Introduction to EECS II: Digital Communication Systems

Introduction and objectives for communication systems, information and entropy, Huffman coding

Source coding: Huffman codes and LZW

Errors and binary symmetric channels, error correction introduction

Error correction (channel coding), Hamming distance, parity bits

Rectangular parity codes, Hamming codes, linear block codes, interleaving

Convolutional codes

Viterbi decoding of convolutional codes

Gaussian noise, SNR and BER, dB scale

Transmitting on a physical channel: the bits-signal boundary, digital signaling, modulation and demodulation

Linear, time-invariant (LTI) channel models in continuous time (CT) and discrete time (DT), step response, unit sample (impulse) response, convolution, causality

Intersymbol interference (ISI), PyAudio channel demo (full oneping library), understanding LTI systems through their frequency response

Filters and composition, deconvolution as (noise-sensitive) inverse filtering

Fourier transformation to display the spectrum of a periodic signal (discrete-time Fourier series)

Discrete-time Fourier series, spectrum of non-periodic signals (discrete-time Fourier transforms), spectral character of noise

Modulation on a sinusoidal carrier, demodulation (time-domain and frequency-domain interpretations), sharing spectrum using multiple carriers

Signals in time and frequency, LTI channels, filtering, and modulation/demodulation: how these come together in modern design

Multi-hop networks, packet switching, queues, sources of delay

Sharing a channel: MAC protocols (TDMA, Aloha)

Network layer: routing protocols (without failures)

Network layer: routing protocols (handling failures), comparing distance-vector and link-state protocols

Transport protocols: reliable data delivery

Transport protocols: improving throughput with sliding windows

From the telegraph to the Internet