husband Jorge for all the encouragement, love, patience, source of inspiration, and technical support he gave me during this journey. For always looking after my well-being.

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Section: Chapter 4 Path Loss Prediction For Mmwave Outdoor Communicat...mentioning

confidence: 99%

Section: Final Models Comparisonmentioning

confidence: 99%

Section: Final Models Comparisonmentioning

confidence: 99%

Section: Final Models Comparisonmentioning

confidence: 99%

See 2 more Smart Citations