Interference map estimation using spatial interpolation of MDT reports in cognitive radio networks

Naranjo, Juan Diego; Ravanshid, Azad; Viering, Ingo; Halfmann, R.; Bauch, Gerhard

doi:10.1109/wcnc.2014.6952411

Cited by 14 publications

(8 citation statements)

References 8 publications

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“…Other comparative studies in various aspects of different interpolation techniques for constructing (IC) or (REM) can be found in [38], [40], [35], [41] and [42].…”

Section: Comparative Studies Of Direct Methodsmentioning

confidence: 99%

Indirect Methods for Constructing Radio Environment Map

Alfattani

Yonzacoglu

2018

2018 IEEE Canadian Conference on Electrical &Amp; Computer Engineering (CCECE)

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To solve the spectrum scarcity problem caused by the high number of wireless applications and users, the concept of cognitive radio (CR) was proposed in the past few years. Cognitive radio networks (CRNs) provide dynamic spectrum access (DSA), where the unlicensed users can access the spectrum without causing unacceptable level of interference to the primary user (PU). DSA was based on conventional spectrum sensing information or geolocation databases. Later, radio environment map (REM) as an improved geolocation database was introduced to enhance the DSA process. It is a comprehensive map consists of different integrated databases, and the interference field information is one of its databases.

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“…Other comparative studies in various aspects of different interpolation techniques for constructing (IC) or (REM) can be found in [38], [40], [35], [41] and [42].…”

Section: Comparative Studies Of Direct Methodsmentioning

confidence: 99%

Indirect Methods for Constructing Radio Environment Map

Alfattani

Yonzacoglu

2018

2018 IEEE Canadian Conference on Electrical &Amp; Computer Engineering (CCECE)

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“…Authors in [25] use regression clustering for construction of received signal strength maps from a sparse set of MDT measurements. The authors in [26] analyze the performance of selected spatial interpolation techniques used in the estimation of interference produced by an LTE-Advanced network. The authors in [27] provide a visualization method based on inverse distance weighted interpolation that shows every point of the received data as a heatmap.…”

Section: ) Data Sparsity Onlymentioning

confidence: 99%

“…The authors in [27] provide a visualization method based on inverse distance weighted interpolation that shows every point of the received data as a heatmap. Another work [28] investigates several classical interpolation methods to reconstruct interference maps in cognitive radio networks. Authors in [29] propose a new technique, called Fixed Rank Kriging that is superior in terms of computational complexity as compared to Kriging.…”

Section: ) Data Sparsity Onlymentioning

confidence: 99%

“…This calls for an optimization of bin width that would minimize the overall error under positioning error constraints. The errors in (4), (10) and (28) can have an upper bound of greater than 1. In order to get a bounded measure between 0 and 1 of these errors and to enable comparison of combined quantization and user positioning error with matrix recovery error, we define new bounded error measures based on the relative error measures as follows:…”

Section: B Determining Optimal Bin Widthmentioning

confidence: 99%

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Enhanced MDT-Based Performance Estimation for AI Driven Optimization in Future Cellular Networks

2020

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Minimization of drive test (MDT) allows coverage estimation at a base station by leveraging measurement reports gathered at the user equipment (UE) without the need for drive tests. Therefore, MDT is a key enabling feature for data and artificial intelligence driven autonomous operation and optimization in future cellular networks. However, to date, the utility of MDT feature remains thwarted by issues such as sparsity of user reports and user positioning inaccuracy. We characterize three key types of errors in MDT-based coverage estimation that stem from inaccurate user positioning, scarcity of user reports and quantization. For the first time, the presented analysis shows existence of joint interplay between these errors on coverage estimation that result from inter-dependency between positioning error and bin width. The analysis also shows that there exists an optimal bin width for given user positioning inaccuracy and user density that minimizes the overall error in MDT-based estimated coverage. Utility of our framework is presented by addressing two applications from network optimization perspective: determining optimal bin width to maximize accuracy of MDT-based coverage estimation and its calibration to further improve its accuracy. INDEX TERMS Minimization of drive test, autonomous coverage estimation, optimal bin width, sparse data, coverage calibration, data driven optimization

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“…The solution given by (3) implies finding N parameters from N observations which can be computationally expensive for large data sets. Moreover, Φ is not always invertible.…”

Section: System Modelmentioning

confidence: 99%

Spectrum cartography using adaptive radial basis functions: Experimental validation

Idsøe

Hamid

Jordbru

et al. 2017

2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The performance of adaptive RBFs based spectrum cartography is shown through measurements using a universal software radio peripheral, a customized node and LabView framework. The obtained results verify the ability of adaptive RBF to construct spectrum maps with an acceptable performance measured by normalized mean square error (NMSE).

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Interference map estimation using spatial interpolation of MDT reports in cognitive radio networks

Cited by 14 publications

References 8 publications

Indirect Methods for Constructing Radio Environment Map

Indirect Methods for Constructing Radio Environment Map

Enhanced MDT-Based Performance Estimation for AI Driven Optimization in Future Cellular Networks

Spectrum cartography using adaptive radial basis functions: Experimental validation

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