1 / 21

EE 6332, Spring, 2017 Wireless Telecommunication

EE 6332, Spring, 2017 Wireless Telecommunication. Zhu Han Department of Electrical and Computer Engineering Class 17 Mar. 27 th , 2017. Outline. BER Performance AWGN Channel Fading Channel Chapter 6.1 AWGN Chapter 6.2. Baseline: Stationary Channel. BPSK modulation.

wendit
Download Presentation

EE 6332, Spring, 2017 Wireless Telecommunication

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. EE 6332, Spring, 2017Wireless Telecommunication Zhu Han Department of Electrical and Computer Engineering Class 17 Mar. 27th, 2017

  2. Outline BER Performance AWGN Channel Fading Channel Chapter 6.1 AWGN Chapter 6.2 ECE 6331, Spring 2009

  3. Baseline: Stationary Channel BPSK modulation y: the received signal x: the transmitted signal with amplitude a w: white noise with power N0

  4. Bit Error Probability Noisena(t) gTx(t) gRx(t) d(i) We assume: • binary transmission with • transmission system fulfills 1st Nyquist criterion • noise , independent of data source Probability density function (pdf) of Mean and variance

  5. if • if Conditional pdfs The transmission system induces two conditional pdfs depending on

  6. Example of samples of matched filter output for some bandpass modulation schemes

  7. Figure 5.8 Illustrating the partitioning of the observation space into decision regions for the case when N 2 and M 4; it is assumed that the M transmitted symbols are equally likely.

  8. Placing a threshold Probability of wrong decisions Probability of wrong decision When we define and as equal a-priori probabilities of and we will get the bit error probability s

  9. Conditions for illustrative solution and  With  equivalently with  substituting for

  10. Special Case: Gaussian distributed noise • many independent interferers • central limit theorem • Gaussian distribution Motivation: é ù 2 - 1 2 ê ú ò 2 s = - 2  P 1 e d N ê ú b p s 2 2 0 N ê ú 0 ë û no closed solution Definition of Error Function and Error Function Complement

  11. 2.5 2 1.5 1 0.5 0 -0.5 -1 -1.5 -3 -2 -1 0 1 2 3 Error function and its complement • function y = Q(x) y = 0.5*erfc(x/sqrt(2)); erf(x) erfc(x) erf(x), erfc(x) x

  12. Expressions with and Bit error rate with error function complement  antipodal: unipolar Q function

  13. Bit error rate for unipolar and antipodal transmission • BER vs. SNR theoretical -1 simulation 10 unipolar -2 10 BER antipodal -3 10 -4 10 -2 0 2 4 6 8 10

  14. Flat Fading Channel Assume h is Gaussian random: BPSK: Conditional on h, 6.154, 6.155 Averaged over h, which follows chi-square distribution at high SNR.

  15. Effects of Fading Other modulation

  16. Simulation of Fading and Multipath

  17. Irreducible Bit Error Rate due to multipath Error floor

  18. Irreducible BER due to fading

  19. Irreducible BER due to fading

  20. BER due to fading & multipath

  21. Homework 4 • 5.4, 5.5,5.9, 5.17,5.18, 6.1, 6.12, 6.16 • Due 4/10 ECE6331 Spring 2009

More Related