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Course Contents

Introduction to simulation. Discrete time signals and systems. Modeling linear time invariant system. Modeling linear time varying system. Modeling memory less nonlinear systems. Modeling nonlinear system with memory. Nonlinear differential equation models. Review of probability and random processes. Monte Carlo simulation and random number generation. Testing of random number generators. Modeling of functional blocks in communication systems. Wireless fading channel models. Discrete Markov fading channel models. Estimation of parameters in simulation. Estimation of performance measures from simulation. Importance sampling. Other performance estimation methods. Variance reduction techniques. Simulation optimization. Case Study. 

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