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Course Detail

Course Name Communications Signal Processing and Algorithms
Course Code 24CCE334
Program B. Tech. in Computer and Communication Engineering
Credits 3
Campus Coimbatore, Chennai, Amaravati

Syllabus

Unit 1

Random Processes– Signal correlation, power spectra, multivariate analysis and large sample theory; Bayesian, Neyman Pearson (NP) min-max detector– analysis of digital communication systems (matched filter receivers, probabilities of error in digital modulations); Detection of signals with unknown parameters– GLRT and Bayesian approach- applications in wireless communications (synchronization, noncoherent receivers, detection in presence of interference or jammers);

Unit 2

Theory of distributed detection with applications in cognitive radio; Distributed signal processing in wireless communications; Estimation of unknown deterministic parameters, estimation of random parameters, Weiner filtering with applications in wireless communications (MMSE receiver structure, channel equalization, synchronization, diversity receiver in MIMO);

Unit 3

Spectral estimation methods with applications in cognitive radio; Monte Carlo simulation– Importance sampling, M-H sampling, Gibbs sampling, Fast variational Bayesian methods; Iterative receivers– algorithms and structures; Multi User Detection– Random access communications, interference suppression in CDMA.

Objectives and Outcomes

Pre Requisite(s): Communication Theory

Course Objectives

  • To provide foundation in estimation and detection theory in communication receiver.
  • To provide an insight on adaptive signal processing methods in wireless receivers.
  • To provide an introduction to various simulation techniques for wireless communication systems.

Course Outcomes

  • CO1: Able to understand estimation and detection theory in communication receiver.
  • CO2: Able to understand adaptive signal processing methods in wireless receivers
  • CO3: Able to understand signal processing aspects of diversity schemes
  • CO4: Able to understand structures and algorithm for iterative receivers

CO – PO Mapping

PO/PSO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2
CO
CO1 3 2 3 1
CO2 3 2 3 1
CO3 3 2 3 1
CO4 3 2 3 1

Text Books / References

Text Book(s)

  1. Kay, Steven M. “Fundamentals of Statistical Signal Processing, Volume 3: Practical Algorithm Development”, 1st edition, Pearson, 2013.
  2. Madhow, Upamanyu. “Fundamentals of Digital Communication”, Cambridge University Press, 2008.

Reference(s)

  1. Robert, Christian P., and G. C. Casella. “Monte Carlo Statistical Methods”, Springer-Verlag New York Inc., 1999.
  2. Stoica, Petre, and Randolph L. Moses. “Spectral Analysis of Signals”, Pearson, 2005.
  3. Trees, Harry L. Van, et al. “Detection Estimation and Modulation Theory, Part I: Detection, Estimation, and Filtering Theory”, 2nd edition, Wiley, 2013.
  4. Varshney, Pramod K., and C. S. Burrus, “Distributed Detection and Data Fusion”, Springer, 1997.
  5. Verdu, Sergio. “Multiuser Detection”, Illustrated edition, Cambridge University Press, 1998.
  6. Vucetic, B. “Space-Time Coding” 1st edition, John Wiley & Sons Inc, 2003.

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