1 / 32

Additive White Gaussian Noise (AWGN) Channel and Matched Filter Detection

Additive White Gaussian Noise (AWGN) Channel and Matched Filter Detection. ELE 745 – Digital Communications Xavier Fernando. ELE 745 – AWGN Channel. Part I – Gaussian distribution. Gaussian (Normal) Distribution.

chase-ochoa
Download Presentation

Additive White Gaussian Noise (AWGN) Channel and Matched Filter Detection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Additive White Gaussian Noise (AWGN) Channel and Matched Filter Detection ELE 745 – Digital Communications Xavier Fernando

  2. ELE 745 – AWGN Channel Part I – Gaussian distribution

  3. Gaussian (Normal) Distribution • The Normal or Gaussian distribution, is an important family of continuous probability distributions • The mean ("average", μ) and variance (standard deviation squared, σ2) are the defining parameters • The standard normal distribution is the normal distribution with zero mean (μ=0)and unity variance (σ2 =1) • Many measurements, from psychological to thermal noise can be approximated by the Gaussian distribution.

  4. Gaussian RV

  5. General Gaussian RV

  6. PDF of Gaussian Distribution Standard Norma Distribution

  7. CDF of Gaussian Distribution

  8. The Central Limit Theorem • The sum of independent, identically distributed large number of random variables with finite variance is approximately normally distributed under certain conditions • Ex: Binomial distribution B(n, p) approaches normal for large n and p • The Poisson(λ) distribution is approximately normal N(λ, λ) for large values of λ. • The chi-squared distribution approaches normal for large k. • The Student’s t-distribution t(ν) approaches normal N(0, 1) when ν is large.

  9. Area under Gaussian PDF The area within +/- σ is ≈ 68% (dark blue) The area within +/- 2σ is ≈ 95% (medium and dark blue) The area within +/- 2σ is ≈ 99.7% (light, medium, and dark blue)

  10. Bit Error Rate (BER) • BER is the ratio of erroneous bits to correct bits • BER is an important quality measure of digital communication link • BER depends on the signal and noise power (Signal to Noise Ratio) • BER requirement is different for different services and systems • Wireless link BER < 10-6 while Optical BER < 10-12 • Voice  Low BER while Data  High BER

  11. Logic 0 and 1 probability distributions

  12. Digital Receiver Performance Probability of error assuming Equal ones and zeros Where, Depends on the noise variance at on/off levels and the Threshold voltage Vththat is decided to minimize the Pe; Often Vth = V+ + V-

  13. The Q Function Fx(x) = 1 – Q(X)

  14. Error Probability of On-Off Signaling

  15. BER (Pe) versus Q factor in a Typical Digital Communication Link

  16. Part-iiMatched filter detection

More Related