This course examines modern digital communications systems. The study of digital communications systems includes waveform sampling, time multiplexing, line coding, digital modulation, and clock recovery techniques. Time and frequency domain analysis are the basis for study of bandwidth considerations, filtering, and channel and communication system modeling. Mathematics topics include Fourier analysis, probability, information theory, correlation, random variables, and entropy. Digital communication resilience is explored through channel capacity, line coding, and error correcting codes. Four labs are utilized to put topics into practice.
This course examines modern digital communications networks, with particular emphasis on wired networks at the physical layer and the TCP/IP network model above the physical layer. The study of digital communications systems includes waveform sampling, time multiplexing, line coding, digital modulation, and clock recovery techniques. Time and frequency domain analysis are the basis for study of bandwidth considerations, filtering, and channel and communication system modeling. Network topology, traffic representation, and link capacity assignment schemes are analyzed. Cost and time delay optimization for centralized and distributed networks are investigated. Queuing theory is presented with application to buffer modeling, buffer design considerations, and throughput constraints. Basic network design algorithms and flow control schemes are also covered. A communications system project brings these concepts to reality.
This course examines modern digital communications networks, with particular emphasis on wired networks at the physical layer and the TCP/IP network model above the physical layer. The study of digital communications systems includes waveform sampling, time multiplexing, line coding, digital modulation, and clock recovery techniques. Time and frequency domain analysis are the basis for study of bandwidth considerations, filtering, and channel and communication system modeling. Network topology, traffic representation, and link capacity assignment schemes are analyzed. Cost and time delay optimization for centralized and distributed networks are investigated. Queuing theory is presented with application to buffer modeling, buffer design considerations, and throughput constraints. Basic network design algorithms and flow control schemes are also covered. A communications system project brings these concepts to reality.
This is an introductory course devoted to the fundamentals of analog and digital communication systems used for the transfer of information electronically from one point to another. The course topics will focus on the various methods by which information can be transferred from point to point using analog as well as digital signaling techniques, and analyzing performance in terms of output signal-to-noise ratio or bit error probabilities. The analytical tools mastered in EE302, EE360 and EE381 will be called upon frequently in this course. Software applications, such as MATLAB and MultiSim, will be used for numerical analysis, simulation, and as a display tool in order to aid the learning process. Hands-on exercises and demonstrations will also be used for waveform generation, modulation, demodulation, and time and frequency domain analysis. This will be accomplished using the LabVolt communications training systems, microprocessor/FPGA boards, oscilloscope and spectrum analyzer.
This course analyzes modern digital and analog communications systems. The study of digital communications systems includes waveform sampling, time multiplexing, digital modulation, and detection techniques. Amplitude, phase, and frequency modulation, are the major analog communications topics discussed. The television signal is presented as an example of AM and FM with frequency division multiplexing. Time and frequency domain analysis are the basis for study of bandwidth considerations, filtering, and channel and communication system modeling. The course employs basic concepts in information theory to characterize the data content of communication signals and Fourier analysis to characterize their waveform representations. The course concludes with an analysis of system performance limitation due to noise. This analysis addresses the statistical properties of noise in linear systems, signal-to-noise ratios, and probability of error. A communications system project brings these concepts to reality.
This course analyzes modern digital and analog communications systems. The study of digital communications systems includes waveform sampling, time multiplexing, digital modulation, and detection techniques. Amplitude, phase, and frequency modulation, as well as frequency division multiplexing, are the major analog communications topics discussed. Time and frequency domain analysis are the basis for study of bandwidth considerations, filtering, and channel and communication system modeling. The course employs basic concepts in information theory to characterize the data content of communication signals and Fourier analysis to characterize their waveform representations. The course concludes with an analysis of system performance limitation due to noise. This analysis addresses the statistical properties of noise in linear systems, signal-to-noise ratios, and probability of error. A communications system project brings these concepts to reality.
