Electrical Communications Systems ECE.09.433 Noise I Dr. Shreek Mandayam Electrical & Computer Engineering Rowan University

Plan Performance of Comm. Systems corrupted by Noise Performance Measures: Digital and Analog Thermal (Johnson) Noise Amplitude: Recall Random Variables: lab1.ppt Power Spectral Density Autocorrelation function Wiener-Khintchine Theorem

ECOMMS: Topics

Performance of Communications Systems Corrupted by Noise Digital Bit Error Rate (BER) Analog Output SNR

Noise A random, unwanted fluctuation in signal amplitude Thermal (Johnson) Noise Amplitude vs. time: Gaussian PDF Model See Lab1 Pre-lab Lecture: lab1.ppt We also want to know how much noise power there is per Hz – why?

Why? 2. Demodulation 1. Modulation 3. Demodulation f |W(f)| Bandpass fc -fc 1. Modulation 2. Demodulation f |W(f)| Baseband f |W(f)| Bandpass fIF -fIF 3. Demodulation

Power Spectral Density (PSD) Normalized power of a waveform in the frequency domain Used for measuring signal/noise power loss/transfer in communications system blocks

Autocorrelation Function Measure of similarity of a waveform observed at times t seconds apart how rapidly a random waveform fluctuates with time Rx(t) t (time delay) Slowly fluctuating signal rapidly Matlab Demo: autocorr.m Wiener-Khintchine Theorem Rw(t) Pw(f) F

Thermal (Johnson) Noise 0.5 1 1.5 2 2.5 3 x 10 12 -21 PSD of thermal noise frequency, Hz PSD, W/Hz Matlab script: psd_noise.m

Summary