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1) Aims and learning outcomes
The course is finalized to learn the basics of digital communication and to acquire capabilities in the use of commercial software tools as Matlab and Simulink for simulation and performance evaluation of digital transmission systems.
2) Syllabus
2a) Digital Communication I
Representation of Signals. Geometric representation of signals, Schwarz inequality, projection onto the signal space, Gram-Schmidt orthogonalization, geometric representation of noise, signal-to-noise ratio, matched filter. MAP detection, MV detection, minimum squared distance detection, correlation detection. Baseband equivalent of passband signals.
Limits of Communication. Entropy, equivocation, mutual information. Capacity of the discrete-time channel, capacity of the AWGN channel, capacity of the channel with coloured Gaussian noise, water filling.
Modulation. Nyquist filter. QAM and PSK modulation. Error probability, union bound. Law of 6 dB/bit for PSK, law of 3 dB/bit for QAM, back to the AWGN capacity formula. Modulation based on orthogonal signals, examples, performance evaluation. OFDM, cyclic prefix, frequency domain equalization for OFDM.
Binary Channel Codes. Channel capacity with a power constraint, examples of binary block codes, performance of soft and hard decoding. Generator matrix and parity check matrix, generator polynomial and parity check polynomial. Trellis representation of the code and trellis decoding. Convolutional codes, trellis decoding of convolutional codes, performance of convolutional codes. Concatenated coding.
Codes in the signal space. Multidimensional constellations, lattices, lattice partitions.
2b) Digital Communication II
Equalization. Wiener’s method. Discrete-time AWGN model, FIR and unconstrained linear equalization, adaptive equalization, decision feedback equalization, channel capacity with decision feedback equalization. Maximum likelihood sequence detection.
Precoding. Tomlinson-Harashima precoding, partial response systems, examples.
Elements of MIMO transmission. The MIMO principle, the MIMO Gaussian channel, detection for the memoryless MIMO channel, detection for the MIMO channel with memory.
Phase-lock loop. Continuous-time PLL, discrete-time PLL, first-order and second-order loop; common phase detectors, design of the loop filter in the presence of phase noise.
Carrier and timing recovery. Decision-directed phase detector, S-curve, power of M phase detector, differential encoding, feed-forward and feed-back carrier recovery. Square-law timing detector, Gardner detector; digital re-sampling.
3) Laboratory activities
Use of Simulink and Matlab for simulation of digital transmisison systems.
4) Prerequisites
Knowledge of Signal Theory: Fourier analysis, filtering, basics of digital signal processing.
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Inglese