A Development Platform for the Design and Optimization of Mobile Radio Networks Jürgen Deissner, Gerhard Fettweis, Jörg Fischer, Dietrich Hunold, Jens Voigt Endowed Chair for Mobile Communications Systems Ralf Lehnert, Mathias Schweigel, Jörg Wagner Telecommunications Chair Communications Laboratory, Dresden University of Technology, D-01062 Dresden, Germany E-mail: {deissner | fettweis | fischer | hunold | voigtje | lehnert | schweige | wagner}@ifn.et.tu-dresden.de Andreas Steil Mannesmann Mobilfunk GmbH, Am Seestern 1, 40453 Düsseldorf, Germany E-mail:
[email protected]
Abstract The rapidly increasing traffic demand from mobile users forces network operators and service providers to extend and optimize existing networks as well as to plan entirely new mobile radio networks. Current planning methods rely on static coverage prediction. The optimization is partly based on measurements and gathered experiences in connection with empirical methods. However, these methods do not adequately take the complexity and, especially, the dynamics of a mobile radio network into account. In contrast, the presented development platform for the design and optimization of mobile radio networks comprises a modular and generic dynamic system simulator WiNeS (Wireless Network System Simulator). This is conducted simultaneously with a closed concept for the configuration as well as visualization and animation of all important aspects of the mobile radio networks being investigated by use of the simulator. Therefore, this development platform is an effective tool to support the design and optimization of future mobile radio networks.
1
Motivation
Mobile radio networks generally dispose of a limited number of radio resources which have to be assigned to the users in a manner as efficient as possible. In case of incomplete orthogonality, the resources interfere with each other, thereby reducing the network’s capacity and quality. Hence, the network planning and optimization leads to the problem of performing an interference analysis in order to find an optimal network configuration [1] [2]. Thereby, the manifold dynamics of mobile radio net-
works have to be taken into account. The users are moving and therefore, the network access points are changing by handovers. There is a growing use of new services with heterogeneous traffic profiles and of adaptive air interfaces. Since it is essential to take all these characteristics into consideration, dynamic system simulations based on stochastic models is the appropriate means for the analysis of mobile radio networks. Existing simulators limit the investigation of mobile radio networks for several reasons: • They only rudimentarily include the dynamics of mobile radio networks (e.g. OPNET by MIL3 Inc.1). • They are confined to single mobile radio systems or components (e.g. DESI, GOOSE, SIMCO by RWTH Aachen2) or they are proprietary simulation tools of single system manufacturers. • They are focused on aspects other than the interference-related capacity and quality of a radio network, e.g. on the protocol level (e.g. SDT3, METWERK4 by Telelogic AB). Additionally, most of these tools do not simultaneously provide the engineer with a development platform that supports an effective handling of the simulator. A quality user-interface is also not provided for the extensive configuration, status, and result data of the mobile radio network simulations. In order to overcome these limits a new approach is required which leads to the idea of a development plat1. 2. 3. 4.
http://www.mil3.com/products/modeler/ home.html http://www.comnets.rwth-aachen.de/ http://www.telelogic.se/solution/tools/ sdt.asp http://www.comnets.rwth-aachen.de/project/metwerk/
form for mobile radio networks. A solution is presented in this paper along with the tool demonstration at the conference.
2
A Development Platform for Mobile Radio Networks
In order to cope with the task that we described above a simple simulator is not sufficient. The large variety of parameters of a mobile radio network requires a flexible and easy-to-use, but also extensive configuration. The output data is also versatile and has to be illustrated appropriately. That is why the simulator is additionally comprised of a configurator and an animator (Fig. 1). The configurator and the animator are the user interface of the development platform. Through the use of the configurator, the simulator and the animator can be configured (simulation layout, network layout, general parameters etc.) and controlled. The animator is dedicated to the graphical visualization of any data. It also enables a graphically supported on-line configuration of the simulation.
