No abstract

Digital communications and computers are having a tremendous impact on the world today. In order to meet the increasing demand for digital communication services, engineers must design systems in a timely and cost-effective manner. The number of technologies available for providing a given service is growing daily, covering transmission media, devices, and software. The resulting design, analysis, and optimization of performance can be very demanding and difficult. Over the past decades, a large body of computer-aided engineering techniques have been developed to facilitate the design process of complex technological systems. These techniques rely on models of devices and systems, both analytic and simulation, to guide the analysis and design throughout the life cycle of a system. Computer-aided design, analysis, and simulation of communication systems constitute a new and important part of this process.This thesis studies different aspects of the simulation of communication systems by covering some basic ideas, approaches, and methodologies within the simulation context. Performance measurement of a digital communication is the main focus of this thesis. However, some popular visual indicators of signal quality, which are often generated in a simulation to provide a qualitative sense of the performance of a digital system, are also considered.Another purpose of this thesis is to serve as a model for developing simulations or template of other systems. In other words, students learning to simulate a system can use the work presented here as a starting point.iii Acknowledgement

No abstract

Abstruct-Digital communication systemsare frequently operated over nonlinear channels with memory. The analysis of the performance of these systems is difficult and no complete analytical treatment of the problem has been obtained before. Several recent efforts have been directed toward the computation of error probabilities via Monte-Carlo simulation using a complete system model. These simulations require excessively large sample sizes and are not practical for estimating very low values of error probabilities. This paper presents a modified Monte-Carlo simulation technique for estimating error Probabilities in digital. communication systems operating over nonlinear channels.An importance-sampling technique is used to modify the probability density function of the noise process in a way to make simulation possible. Theoretical results as well as realistic examples are presented, showing that the number of samples needed for simulation is reduced considerably.

No abstract