son laboratory: a multi-technology radio network umts 2100,...

User and Traffic Distribution

Available Data

■ 2G Voice [Erl]

■ 2G Data [kb/s]

■ 3G Voice [Erl]

■ 3G Data [kb/s]

Intensity Distribution

■ User distribution based on

■ Land use class

■ Day of week

■ Time of day

■ Derived from real PM-data

Hannover Scenario The scenario covers an area of 20x24 km with the city of Hannover, Germany, at its centre. Individual

networks for GSM900/1800 and UMTS2100 have been planned on the basis of publicly available data

from the regulatory authority, publicly reported sites and typical network design assumptions.

The resulting networks consist of

■ GSM 900: 49 sites, 142 sectors, 560 TRXs (per sector min 1, avg 3.9, max 5)

■ GSM 1800: 72 sites, 214 sectors, 693 TRXs (per sector min 1, avg 3.2, max 5)

■ UMTS 2100: 72 sites, 214 sectors, 428 carriers (per sector 2)

Pathloss Predictions

Ray Optical Outdoor Predictions

The coverage of the individual cells has been predicted

By using a ray optical pathloss prediction model for

outdoor regions [1].

Outdoor-to-Indoor Predictions

Based on a “Ground Outdoor-to-Indoor” approach [2],

The indoor signal levels are derived from signal levels

at references points at the building boundary. The

reference points for an indoor pixel are the foots of the

dropped perpendiculars onto the building boundary.

Abstract The SON laboratory addresses the need for tools that analyze the behaviour and likely gains from

SON solutions under realistic conditions. At the core of the SON laboratory are high-performance

simulation engines that offer extensive system-level multi-RAT network performances analyzes for

medium- to large-scale scenarios using high-resolution signal predictions, realistic mobility models,

and real-world or realistic traffic data. The simulations within the SON laboratory employ loosely

coupled clients (using XML-RPC) either from MATLAB or via a custom API.

SON Laboratory: A Multi-Technology Radio Network Simulation Environment for the SON Analysis

Johannes Baumgarten², Andreas Eisenblätter¹, Thomas Jansen², Thomas Kürner², Dennis M. Rose², Ulrich Türke¹

¹atesio GmbH, Berlin, Germany ²Technische Universität Braunschweig | Institut für Nachrichtentechnik, Braunschweig, Germany

{eisenblaetter,tuerke}@atesio.de {baumgarten,jansen,kuerner,rose}@ifn.ing.tu-bs.de

Geometrical indoor prediction for ARFCN=985, h In

=7.50 m , h Out

=1.00 m

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SON Laboratory Set-Up and Demonstration

Observation Change Requests

UMTS 2100, Received Power

[dBm]-110

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[1] Kürner, T.; Schack, M.: "3D Ray-

Tracing Embedded Into an Integrated

Simulator for Car-to-X

Communications“. In Proc. of URSI

Commission B International

Symposium on Electromagnetic Theory

(EMTS), Berlin, August 2010.

[2] Rose, D. M.; Kürner, T.: "Outdoor-

to-Indoor Propagation – Accurate

Measuring and Modeling of Indoor

Environments at 900 and 1800 MHz“.

6th European Conference on Antennas

and Propagation (EUCAP), 2012, vol.,

no., pp.1440-1444, 26-30 March 2012.

Simulation Control

Simulation and time management

Matlab/Windows (Paris)

Network

Simulation

Platform

(NGPS)

Linux (Berlin)

Network Inspector

Observation of network state,

performance and changes;

Manual configuration changes

Matlab/Windows (Paris)

Energy Saving

Schedules ON/OFF for UMTS sites

Python/Linux (Berlin)

Cell Outage Management

Detection and compensation of UMTS

cell outages

Python/Linux (Berlin)

Scheduled/Random Changes

Unpromted changes of GSM and UMTS

network configuration

Python/Linux (Berlin)

XML RPC

XML RPC Energy Consumption Monitor

Matlab/Windows (Braunschweig)

Analysis of network

energy consumption