Mar 22, 2023  
2020-2021 Undergraduate Academic Catalog 
2020-2021 Undergraduate Academic Catalog [ARCHIVED CATALOG]

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EE 4022 - Principles of Communications

3 lecture hours 2 lab hours 4 credits
Course Description
In the study of communication systems, students will investigate how they operate and what affects their performance. The course relies heavily on system and signal analysis, both in the time and frequency domains, and on the statistical representation of random signals and noise. Amplitude and angle modulation systems are analyzed, including systems that transfer analog data and systems transferring digital data. Performance comparisons of commonly used digital modulation methods are presented. Signal-processing techniques that are commonly used in systems that transfer digital data are presented. Bit-error rate performance for baseband signal detection in the presence of noise is analyzed. Laboratory experiments reinforce the concepts from the lecture, with an emphasis on communication system functional modules. (prereq: MA 262  or MA 3620, EE 3032 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Develop the representations of analog AM, FM, and PM communication signals both in the time and frequency domains
  • Explain the representations of digitally modulated ASK, FSK, and PSK communication signals both in the time and frequency domains
  • Analyze communication systems and subsystems (both analog and digital) using both time and frequency domain techniques
  • Explain advantages and disadvantages of various modulation systems under differing circumstances
  • Determine the performance of digitally modulated amplitude and angle modulation systems with a specified signal-to-noise ratio
  • Determine required bandwidths and signal-to-noise ratios needed to achieve specified bit-error rates for various digital modulation methods in the presence of noise, at specified bit rates
  • Design an optimal correlation receiver for baseband and bandpass, binary and M-ary, digital communication systems operating in the presence of noise

Prerequisites by Topic
  • Calculate the Fourier series coefficients (in trigonometric and exponential forms) for a continuous-time periodic signal
  • Reconstruct periodic signals from Fourier series coefficients. (This may be done with the aid of a digital computer)
  • Determine the result of signal and system interaction by convolution
  • Obtain the Fourier transform of a finite-energy signal, and the inverse-Fourier transform of a spectrum
  • Properly sample a continuous time signal to create a discrete time signal
  • Determine the probability that a random variable having a specified density function exceeds a stated threshold
  • Determine the mean-square value of a random variable having a specified density function

Course Topics
  • Signal representations (2 classes)
  • System representations (2 classes)
  • Analog amplitude modulated (AM) signals and systems (6 classes)
  • Analog frequency and phase modulated (FM and PM) signals and systems (4 classes)
  • Digitally modulated amplitude-, phase- and frequency-shift key signals and systems (3 classes)
  • Random variables, processes, noise, performances with noise, optimal filters (6 classes)
  • Pulse code modulation and error-correction coding (2 classes)
  • Problem sessions, reviews, and tests (6 classes)

Laboratory Topics
  • Spectrum measurements
  • Multiplication of signals and frequency conversion
  • Amplitude modulation
  • Frequency modulation
  • Sampling, quantization, and PCM
  • Digital modulation: ASK and FSK
  • Digital modulation: BPSK and QPSK
  • Baseband digital channel bit-error rate
  • Direct sequence spread spectrum and code division multiple access (CDMA)

Dr. Cory Prust

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