Monday, Wednesday, Friday, 11:00-11:50, Duncan Hall 1064
| Week |
|
(Johnson & Wise) |
|
| 1 8/24 |
Course overview. |
Themes, Signals
Represent Information, Structure
of Communication Systems, The
Fundamental Signal, Complex
numbers (definitions, addition, polar and Cartesian forms), Elemental
Signals, Signal
Decomposition Introduction to Systems, Simple Systems |
Problem Set I |
| 2 8/31 |
Analog
signals as voltages and currents.
Circuit elements (R, C, L, sources). Basic circuit analysis: KCL and KVL; voltage and current divider. Power dissipation in circuits. Equivalent circuits. |
Voltage, Current, and Generic Circuit Elements, Ideal Circuit Elements, Ideal and Real-World Circuit Elements, Electric Circuits and Interconnection Laws, Power Dissipation in Resistor Circuits, Series and Parallel Circuits, Equivalent Circuits: Resistors and Sources |
Problem Set II |
| 3* 9/7 WF |
Frequency domain circuit analysis: Complex-amplitude
version of KVL, KCL, and v-i relations. Notions of impedance. Equivalent circuits with impedances. Transfer functions. RC circuits as filters. Lab 1: Safety and basic measurements |
Circuits with Capacitors and Inductors, The Impedance Concept, Complex numbers (rational functions, the complex plane) | Problem Set III 3.3, 3.4, 3.5, 3.6, 3.19 Due 9/18 |
| 4 9/14 |
Notion of bandwidth. Node analysis. Proof of Conservation of Power. Dependent sources. Lab 2: Signal sources and sinks |
Time
and Frequency Domains, Power
in the Frequency Domain
Equivalent Circuits: Impedances and Sources, Transfer Functions, Designing Transfer Functions, Formal Circuit Methods: Node Method, Power Conservation in Circuits, Dependent Sources |
Prepare for Quiz I |
| 5 9/21 |
Quiz I |
Electronics, Operational Amplifiers, Introduction to the Frequency Domain, Complex Fourier Series | Problem Set IV 3.13, 3.16, 3.21, 3.23, 3.41 Due 10/2 |
| 6 9/28 |
Fourier series: complex and classic. Fourier series approximations.
Parseval's Theorem. Lab 4: Signal Processing II: Active circuits |
Complex Fourier Series, Classic Fourier Series, A Signal's Spectrum, Fourier Series Approximation of Signals, Encoding Information in the Frequency Domain | Problem Set V 3.43, 4.1, 4.2, 4.5, 4.6 Due 10/9 |
| 7 10/5 |
Filtering periodic signals. The Fourier Transform. Fourier Transform properties. Solving linear systems in the frequency domain. Return to communication systems. Introduction to AM. Lab 5: Signal analysis & characterization |
Filtering Periodic Signals, Derivation of the Fourier Transform, Linear, Time-Invariant Systems | Problem Set VI 4.8, 4.12, 4.13, 4.20, 4.26 Due 10/16 |
| 8* 10/12 WF |
Characterizing speech.
|
Modeling the Speech Signal, Introduction to Digital Signal Processing, Introduction to Computer Organization, The Sampling Theorem |
Problem Set VII 5.1, 5.4, 5.7, 5.8, 5.9 Due 10/23 |
| 9 10/19 |
A/D and D/A conversion. Amplitude quantization.
Computation of Digital Systems, Discrete-time Fourier transform. Lab 6: Analog to Digital Conversion |
Amplitude Quantization, Discrete Time Signals and Systems, Discrete-Time Fourier Transform (DTFT) |
Prepare for Quiz II |
| 10 10/26 |
Quiz II DFT and the FFT. Computational complexity and real-time systems. Spectrograms. Manipulation of DT signals with difference equations. Lab 7: Digital Signal Processing I |
Discrete Fourier Transform (DFT), DFT: Computational Complexity, Fast Fourier Transform (FFT), Spectrograms, Discrete-Time Systems, Discrete-Time Systems in the Time Domain | Problem Set VIII 5.11, 5.18, 5.22, 5.23, 5.24 Due 11/6 |
| 11 11/2 |
Frequency-domain filtering. Mixed discrete- and continuous-time systems. Communication systems. Wireline and wireless channels. Lab 8: Digital Signal Processing II |
Discrete-Time Systems in the Frequency Domain, Filtering in the Frequency Domain, Efficiency in Frequency-Domain Filtering, Discrete-Time Filtering of Analog Signals, Information Communication, Types of Communication Channels, Wireline Channels | Problem Set IX 5.31, 5.33, 5.34, 6.5, 6.10 Due 11/13 |
| 12 11/9 |
Wireline and wireless channel models. Baseband and modulated
communication. Analog communication: Noise and its sources. Filters and denoising for noise reduction. Signal-to-noise ratio. Analysis of baseband and AM systems. Digital Communication: Representing bits with analog signals. Notion of datarate. Lab 9: Optical Communication |
Wireline Channels, Wireless
Channels, Line-of-Sight
Transmission, The
Ionosphere and Communcation, Communication
with Satellites, Noise
and Interference, Channel
Models, Baseband
Communications, Modulated
Communication, Signal-to-Noise
Ratio of an Amplitude-Modulated Signal Digital Communication, Binary Phase Shift Keying, Frequency Shift Keying, Digital Communication Receivers |
Prepare for Quiz III |
| 13 11/16 |
Quiz III Shannon's Source Coding Theorem. Introduction to compression (lossless and lossy). Huffman codes. Receivers for digital communication Error correcting codes. Lab 9 continued |
Digital Communication in the Presence of Noise, Digital Communication System Properties, Digital Channels, Entropy, Source Coding Theorem, Compression and the Huffman Code, Subtleties of Coding, Channel Coding, Repetition Codes, Block Channel Coding | Problem Set X 6.12, 6.15, 6.16, 6.18, 6.22, 6.28 Due 12/1 |
| 14* 11/23 MW |
Shannon's Capacity Theorem. |
Error-Correcting Codes: Hamming Distance, Error-Correcting Codes: Channel Decoding, Error Correcting Codes: Hamming Codes | |
| 15 11/30 |
Fundamental limits of communication systems. |
Noisy Channel Coding Theorem, Capacity of a Channel, Comparison of Analog and Digital Communication, |
Monday evenings, 7–9PM, in Duncan Hall 1064. See Sam's ELEC 241 webpage for details.
One of Wednesday, Friday (2-5PM), or Thursday (2:30-5:30PM), Abercrombie A141