Göm meny
Denna sida finns ej på svenska.
Denna sida utgör del av kursinformation från ett tidigare år. Den finns här av historiska skäl. För aktuell information, klicka på kurskoden i navigationsraden ovan.

TSKS04 Digital Communication Continuation Course

Lectures Spring 2014

Here you primarily will find slides from the lectures. Those slides will be added here as the lectures go by.

You may be interested i the slides from last year. However, the slides will most likely be significantly different this year, since it is not the same teacher this time.

  • Lecture 1
    Introduction, course plan, PSD of digital modulation.
    No slides this time, but notes.
    Lecture notes for lectures 1 and 2.: PDF[131k].
  • Lecture 2
    PSD of digital modulation.
    No slides this time, but see notes under Lecture 1.
  • Lecture 3
    Complex baseband representation of narrowband real-valued deterministic signals.
    No slides this time.
  • Lecture 4
    Lab instructions.
    Complex-valued stochastic processes, complex baseband representation of narrowband real-valued stochastic processes.
    Introduction to estimation.
    No slides this time.
  • Lecture 5
    Hypothesis testing, likelihood-ratios and likelihood-functions. Estimation, specifically estimation of delay, phase-shift and amplitude.
    Slides: Figures 4.3 and 4.4 from Madhow.
  • Lecture 6
    Non-coherent detection. ML detection of sequences.
    Slides: Figure 4.6 from Madhow.
  • Lecture 7
    ML detection in the presence of ISI. The Viterbi algorithm.
    No slides this time.
  • Lecture 8
    Equalizing, Linear equalizing, Zero-forzing equalizing, MMSE.
    No slides this time.
  • Lecture 9
    Channel Coding. Convolutional Codes.
    Binary convolution, the D-transform, periodic sequences, delay-less inverse of a sequence, matrix convolution, examples of encoders.
    No slides this time.
  • Lecture 10
    Channel Coding. Convolutional Codes.
    Delay-less inverse of a convolutional encoder. Catastrophic encoders. State diagrams, trellises, and the free distance. Terminated convolutional codes. Decoding using the Viterbi algorithm.
    No slides this time.
  • Lecture 11
    Channel Coding. Properties and structure of Convolutional Codes.
    Path-weight enumerators and their relation to code structure.
    Error probabilities.
    Summary of the course.
    No slides this time.

Sidansvarig: Mikael Olofsson
Senast uppdaterad: 2019 07 30   10:17