3
Wireless Network System Simulator (WiNeS)
The Wireless Network System Simulator (WiNeS) (the shaded part including the WiNeS kernel in Fig. 1) has a modular structure and supports both the reusability of models and a way of modeling which is, to a great extent, independent from the simulation technique. The simulator consists of the primary WiNeS kernel, the simulation control and one or more system modules, each of which implements the functionality of a mobile radio system. [3] Due to the complexity of mobile radio networks the modeling is focussed on the system level, i.e. all functions for the management and use of radio resources through an interference analysis of a whole mobile radio network with a time resolution that corresponds to the length of data packets or frames. The characteristics of the link level and the protocol level are represented on the system level, but not modeled in the same extent and detail as the system level.
3.1
WiNeS Kernel
As the basis for a generic software implementation, we performed an object-oriented analysis for the mobile
Configurator
Ptolemy GUI
System Modules
Animator
GSM 60 GHz
(Java)
WiNeS Kernel
IBMS
UMTS
WiNeS (C++)
Fig. 1
Simulation Control
Ptolemy Discrete-Event Domain
Structure of the development platform for the design and optimization of mobil radio networks
radio systems to be investigated [4]. The WiNeS kernel maps the designed [abstract] class structure to software. Additionally, the WiNeS kernel defines all internal interfaces of the simulator as well as all external interfaces to the configurator and animator. In particular, these interface definitions realize the decoupling of the WiNeS kernel from a specific system module and from the simulation control. This guarantees the interchangeability of the system modules from within the simulator. Furthermore, it allows the addition of future system modules with no change to the WiNeS kernel. Moreover, the simulation control can be easily replaced by another, and the model is capable of handling multiple simulation machines in the future. Altogether the WiNeS kernel defines three kinds of interfaces: 1. The connection of the system modules to the WiNeS kernel. This interface is defined by virtual methods in the abstract base classes of the WiNeS kernel. 2. The connection between the system modules and the simulation control. This connection is done in the same way as interface except that these classes are derived from the base classes. 3. The connection between the system modules on one hand and the configurator and the animator on the other hand. In order to exchange information with the configurator and the animator, the system module classes have to use methods from the interface definition.
3.2
Simulation Control
As a simulation control, WiNeS currently uses the discrete-event domain of Ptolemy which is a versatile simulation platform by the UC Berkeley [5]. For the simulation of mobile radio networks, this domain was extended with components that support mutable system configurations during a simulation run [6]. Through the modular concept of WiNeS, it is possible to replace the simulation control by another (e.g. discrete-event or process-calculi [7]). In comparison to other simulation tools, Ptolemy features the simultaneous use of different simulation paradigms (Ptolemy domains) in one hierarchically structured simulation layout. This feature was already considered during the identification of key abstractions in the object-oriented analysis.
3.3
System Modules
A system module is a software class library that implements the functionality of a specific mobile radio system. The following examples demonstrate the
flexibility of the simulator and the universality of the WiNeS kernel as the common basis for all system modules. There already exists three ready-to-use system modules.
3.3.1
GSM System Module
The most comprehensive system module was developed for the Global System for Mobile Communications (GSM) for the German network operator Mannesmann Mobilfunk GmbH, Düsseldorf. This system module models the functionality of the GSM air interface that is essential for a co-channel interference analysis of the speech channels on burst level. Traffic, network configuration, and environmental data from a real GSM network as well as path loss prediction data from a network planning tool serve as an input for the simulation. The radio connections are considered during the active mode of the mobile stations. One out of seven movement models covering, e.g., random and directed movement with different speeds as well as movement along streets can be assigned to an individual user. All GSM algorithms that influence the transmit powers on the air interface are modeled in detail: • measurement reporting and processing • power control • handover • frequency hopping • smart antennas with beam switching Shadowing is modeled following a log-normal distribution over the investigation area, but also in relation to the mobile station’s position. For the consideration of the diversity effects that are introduced by frequency hopping, adequate fading margins are used. The model for the link level performance makes use of the mapping procedures proposed in [8]. This system module enables capacity and quality investigations when using advanced features such as frequency hopping and adaptive antennas. Different real network configurations in their different environments can be compared. Their performance can be analyzed off-line by means of the statistics of the signal powers, the interference, and the signal-to-interference ratios which are recorded during the simulation. Moreover, the blocking rate and handover failure rate can be derived from several counters which monitor the channel assignment, handover and radio link failure procedures during the simulation. In addition to the simulator functionality, a comprehensive Java™-based on-line animation illustrates the network element’s states as they evolve over time within the plot of the applicable network configuration and environment.
