Undergraduate Course: Signals and Communication Systems 2 (SCEE08007)
|School||School of Engineering
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 8 (Year 2 Undergraduate)
||Availability||Available to all students
|Summary||This course aims to introduce students to the fundamentals of Signal Processing, Communication, and Information Theory. The course aims to provide an insight into time domain and frequency domain analysis of continuous-time signals, and provide an insight into the sampling process and properties of the resulting discrete-time signals. The course then introduces the students to basic communication modulation techniques, as well as probability theory for analysing random signals. At the end of the module students will have acquired sufficient expertise in these concepts to appreciate and analyse physical-layer communication signals.
1. Course overview, and introduction to signals, systems, communications and the broader topic of signal processing (1 hour).
2. Nature of, and types of signals; definitions of continuous time, discrete time, periodic, aperiodic, deterministic and random. Introduction to phasors and concept of frequency of single tone, typical signals and signal classification, power and energy (2 hours).
3. Signal decompositions and concept of signal building blocks (1 hour)
4. Fourier Analysis, including trigonometric and complex Fourier series, Fourier transforms, Parseval's theorem, physical interpretations, and plotting spectra (3 hours).
5. Convolution, including the concept of an impulse and the impulse response of a linear system; the concept and application of convolution, and evaluating the convolution integral using graphical methods (3 hours)
6. Nyquist's Sampling Theorem and Discrete-Time Signals (including discrete-time convolution) (3 hours)
7. Introduction to communication theory and modulation techniques, including OOK, FSK, and PSK (2 hours)
8. Multiplexing techniques, including Frequency Division Multiplexing and Time Division Multiplexing (2 hours)
9. Basic Information theory and probability (3 hours).
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2017/18, Available to all students (SV1)
|Course Start Date
|Learning and Teaching activities (Further Info)
Lecture Hours 22,
Seminar/Tutorial Hours 10,
Formative Assessment Hours 1,
Summative Assessment Hours 1.5,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||100% written examination.
Any student who does not attend and perform satisfactorily on the Signals and Communications 2 laboratory is deemed to have failed the course, as it tests competency regarding the use of MATLAB to analyse simple signals and communication systems.
||Hours & Minutes
|Main Exam Diet S2 (April/May)||1:30|
|Resit Exam Diet (August)||1:30|
On completion of this course, the student will be able to:
- A student should be able to distinguish between, and give examples of, deterministic and random, periodic and aperiodic, continuous-time and discrete-time signals. For these signals, students should be able distinguish between energy and power signals, be able to perform the appropriate measure calculation for a given signal.
- The student should be able to evaluate the trigonometric, complex Fourier Series, and Fourier transforms of simple waveforms, provide a physical interpretation for these transforms, and plot phase, magnitude, and line spectra. The student should also be able to apply Parseval's theorem for each transform.
- The student should be able recall the Nyquist sampling theorem and analyse the effect of sampling on the frequency content of a signal.
- The student should be able to describe various pulse modulation schemes and circuits for their generation and reception, including OOK, FSK, and PSK; explain frequency division and time-vision multiplexing, and analyse simple multiplexing communication systems; explain how communication signals can be modelled as a random process, and perform simple statistical and probabilistic analysis of simple communication schemes.
- The student should be able to demonstrate an ability of use MATLAB to analyse simple signals and communication systems.
|See lecture notes for full reading list.|
|Graduate Attributes and Skills
|Keywords||Continuous and discrete-time signal,Fourier analysis,Nyquist sampling theory,communication system
|Course organiser||Dr James Hopgood
Tel: (0131 6)50 5571
|Course secretary||Miss Lucy Davie
Tel: (0131 6)51 7073