Multidimensional Big Spatial Data Modeling Through a Case Study: LTE RF Subsystem Power Consumption Modeling

Multidimensional Big Spatial Data Modeling Through a Case Study: LTE RF Subsystem Power Consumption Modeling

F. Antón Castro D. Musiige D. Mioc V. Laulagnet 

National Space Institute, Technical University of Denmark, Elektrovej 328, 2800 Kgs. Lyngby, Denmark

Micromove.com, Frederikskaj 10, 2450 Copenhagen SV, Denmark

Page: 
208-219
|
DOI: 
https://doi.org/10.2495/DNE-V11-N3-208-219
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

This paper presents a case study for comparing different multidimensional mathematical modeling methodologies used in multidimensional spatial big data modeling and proposing a new technique. An analysis of multidimensional modeling approaches (neural networks, polynomial interpolation and homotopy continuation) was conducted for finding an approach with the highest accuracy for obtaining reliable information about a cell phone consumed power and emitted radiation from streams of measurements of different physical quantities and the uncertainty ranges of these measure ments. The homotopy continuation numerical approach proved to have the highest accuracy (97%). This approach was validated against another device with a different RF subsystem design. The approach modelled the power consumption of the validation device with an accuracy of 98%.

Keywords: 

big spatial data, haskell, homotopy continuation, interval analysis, mathematical modeling.

  References

[1] Juditsky, A., Hjalmarsson, H., Benveniste, A., Delyon, B., Ljung, L., Sjo¨berg, J. & Zhang, Q., Nonlinear black-box models in system identification: mathematical foundations. Automatica, 31(12), pp. 1725–1750, 1995.

http://dx.doi.org/10.1016/0005-1098(95)00119-1

[2] Palancz, B., Awange, J.L., Zaletnyik, P. & Lewis, R.H., Linear homotopy solution of nonlinear systems of equations in geodesy. Journal of Geodesy, 84(1), pp. 79–95, 2010. http://dx.doi.org/10.1007/s00190-009-0346-x

[3] Kolmogorov, A.N., On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition. American Mathematical Society Translations, 28(28), pp. 55–59, 1963.

[4] Bishop, C.M., Pattern Recognition and Machine Learning, Springer, pp. 33–38, 2006.

[5] Musiige, D., Laulagnet, V., Anton, F. & Mioc, D., LTE RF subsystem power consumption modeling. The 1st IEEE Global Conference on Consumer Electronics 2012 (IEEE GCCE 2012), Tokyo, Japan, pp. 654–658, 2012.

http://dx.doi.org/10.1109/gcce.2012.6379941

[6] ETSI, 3GPP Technical specification 36.101. V8.8.0 edition, (2009–12). [7]  ETSI, 3GPP Technical Specification 36.211. V8.9.0 edition, 2009.

[8] Allgower, E.L. & Georg, K., Numerical Continuation Methods: An Introduction. SpringerVerlag: New York, NY, USA, 1990. http://dx.doi.org/10.1007/978-3-642-61257-2