Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction

M. Sousa, A. Martins, P. Vieira

Abstract

This paper presents a new approach for automatic detection of low coverage and high interference scenarios (overshooting and pilot pollution) in Universal Mobile Telecommunications System (UMTS) /Long Term Evolution (LTE) networks. These algorithms, based on periodically extracted Drive Test (DT) measurements (or network trace information), identify the problematic cluster locations and compute harshness metrics, at cluster and cell level, quantifying the extent of the problem. Future work is in motion by adding self-optimization capabilities to the algorithms, which will automatically suggest physical and parameter optimization actions, based on the already developed harshness metrics. The proposed algorithms were validated for a live network urban scenario. 830 3rd Generation (3G) cells were self-diagnosed and performance metrics were computed. The most negative detected behaviors regards high interference control and not coverage verification.

References

  1. Duarte, D., Vieira, P., Rodrigues, A. J., and Silva, N. (2015). A New Approach for Crossed Sector Detection in Live Mobile Networks based on Radio Measurements. In Wireless Personal Multimedia Communications Symp. - WPMC, volume 1.
  2. Ericsson (2015). Ericsson mobility report. Technical report, ERiCSSON.
  3. Izenman, A. J. (2008). Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning. Springer Publishing Company, Incorporated, 1 edition.
  4. Kysti, P., Meinil, J., Hentil, L., Zhao, X., Jms, T., Schneider, C., Narandzi, M., Milojevi, M., Hong, A., Ylitalo, J., Holappa, V., Alatossava, M., Bultitude, R., Jong, Y., and Rautiainen, T. (2007). Ist-4-027756 winner ii d1.1.2 v1.2. Technical report, EBITG, TUI, UOULU, CU/CRC, NOKIA.
  5. Sallent, O., Perez-Romero, J., Sanchez-Gonzalez, J., Agusti, R., Diaz-Guerra, M., Henche, D., and Paul, D. (2011). Automatic detection of sub-optimal performance in umts networks based on drive-test measurements. In Network and Service Management (CNSM), 2011 7th International Conference on, pages 1-4.
  6. Sanchez-Gonzalez, J., Sallent, O., Pérez-Romero, J., and Agustí, R. (2013). A multi-cell multi-objective selfoptimisation methodology based on genetic algorithms for wireless cellular networks. Int. Journal of Network Management, 23(4):287-307.
  7. Sousa, M., Martins, A., Vieira, P., Oliveira, N., and Rodrigues, A. (2015). Caracterizacao da Fiabilidade de Medidas Rádio em Larga Escala para Redes AutoOtimizadas. In 9. Congresso do Comité Portugueˆs da URSI - ”5G e a Internet do futuro” .
  8. Vieira, P., Silva, N., Fernandes, N., Rodrigues, A. J., and Varela, L. (2014). Improving Accuracy for OTD Based 3G Geolocation in Real Urban/Suburban Environments. In Wireless Personal Multimedia Communications Symp. - WPMC, volume 1.
  9. Witten, I. H. and Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  10. Zheng, N. and Xue, J. (2009). Statistical Learning and Pattern Analysis for Image and Video Processing. Advances in Pattern Recognition. Springer.
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Paper Citation


in Harvard Style

Sousa M., Martins A. and Vieira P. (2016). Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction . In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016) ISBN 978-989-758-196-0, pages 31-39. DOI: 10.5220/0005958300310039


in Bibtex Style

@conference{winsys16,
author={M. Sousa and A. Martins and P. Vieira},
title={Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016)},
year={2016},
pages={31-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005958300310039},
isbn={978-989-758-196-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016)
TI - Self-Diagnosing Low Coverage and High Interference in 3G/4G Radio Access Networks based on Automatic RF Measurement Extraction
SN - 978-989-758-196-0
AU - Sousa M.
AU - Martins A.
AU - Vieira P.
PY - 2016
SP - 31
EP - 39
DO - 10.5220/0005958300310039