3.3.2
mm-Wave Indoor Network System Module
Within the DFG Innovation Center, ¨Communications Systems¨, (sponsored by the German Research Society (DFG)) a simulator implementation for a 60 GHz campus indoor mobile communications system was created [9]. Adjustable options of this system modul are, among others: Traffic load Two models for the traffic load (Erlang and Engset traffic) can be used to drive the simulations. Both models allow the following parameter settings: • mean service time • mean interarrival time • maximum number of mobile subscribers User mobility A random walk mobility model for mobile subscribers is incorporated into the software [10]. The movements of the mobile subscribers can hereby be restricted to a tiny area, to a room, or movements through the entire environment. The mobile’s speed can be set as a parameter. Network Configuration Using a joint configuration file with the Radiowave Propagation Simulator, a deterministic ray-launching radio-wave propagation tool which is used simultaneously for system simulations [2][11], a 3-dimensional indoor environment as well as the network setup can be edited and read into the simulation software, e.g.: • walls, windows, and doors (position, thickness, dielectric parameters (complex epsilon)) • base stations (position, transmission power, antenna pattern, frequency reuse factor) • mobile stations (parameters for traffic load and mobility as described above, antenna pattern) For system analysis, the following values can be monitored during simulation and will be stored into Matlab™-compatible files for a later off-line evaluation: • timed cell load per cell • number of intercell and intracell handovers per user and per cell • cell dwell time of users per cell • entire number of users • number of link failures per cell due to: - no base station to be received (no coverage) - no resource (channel) available - failure in intercell handover - failure in intracell handover • timed signal strength per cell • timed signal-to interference ratio per cell • number of interferers as well as strength of each single interferer per cell This system model has been used to investigate propa-
gation problems, handover algorithms, and the influence of the user mobility in indoor environments in the mm-wave range [2][10][11]. Furthermore, an animator for this system module exists. This animation software is written in Java™. It can be used to animate the entire system, including mobility traces and multipaths. A randomly chosen mobile is traced. Its signalto-interference ratio as well as the received signal strength are illustrated [9].
3.3.3
4th Generation (IBMS) System Module
The Integrated Broadband Mobile System (IBMS) is a 4th generation wireless communications systems research project [12] [13] [14] sponsored by the German Federal Ministry for Education and Research (BMBF). A system module for this new system concept is currently being developed [14]. The objective of IBMS is to provide an unified way for supporting a variety of communication classes ranging from high mobility with low data rates towards portability at high data rates. The fundamental idea is to integrate this set of heterogeneous communication classes in one system are smart antennas [15][16]. The IBMS system module is especially aimed at the optimization of user and net data rate capacity. For this purpose several mechanisms are implemented as, e.g., • integrating different multiple access schemes (CDMA, SDMA, TDMA) along with different antenna configurations working in the same frequency band • different antenna models for smart antennas (e.g. sector antenna with Bartlett beamformer for base stations) • offering several QoS classes with a flexible assignment to physical transmission classes • providing heterogeneous applications running on different equipment in one system • connection quality enhancing procedures as data rate fall-back and TCC upgrade (using different transmission class in order to improve system capacity [14]) • hierarchical network structure to support heterogeneous services • Network Access and Connectivity Channel (NACCH) for basic signaling to provide permanent network access and maintenance of established connections The system performance is studied by means of measurements of the signal power in all transmissions. The resulting data is written to files for further evaluation. As the other modules, the IBMS module has an animator written in Java™. The whole system can be watched; the link quality, the transmission classes and the running services can be inspected.
A fourth system module for the Universal Mobile Telecommunications System (UMTS) is currently under development.
