Simulations can be developed to investigate either transient phenomena or steady-state properties of The study of the acquisition time of a phase-lock loop receiver is an example of a transient phend Simulations that are performed to study transient behavior often focus on a single subsystem such as synchronization system Simulations that are developed to study steady-state behavior often model system. An example is a simulation to determine the BeR of a system 78.3 Motivation for the Use of simulation As mentioned previously, simulation is a reasonable approach to many design and analysis problems because complex problems demand that computer-based techniques be used to support traditional analytical approaches. There are many other motivations for making use of simulation. A carefully developed simulation is much like having a breadboard implementation of the communication system available for study. Experiments can be performed using the simulation much like experiments can be performed using hardware. System parameters can be easily changed, and the impact of these changes can be evaluated. By ontinuing this process, parameteric studies can easily be conducted and acceptable, or perhaps even optimun parameter values can be determined. By changing parameters, or even the system topology, one can play "what if games much more quickly and economically using a simulation than with a system realized in hardware. It is often overlooked that simulation can be used to support analysis. Many people incorrectly view simu lation as a tool to be used only when a system becomes too complex to be analyzed using traditional analysis hniques. Used properly, simulation goes hand in hand with traditional techniques in that simulation can often be used to guide analysis. a properly developed simulation provides insight into system operation. As an cample, if a system has many parameters, these can be varied in a way that allows the most important parameters, in terms of system performance, to be identified. The least important parameters can then often be discarded, with the result being a simpler system that is more tractable analytically. Analysis also aids mulation. The development of an accurate and efficient simulation is often dependent upon a careful analysis of various portions of the syst 78.4 Limitations of Simulation Simulation, useful as it is, does have limitations. It must be remembered that a system simulation is an approximation to the actual system under study. The nature of the approximations must be understood if one is to have confidence in the simulation results. The accuracy of the simulation is limited by the accuracy to which the various components and subsystems within the system are modeled. It is often necessary to collect extensive experimental data on system components to ensure that simulation models accurately reflect the ehavior of the components. Even if this step is done with care, one can only trust the simulation model over the range of values consistent with the previously collected experimental data. A main source of error in a simulation results because models are used at operating points beyond which the models are valid In addition to modeling difficulties, it should be realized that the digital simulation of a system can seldo be made perfectly consistent with the actual system under study. The simulation is affected by phenomena not present in the actual system. Examples are the aliasing errors resulting from the sampling operation and the finite word length (quantization) effects present in the simulation. Practical communication systems use a number of filters, and modeling the analog filters present in the actual system by the digital filters required by the simulation involves a number of approximations. The assumptions and approximations used in modeling an analog filter using impulse-invariant digital filter synthesis techniques are quite different from the ass tions and approximations used in bilinear z-transform techniques. Determining the appropriate modeling technique requires careful thought. Another limitation of simulation lies in the excessive computer run time that is often necessary for estimating performance parameters. An example is the estimation of the system BER for systems having very low nominal bit error rates. We will expand on this topic later in this chapter. e 2000 by CRC Press LLC© 2000 by CRC Press LLC Simulations can be developed to investigate either transient phenomena or steady-state properties of a system. The study of the acquisition time of a phase-lock loop receiver is an example of a transient phenomenon. Simulations that are performed to study transient behavior often focus on a single subsystem such as a receiver synchronization system. Simulations that are developed to study steady-state behavior often model the entire system. An example is a simulation to determine the BER of a system. 78.3 Motivation for the Use of Simulation As mentioned previously, simulation is a reasonable approach to many design and analysis problems because complex problems demand that computer-based techniques be used to support traditional analytical approaches. There are many other motivations for making use of simulation. A carefully developed simulation is much like having a breadboard implementation of the communication system available for study. Experiments can be performed using the simulation much like experiments can be performed using hardware. System parameters can be easily changed, and the impact of these changes can be evaluated. By continuing this process, parameteric studies can easily be conducted and acceptable, or perhaps even optimum, parameter values can be determined. By changing parameters, or even the system topology, one can play “what if” games much more quickly and economically using a simulation than with a system realized in hardware. It is often overlooked that simulation can be used to support analysis. Many people incorrectly view simu￾lation as a tool to be used only when a system becomes too complex to be analyzed using traditional analysis techniques. Used properly, simulation goes hand in hand with traditional techniques in that simulation can often be used to guide analysis. A properly developed simulation provides insight into system operation. As an example, if a system has many parameters, these can be varied in a way that allows the most important parameters, in terms of system performance, to be identified. The least important parameters can then often be discarded, with the result being a simpler system that is more tractable analytically. Analysis also aids simulation. The development of an accurate and efficient simulation is often dependent upon a careful analysis of various portions of the system. 78.4 Limitations of Simulation Simulation, useful as it is, does have limitations. It must be remembered that a system simulation is an approximation to the actual system under study. The nature of the approximations must be understood if one is to have confidence in the simulation results. The accuracy of the simulation is limited by the accuracy to which the various components and subsystems within the system are modeled. It is often necessary to collect extensive experimental data on system components to ensure that simulation models accurately reflect the behavior of the components. Even if this step is done with care, one can only trust the simulation model over the range of values consistent with the previously collected experimental data. A main source of error in a simulation results because models are used at operating points beyond which the models are valid. In addition to modeling difficulties, it should be realized that the digital simulation of a system can seldom be made perfectly consistent with the actual system under study. The simulation is affected by phenomena not present in the actual system. Examples are the aliasing errors resulting from the sampling operation and the finite word length (quantization) effects present in the simulation. Practical communication systems use a number of filters, and modeling the analog filters present in the actual system by the digital filters required by the simulation involves a number of approximations. The assumptions and approximations used in modeling an analog filter using impulse-invariant digital filter synthesis techniques are quite different from the assump￾tions and approximations used in bilinear z-transform techniques. Determining the appropriate modeling technique requires careful thought. Another limitation of simulation lies in the excessive computer run time that is often necessary for estimating performance parameters. An example is the estimation of the system BER for systems having very low nominal bit error rates. We will expand on this topic later in this chapter. 8574/ch078/frame Page 1751 Wednesday, May 6, 1998 11:08 AM