Slides1 The Communication System midterm Slides
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This document discusses key concepts in digital communication systems including: - Transmitters send signals from a finite set of possible waveforms during a limited time, while channels distort and attenuate signals and add noise. Receivers decide which waveform was sent given the noisy received signal. - Digital communications have advantages like regeneration of signals at receivers, identical treatment of different signal types, and error correction techniques. - All communication signals are represented as random variables or random processes since receivers do not have prior information about transmitted signals. Random processes are collections of time functions corresponding to random experiment outcomes.
![Noise in communication systems
Lecture 17
Thermal noise is described by a zero-mean Gaussian random
process, n(t).
Its PSD is flat, hence, it is called white noise.
[w/Hz]
Probability density function
Power spectral
density](https://image.slidesharecdn.com/slides1-140807031229-phpapp01/85/Slides1-The-Communication-System-midterm-Slides-7-320.jpg)
Slides1 The Communication System midterm Slides
- 2. Digital communication system Lecture 12 Important features of a DCS: The transmitter sends a waveform from a finite set of possible waveforms during a limited time The channel distorts, attenuates the transmitted signal and adds noise to it. The receiver decides which waveform was transmitted given the noisy received signal The probability of an erroneous decision is an important measure for the system performance
- 3. Digital versus analog Lecture 13 Advantages of digital communications: Regenerator receiver Different kinds of digital signal are treated identically. Data Voice Media Propagation distance Original pulse Regenerated pulse A bit is a bit!
- 4. Digital versus analog.... Error Correction • Linear Block Codes • Convolutional Codes • Turbo Codes Encryption and Decryption
- 5. Random Variable and Random Process All the communication signals are random. The receiver does not have any A Priori Information about the transmitted signals. Random Variable X(A) represents the functional relationship between the random event A and a number.
- 6. Lecture 16 Random process A random process is a collection of time functions, or signals, corresponding to various outcomes of a random experiment. For each outcome, there exists a deterministic function, which is called a sample function or a realization. Sample functions or realizations (deterministic function) Random variables time (t) Realnumber
- 7. Noise in communication systems Lecture 17 Thermal noise is described by a zero-mean Gaussian random process, n(t). Its PSD is flat, hence, it is called white noise. [w/Hz] Probability density function Power spectral density
- 8. Signal transmission through linear systems Lecture 18 Deterministic signals: Random signals: Ideal distortion less transmission: All the frequency components of the signal not only arrive with an identical time delay, but also are amplified or attenuated equally. Input Output Linear system