Digital Communications 0909.402.03/0909.504.01 Fall 2002

1. Digital Communications0909.402.03/0909.504.01Fall 2002 Lecture 5October 7, 2002 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall02/digcomm/

2. Plan • Baseband Data Transmission • Recall: Binary Symmetric Channel • Joint and Conditional Probabilities • Baye’s Theorem • BER • Optimum Receiver • Detection in the presence of AWGN • Receiver Model • Noise Model • Single Sample Detector • Matched Filter Detector • Unipolar and Bipolar Signaling

3. Digital Communications Transceiver Anti- aliasing Filter Error Control Encoder Data Encryption Encoder Channel/ Line Encoder Source Encoder Sampling Quantization Modulator MUX ADC Analog i/p CODEC MODEM Multiple access channel Analog o/p Error Control Decoder Data Encryption Decoder Source Decoder Audio Amp Reconstruction/ DAC Equalization / Decision Circuits Demod-ulator DEMUX

4. m0 r0 m1 r1 Recall: Binary Symmetric Channel Noise 0/1 m0/m1 r0/r1 Digital Modulation System Discrete Memoryless Channel Digital Demodulation System 0/1 Channel Transition Diagram

5. t=t0 r(t) r0(t) s(t) r0(t0) S TX ~ LPF Comparator m n(t) VT Receiver Model m

6. -21 PSD of thermal noise x 10 2 1.5 PSD, W/Hz 1 0.5 0 0 0.5 1 1.5 2 2.5 3 frequency, Hz 12 x 10 Thermal (Johnson) Noise

7. f(x) x m All White Gaussian Noise (AWGN)

8. Computing Probability of Error Condtional PDFs f(r0\s1 sent) f(r0\s2 sent) r0 VT P(error\s2 sent) P(error\s1 sent)

9. Matched Filter Matched Filter h(t) r0(t) = s0(t) + n0(t) r(t) = s(t) + n(t) demos/matched_filter

10. 0/A or -A/+A m Random Binary Source Line Encoder S Detector ~ 0/1 m AWGN Comparator Error Counter Lab Project 1: Monte Carlo Simulation of a Baseband Binary Communications System

11. Summary