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Probabilistic Models in Telecommunications - Sylabus

1. Random variables and random processes: random variables, discrete random variables, continuous random variables random processes. Discrete-time Markov chain: transient response, Chapman-Kolmogorov equation, birth-death process. (allowance 3/2)
2. Continuous-time Markov chain: birth-death process. Classical queueing systems: M/M/1/, M/M//, M/M/m/, M/M/1/K, M/M/m/m. (allowance 3/2)
3. Classical queueing systems: M/M/1//M, M/M///M, M/M/m/K/M. (allowance 3/2)
4. Advanced queueing models: bulk input, bulk service. (allowance 3/2)
5. Networks and series queues: M/M/1/-M/M/1/. (allowance 3/2)
6. Open Jackson networks, closed Jackson networks. (allowance 3/2)
7. Models with general arrival or service patterns: M/G/1/, G/M/1/, M/Er/1/, Er/M/1/. (allowance 3/2)
8. Markov chain error models for data transmission: GAP, Gilbert model, Fritchmann model. (allowance 3/2)
9. Markov chain error models for data transmission: throughput of ARQ - GBN, SASTRY, SW, GRN-SASTRY, adaptive ARQ. (allowance 3/2)
10. Elementary models for inventory. (allowance 3/2)
11. Models forb digital signal processing: AR(1), MA, ARMA, correlation models for image. (allowance 3/2)
12. Random generators. (allowance 3/2)