Monday, Wednesday, Friday, 11:00-11:50, Duncan Hall 1064
(Johnson & Wise) |
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1
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Course overview. |
Themes, Signals
Represent Information (v), Structure
of Communication Systems, The
Fundamental Signal, Complex
numbers (v): definitions, addition,
polar and Cartesian forms, Elemental
Signals, Signal
Decomposition (v) Introduction to Systems, Simple Systems (v) |
Problem Set I
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2* 9/2 WF |
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 (v), Ideal Circuit Elements, Ideal and Real-World Circuit Elements, Electric Circuits and Interconnection Laws (v), Power Dissipation in Resistor Circuits, Series and Parallel Circuits (v), Equivalent Circuits: Resistors and Sources (v) |
Problem Set II |
3 9/9 |
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 (v), Complex numbers (v): rational functions, the complex plane |
Problem Set III 3.3, 3.4, 3.5, 3.6, 3.13 Due 9/20 |
4 9/16 |
Notion of bandwidth. Node analysis. Proof of Conservation of Power. Dependent sources. Lab 2: Signal sources and sinks |
Time and Frequency Domains (v), Power in the Frequency Domain, Equivalent Circuits: Impedances and Sources (v), Transfer Functions, Designing Transfer Functions, Formal Circuit Methods: Node Method, Power Conservation in Circuits (v), Dependent Sources | Prepare for Quiz I |
5 9/23 |
Quiz I |
Electronics, Operational Amplifiers (v), Introduction to the Frequency Domain, Complex Fourier Series (v) | Problem Set IV 3.19, 3.21, 3.24, 3.42, 3.44 Due 10/4 |
6 9/30 |
Fourier series: complex and classic. Fourier series approximations.
Parseval's Theorem. Lab 4: Signal Processing II: Active circuits |
Complex Fourier Series, A Signal's Spectrum, Fourier Series Approximation of Signals, Encoding Information in the Frequency Domain (v), Filtering Periodic Signals (v), Derivation of the Fourier Transform, | Problem Set V 4.1, 4.2, 4.5, 4.6, 4.8 Due 10/11 |
7 10/7 |
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 |
Linear, Time-Invariant Systems (v), Modeling the Speech Signal (v), Introduction to Digital Signal Processing, Introduction to Computer Organization (v) | Problem Set VI 4.12, 4.18, 4.20, 4.26 Due 10/18 |
8* 10/14 WF |
Characterizing speech.
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The Sampling Theorem, Amplitude Quantization (v), Discrete Time Signals and Systems (v), Discrete-Time Fourier Transform (DTFT) (v) |
Problem Set VII 5.1, 5.4, 5.7, 5.8, 5.9 Due 10/25 |
9 10/21 |
DFT and the FFT. Computational
complexity and real-time systems. Spectrograms. Manipulation of DT signals with difference equations. Lab 6: Analog to Digital Conversion |
Discrete Fourier Transform (DFT) (v), DFT: Computational Complexity, Fast Fourier Transform (FFT) (v), Spectrograms (v), Discrete-Time Systems, Discrete-Time Systems in the Time Domain (v) |
Prepare for Quiz II |
10 10/28 |
Quiz II Frequency-domain filtering. Mixed discrete- and continuous-time systems. Communication systems. Wireline and wireless channels. Lab 7: Digital Signal Processing I |
Discrete-Time Systems in the Frequency Domain, Filtering in the Frequency Domain, Efficiency in Frequency-Domain Filtering (v), Discrete-Time Filtering of Analog Signals, Information Communication, Types of Communication Channels, Wireline Channels (v) | Problem Set VIII 5.11, 5.17, 5.21, 5.23, 5.33 Due 11/8 |
11 11/4 |
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 8: Digital Signal Processing II |
Wireless Channels, Line-of-Sight Transmission, The Ionosphere and Communcation, Communication with Satellites (v), Noise and Interference, Channel Models, Baseband Communications (v), Modulated Communication, Signal-to-Noise Ratio of an Amplitude-Modulated Signal (v), Digital Communication, Binary Phase Shift Keying, Frequency Shift Keying (v), Digital Communication Receivers (v) | Problem Set IX 6.5, 6.8, 6.10, 6.12, 6.13 Due 11/15 |
12 11/11 |
Shannon's Source
Coding Theorem. Introduction to compression (lossless and lossy). Huffman codes. Receivers for digital communication Error correcting codes. |
Digital Communication in the Presence of Noise, Digital Communication System Properties, Digital Channels, Entropy, Source Coding Theorem, Compression and the Huffman Code (v), Subtleties of Coding, Channel Coding, Repetition Codes |
Prepare for Quiz III |
13 11/18 |
Quiz III
Shannon's Capacity Theorem. Error-correcting codes. Lab 9: Radio Communication |
Block Channel Coding, Error-Correcting Codes: Hamming Distance (v), Error-Correcting Codes: Channel Decoding (v) | Problem Set X |
14* 11/25 MW |
Fundamental limits of communication systems. Comparison of analog and digital waveform communications systems. |
Error Correcting Codes: Hamming Codes, Noisy Channel Coding Theorem | |
15 12/2 |
Comparison of analog and
digital waveform communications systems. Lab 9 continued |
Capacity of a Channel (v), Comparison of Analog and Digital Communication (v) |
Monday evenings, 7–9PM, in Duncan Hall 1064.
One of Thursday (2:30-5:30PM) or Friday (2-5PM), Abercrombie A141