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Self-Organizing Networks: Self-Planning, Self-Optimization and Self-Healing for GSM, UMTS and LTE by Khalid Hamied, Juan Ramiro

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Appendix B

X-Map Estimation for LTE*

Michaela Neuland, Mehdi Amirijoo and Thomas Kürner

B.1. Introduction

Information about the radio coverage is essential for network planning, RF tuning, and Radio Resource Management (RRM) parameters optimization. Nowadays, network operators use prediction tools to produce this information. These tools are based on maps providing topographic and land use information (e.g. buildings, natural areas and roads), as well as on tuned propagation models. However, this approach is not fully accurate. Reasons for the inaccuracies are imperfections in the used geographic data, simplifications or approximations in the applied propagation models, and changes in the environment caused by, for example, constructions/demolitions or seasonal effects (foliage changes). Furthermore, variations in the traffic distribution and user profiles are a source for inaccurate results provided by prediction tools. For this reason, rigorous drive tests are performed in order to get more information about the real situation in the network and to gather measurement data for calibrating the used propagation models. Drive tests provide a picture of the end user perception in the field and enable the operator to identify locations causing poor performance and their corresponding cause (e.g. incorrect tilt or handover settings). Drive tests are, however, not ideal since they are expensive, time-consuming and cover only a limited (outdoor) part of the network due to access ...

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