Monday, Wednesday, Friday, 11:00-11:50, Duncan Hall 1064
| Week |
|
(Johnson & Wise) |
|
| 1 8/27 |
Course overview. Definition of signals and systems, in both continuous- and discrete-time. Introduction to block diagrams. Fundamental model of communication (XMTR -> Channel -> RCVR). Simple signal manipulations: delay, amplification, time-reverse, addition Linearity and time-invariance. |
Themes, Signals Represent Information, Structure of Communication Systems, The Fundamental Signal, Elemental Signals, Signal Decomposition, Discrete-Time Signals, Introduction to Systems, Simple Systems, Complex numbers | Problem Set I 1.1, 1.2, 2.1, 2.3, 7.1.4 Due 9/7 |
| 2* 9/3 WF |
Analog signals as voltages and currents. Circuit elements (R, C, L, sources). KCL and KVL. Basic circuit analysis: KCL and KVL. Voltage and current divider. Lab 1: Safety and basic measurements |
Voltage, Current, and Generic Circuit Elements, Ideal Circuit Elements, Ideal and Real-World Circuit Elements, Electric Circuits and Interconnection Laws, Series and Parallel Circuits, Equivalent Circuits: Resistors and Sources | Problem Set II 3.1-3.5 Due 9/14 |
| 3 9/10 |
Frequency domain circuit analysis: Complex-amplitude version of KVL, KCL, and v-i relations. Notions of impedance and transfer functions. RC circuits as filters. Notion of bandwidth. Lab 2: Signal sources and sinks |
Circuits with Capacitors and Inductors, The Impedance Concept, Time and Frequency Domains, Equivalent Circuits: Impedances and Sources, Transfer Functions, Designing Transfer Functions | Problem Set III 3.7, 3.8, 3.13, 3.16 Due 9/21 |
| 4 9/17 |
Node analysis. Basic op-amp circuits. Lab 3: Signal Processing I: Basic circuits |
Formal Circuit Methods: Node Method, Electronics, Dependent Sources, Operational Amplifiers, The Diode | Prepare for Exam I |
| 5 9/24 |
Exam I (9/27, 7 PM) Introduction to diodes. Frequency-domain representation of signals (Fourier series). Fourier series. Lab 4: Signal Processing II: Active circuits |
Introduction to the Frequency Domain, Fourier Series, A Signal's Spectrum, Fourier Series Approximation of Signals, Definition of the Complex Fourier Series | Problem Set IV 3.30, 3.31, 4.1, and problems from handout (H.1, H.2) Due 10/5 |
| 6 10/1 |
Parseval's Theorem. Filtering periodic signals. The Fourier Transform. Fourier Transform properties. Return to communication systems. Introduction to AM. Lab 5: Signal analysis & characterization |
Encoding Information in the Frequency Domain, Filtering Periodic Signals, Derivation of the Fourier Transform | Problem Set V Problems from handout. Due 10/12 |
| 7 10/8 |
Characterizing speech. |
Linear, Time-Invariant Systems, Modeling the Speech Signal, Introduction to Digital Signal Processing, Introduction to Computer Organization, The Sampling Theorem, Amplitude Quantization |
Problem Set VI Problems from handout. Due 10/19 |
| 8* 10/15 WF |
Computation of Digital Systems, Discrete-time Fourier transform. |
Discrete Time Signals and Systems, Discrete-Time Fourier Transform (DTFT) |
Prepare for Exam II |
| 9 10/22 |
Exam II (10/25, 7 PM) DFT and the FFT. Computational complexity and real-time systems. Spectrograms. 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 VII Problems from handout Due 11/2 |
| 10 10/29 |
Manipulation of DT signals with difference equations. Frequency-domain filtering. Mixed discrete- and continuous-time systems 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 | Problem Set VIII Problems from handout Due 11/9 |
| 11 11/5 |
Communication systems. Wireline and wireless channels. 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 |
Noise
and Interference, Channel
Models, Baseband
Communications, Modulated
Communication, Signal-to-Noise
Ratio of an Amplitude-Modulated Signal,
Digital Communication,
Binary Phase Shift
Keying,
Orthogonality of Signal Sets |
Problem Set IX |
| 12 11/12 |
Receivers for digital communication Noise in Digital channels Shannon's Source Coding Theorem. Introduction to compression (lossless and lossy). Huffman codes. Error correcting codes. Lab 9 continued |
Frequency Shift Keying, Digital Communication Receivers, Digital Communication in the Presence of Noise, Digital Communication System Properties, Digital Channels, Entropy, Source Coding Theorem, Compression and the Huffman Code, | Prepare for Exam III |
| 13* 11/19 MW |
Exam III (11/20, 7 PM) |
Subtleties of Coding, Channel Coding, Repetition Codes, Block Channel Coding, Error-Correcting Codes: Hamming Distance, Error-Correcting Codes: Channel Decoding, Error Correcting Codes: Hamming Codes | |
| 14 11/26 | Computer Networks: Local area (Ethernet) and wide area (Internet). |
Noisy Channel Coding Theorem, Capacity of a Channel, Comparison of Analog and Digital Communication, Communication Networks, Message Routing | Problem Set X (Extra Credit) 6.15, 6.16, 6.18, 6.22, 6.27 Due 12/7 |
| 15 12/3 |
Course overview. Teaching evaluations. | Network Architectures and Interconnections, Ethernet, Communication Protocols |
One of Wednesday, Friday (2-5PM), or Thursday (2:30-5:30PM), Abercrombie A141