4
Summary
A development platform for mobile radio networks has been presented, which together with a simulator also combines a configurator and an animator in a closed concept. This platform enables the planning and optimization of mobile radio networks with consideration of their inherent multiple dynamics. The WiNeS kernel models a generic mobile radio system so that specific mobile radio systems can be implemented in different system modules on the basis of the common WiNeS kernel. Furthermore, the interface definitions of the WiNeS kernel are the basis for the decoupling from specific system modules and simulation controls. This ensures the reusability and the exchangeability of the components. This development platform will be demonstrated at the conference.
5
References
[1] Deissner, J.; Noll Barreto, A.; Barth, U.; Fettweis, G.P.: Interference Analysis of a Total Frequency Hopping GSM Cordless Telephony System. Proc. PIMRC’98, Boston, 8-11 September 1998, pp. 1525-1529. [2] Voigt, J.; Hübner, J.; Förster, E.; Fettweis, G.P.: Design Pattern for a Single Frequency Network in a Typical Office Environment at 60GHz. Proc. IEEE Vehicular Technology Conference ’99, Houston, 16-20 May 1999, pp. 1570-1574. [3] WiNeS - Wireless Network System Simulator. http://entmuc.et.tu-dresden.de:4660/
[4] Fischer, J.; Deissner, J.; Fettweis, G. P.; Hunold, D.; Lehnert, R.; Schweigel, M.; Voigt; Wagner, W.: Object-Oriented Modeling of a Generic Mobile Radio System. accepted for presentation at SCSC/SPECTS’99, Chicago, USA, 11-15 July 1999. [5] Lee, E.A. et.al.: The Almagest. Ptolemy Classic Manual. Berkeley: Department of EECS, University of California at Berkeley, 1990-1997.
[6] Voigt, J.: A Heterogeneous Approach for Wireless Network Simulations. In 3rd Ptolemy Miniconference, Berkeley, CA, USA, 19 January 1999. [7] Lee, E. A.; Sangiovanni-Vincentelli, A.: Comparing Models of Computation. Proc. ICAAD, San Jose, 10-14 November 1996. [8] Wigard, J.; Nielsen, T. T.; Michaelsen, P. H.; Mogensen, P.: BER and FER Prediction of Control and Traffic Channels for a GSM Type of AirInterface. Proc. IEEE VTC’98, pp. 1588-1591. [9] A System Simulator for a Cellular Indoor Network in the mm-Wave Range: http:// www.ifn.et.tu-dresden.de/~voigtje/ inno.html
[10] Voigt, J.; Fettweis, G.P.: Influence of User Mobility and Simulcast-Handoff on the System Capacity in Pico-Cellular Environments. accepted for presentation at IEEE Wireless Networking and Communications Conference ‘99, New Orleans, 21-24 September 1999. [11] Voigt, J.; Hübner, J.; Förster, E.; Fettweis, G.P.: Investigation of Wireless Communications Systems using Dynamic Simulation Models including Simultaneous Field Strength Prediction. accepted for presentation at European Wireless ‘99 in conjunction with ITG conference “Mobile Communications”, Munich, 6-8 October 1999. [12] Bronzel, M. et.al.: Integrated Broadband Mobile System (IBMS) Featuring Wireless ATM. Proc. ACTS Mobile Communication Summit ‘97, Aalborg, Denmark, 7-10 October, 1997, pp. 641-646. [13] Fettweis, G.: Integriertes Breitbandiges Mobilkommunikations-System (IBMS). Nachrichtentechnische Zeitschrift, (1-2) 1999. [14] Hunold, D. et.al.: Investigations on Capacity in the Integrated Broadband Mobile System (IBMS) Using a Wireless Network Simulator. Proc. 5th International Workshop on Mobile Multimedia Communication MoMuC’98, Berlin, 12-14 October 1998, pp. 325-336. [15] Bronzel, M. et.al.: Integrated Broadband Mobile System (IBMS) Featuring Smart Antennas. Proc. 8th Annual MPRG Symposium on Wireless Personal Communications, Blacksburg, USA, 10-12 June, 1998. [16] Krim, H.; Viberg, M.: Two Decades of Array Signal Processing Research. IEEE Signal Processing Magazine, July 1996, pp. 67-94.
