The indirect self-tuning method for constructing radio environment map using omnidirectional or directional transmitter antenna

Pesko, Marko; Javornik, Tomaž; Vidmar, Luka; Košir, Andrej; Štular, Mitja; Mohorčič, Mihael

doi:10.1186/s13638-015-0297-2

Cited by 27 publications

(8 citation statements)

References 16 publications

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“…In this paper, the proposed algorithm was compared with three kinds of mainstream algorithms, which are IDW [14-17, 20, 21, 24], Spline [16,20,25], and Kriging [11][12][13][14][15][16][17][18][19][20][21]. We tested them on two kinds of data sets and analyzed the performance of the algorithms through a variety of objective evaluation indexes.…”

Section: Experimental Classification Results and Analysismentioning

confidence: 99%

“…The Kriging method is a method based on the spatial analysis of a variogram, which is an unbiased optimal estimation of regionalized variables over a finite area, and is considered to be the best method for estimating the parameters of the radio environment map [11][12][13][13][14][15][16][17][18][19][20][21]. The Kriging method is divided into ordinary Kriging and universal Kriging depending on the existence of space field drift.…”

Section: Related Workmentioning

confidence: 99%

“…In this paper, we call it radio environment map parameter estimation. This problem, especially since 2012, has been increasingly studied in depth [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Parameter Estimation for the Field Strength of Radio Environment Maps

Gao

Xie

2017

Wireless Communications and Mobile Computing

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The parameters of a radio environment map play an important role in radio management and cognitive radio. In this paper, a method for estimating the parameters of the radio environment map based on the sensing data of monitoring nodes is presented. According to the principles of radio transmission signal intensity losses, a theoretical variogram model based on a propagation model is proposed, and the improved theoretical variation function is more in line with the attenuation of radio signal propagation. Furthermore, a weight variogram fitting method is proposed based on the characteristics of field strength parameter estimation. In contrast to the traditional method, this method is more closely related to the physical characteristics of the electromagnetic environment parameters, and the design of the variogram and fitting method is more in line with the spatial distribution of electromagnetic environment parameters. Experiments on real and simulation data show that the proposed method performs better than the state-of-the-art method.

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Section: Experimental Classification Results and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Parameter Estimation for the Field Strength of Radio Environment Maps

Gao

Xie

2017

Wireless Communications and Mobile Computing

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“…The incorporation of directional antenna modeling is possible to make the model more practical, but it increases the simulation complexity. Actually, it is important to mention that the directional antenna transmission impacts the radio parameter estimation and can consequently affect the performance of spatial predictions [79][80]. The trend estimation is presented in Fig.3(d), which shows a comparison between the theoretical average path loss model and the result of trend estimation along with average path loss measurements contaminated with shadowing of the wireless channel.…”

Section: A Radio Spatial Prediction Model Simulationmentioning

confidence: 99%

On Geostatistical Methods for Radio Environment Maps Generation under Location Uncertainty

Augusto

Panazio

2018

JCIS

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Radio environment map (REM) can provide important information for designing and optimizing the performance of wireless communication networks. However, the location uncertainty related to the measurements used to build the REM can considerably deteriorate the accuracy of such map. This paper addresses this problem by proposing a modified approach of a classical geostatistical prediction tool, named Kriging method, which incorporates the location uncertainty and is able to improve the REM accuracy without adding significant complexity. Finally, we also show through simulation results that the average path loss and covariance parameter estimation play an important role and should be considered when the location errors occur in the wireless communication systems.

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“…Parts of the research outputs of this project focus on constructing radio environment maps using various spatial inference techniques [299].…”

Section: A Spectrum-related Experimentation Projectsmentioning

confidence: 99%

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Ding

Jiao

Wang

et al. 2018

IEEE Commun. Surv. Tutorials

159

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Abstract-Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the 5th generation mobile communications (5G) and next generation high frequency (HF) communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.

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The indirect self-tuning method for constructing radio environment map using omnidirectional or directional transmitter antenna

Cited by 27 publications

References 16 publications

Parameter Estimation for the Field Strength of Radio Environment Maps

Parameter Estimation for the Field Strength of Radio Environment Maps

On Geostatistical Methods for Radio Environment Maps Generation under Location Uncertainty

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

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