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