1. Frequency and Bandwidth A means of quantifying and interpreting media capacity

2. Sinusoidal Waves Taught in math as a function of an angle – sin(90 o ) =1 Taught in Physics as a function of position in wave propagation Think of a wave propagating, –sinusoidal if consider f(t), one point over time –sinusoidal if consider f(x), snapshot for all x Our concern is f(t) with x fixed at each end Physics Wave Machine

3. 1 t Function goes through ONE cycle in 2 pi seconds.

4. 1 t.51.0 Function goes through ONE cycle in ONE second. FREQUENCY = 1

5. Why use Let f=1. Goes through 1 cycle as t=0..1. t 000.251.5 0.75 1 1.0 0 ? f As t=0..1, =0.. cycles 11 22 33 10 = has f=4 Answer by inspection

6. Three basic features of a wave Amplitude phase frequency The only variable (t): As t -> 0..1 the function goes through f cycles

7. Amplitude

8. Frequency

9. Phase

10. Focus on A and f Phase represents a shift right or left in the signal. This is a timing issue. Sin and cos only differ in phase (the time at which you examine the wave Our focus is on A and f

11. You should know The impact of changing the amplitude, A, of a signal. The impact of changing the frequency, f, of a signal. The impact of changing the phase of a signal. How to calculate the frequency of a sin wave.

12. Additive and Subtraction Properties Signals can be expressed as a sum of sinusoidal signals One can subtract frequencies and effectively filter the signal How to build filters is not important to this course, but the concept of filtering is. (see other graphs)

13. Frequency 1 sin(2*Pi*t) Frequency 3 1/3sin(6*Pi*t) Frequency 5 1/5sin(10*Pi*t) Sum of First 3 terms sin(2*Pi*t)+ 1/3sin(6*Pi*t)+ 1/5sin(10*Pi*t)

14. Fourier Series Surprisingly all periodic signals can be expressed as a sum of sinusoidal signals See examples of sawtooth, rectified cos, etc. MOST IMPORTANT TO US: –A square wave (fundamental of a digital signal) can be expressed as a sum of sins. –Requires INFINITE number of terms to exactly express a square wave –see example and program for seeing tradeoff of sin terms versus squareness

15. Frequency vs Time domain S(f) 1 f 12345.33.2

16. S(f) 1 f 12345.33.2 Redundant except for phase information in the time domain

17. Stereo Amplifier Application of frequency analysis Amplifier (lower frequencies) INPUTOUTPUT Certain frequencies do not pass through Frequencies within the dashed box are uniformly amplified This defines a transfer function for the amplifier: S(f) Communications media have similar characteristics and distort certain frequencies like the amplifier.

18. Media is the same Ethernet Cable INPUTOUTPUT Certain frequencies do not pass through What happens when you limit frequencies? Square waves (digital values) lose their edges -> Harder to read correctly.

19. Graphing Application Vary the number of terms and regraph the series. Increasing number of terms-> more square Decreasing number of terms-> less square Decreasing terms is analogous to passing the signal through a filter and has the effect of distorting the signal. Frequency Windows Application

20. The fundamental problem Undistorted signal Noise, bandwidth limitation, delay distortion, etc changes signal Receiver must determine when to read Receiver must correctly read Increasing noise-> Increased probability of misreading See overhead

21. Encoding Lots of techniques for encoding information Based on –type of data digital analog –type of medium digital analog

22. Way of looking at techniques Data Medium Digital Analog Digital Analog NRZ Manchester Differential Manchester Phase Coded Modulation (digitized voice) ASK FSK PSK modems AM/FM radio Television