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Content archived on 2024-05-24

MOdels and siMulations for nEtwork plaNning and conTrol of UMts


UMTS (Universal Mobile Telecommunication System) is a complex, large-scale network; it involves huge investments, worldwide mobile networks an brand new services. For today's operators, it is of utmost importance to have a cost-efficient and reliable network. The current project is triggered by the lack of suitable tools for real-time simulation of these large-scale UMTS networks; a large number of flexible models for e.g. user-behaviour, resource management and propagation are developed and enhanced, and implemented in a dynamic real-time simulator. Based on the simulation results, a cascade of simpler and faster tools is developed, suited for the practice of tomorrow's operator, and aiming at a cost-efficient and reliable network planning.

MOMENTUM aims at a long lasting impact on the development of UMTS planning tools. Major players of system manufacturers, network operators, service providers, and operations research facilities have joined to meet the challenge of analysing UMTS system-behaviour and of developing powerful new planning methods for UMTS.MOMENTUM will:
(i) characterise new services UMTS is going to deliver;
(ii) build usage profiles and planning scenarios to model future demands;
(iii) build the most advanced UMTS real-time system level simulator;
(iv) use the scenarios and the simulator to better understand the dynamics of UMTS networks and their sensitivity to system parameter settings;
(v) develop flexible models, algorithms, and new planning methods for the deployment of the future wireless telecommunication infrastructure;
(vi) build and publish a library of UMTS scenarios and test cases to be used as a benchmark in the development of planning tools.

Work description:
The two key questions in UMTS network planning are:
- Which time- and location-variant demand distribution for mobile users is to be expected?
- How well does a given network configuration satisfy this demand?

MOMENTUM addresses the first question by defining flexible discrete and probabilistic models for the resource demand of various service types, together with expected user mobility patterns.

MOMENTUM addresses the second question at three levels:
- The most accurate performance evaluation will be possible by means of a dynamic real-time system-level simulator to be developed. This simulator will supersede previous simulators by being capable of handling large-scale models and by taking most dynamic aspects of UMTS into account, including radio resource management and users' behaviour. To achieve this goal, the simulator is specifically designed to run on massive parallel super-computers and workstation clusters;
- For every-day planning purposes a fast and simple commercially available snapshot simulator will be tuned to fit the results of the dynamic simulator best possible;
- During automatic planning, tens of thousand configurations need to be considered. An even faster evaluation with heuristic rules is required in this context. Such rules will be identified.

Using the dynamic simulator, MOMENTUM will investigate into the optimisation of Quality-of-Service by tuning radio resource management parameters, such as call admission control, radio resource reservation policies, scheduling, traffic shaping, and macro diversity.

Radio wave propagation and interference also affect system performance. MOMENTUM will investigate which of the existing wave propagation models can best be used for UMTS and how interference may be predicted. With the ability to evaluate a network configuration, systematic planning methods can be developed. MOMENTUM will exploit the heuristic evaluation rules to design algorithms for new automatic planning tools.

- Development of flexible UMTS service models;
- analysis of traffic mixtures on radio interface;
-implementation of distributed dynamic real-time UMTS system-level simulator;
- study on impact of radio resource management on network performance;
- rules to mimic a dynamic simulator using commercially available snapshot simulators;
- models, algorithms, and heuristics for radio network planning;
- public electronic library of scenarios and test cases;
- workshops, conference presentations, scientific articles.
- Characterisation of mobile broadband services, including a procedure to generate> their spatial demand distribution, based on market insights and demographical factors> mobility grids, based on pixel and vector data;

WP2:- A novel snapshot-based simulation approach for UMTS radio network performance evaluation > Traditional static (Monte-Carlo) simulations are enhanced and combined with "Short-Term Dynamic" (STD) simulations. > This combination allows achieving statistics on QoS parameters that were previously only obtainable from dynamic system-level simulations.
- New pixel-based mobility model to introduce mobility in dynamic simulations
- New model and operational procedure to include the effect of mobility on the spread of demand, based on mobility grids and busy hour call arrival grids;

- Development of a powerful parallel simulation environment that enables UMTS network performance evaluation > level of certain system detail can be balanced against required simulation time to obtain reliable results
- A number of radio resource management algorithms and policies are implemented, and studied on their impact on network performance > in certain cases, preferable settings are derived;

- Implementation of the first fully adaptive model for wave propagation simulation > simpler model is submitted to ITU-R
- Development of tool for automatic planning of UMTS RF network configuration, including several heuristics for evaluation of UMTS network performance in order to short-cut simulation computing times > novel methodologies for network synthesis;

- Definition of integral public reference scenarios for UMTS networks, specifying in full detail all aspects of service demand, and service, terminal and network characterisation > data is provided in newly developed generic XML format.

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Participants (7)