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TRANSCRIPT
Chapter 1: Introduction
EET-223: RF Communication Circuits
Walter Lara
Introduction
• Electronic communication involves transmission over medium from source to destination
• Information can contain voice, picture, sensor output, or any data.
• Intelligence signal or simply “intelligence”– contains information to transmit
• Intelligence is at frequencies too low to transmit (e.g. voice 20Hz – 3 KHz) - would require huge antennas
Introduction – Cont’d
• Multiple intelligence signals have the same frequency (e.g. voice) - would result on interference if transmitted simultaneously
• Modulation – process of putting intelligence signal onto high-frequency carrier for transmission
• Demodulation – process of extracting the intelligence from a transmitted signal
Introduction – Cont’d
• Carrier signal is a sinusoid:
– v(t) = Vp sin(wt + Φ)
– Vp : peak value
– w: angular velocity
– Φ: phase angle
• Can modulate by varying:
– Vp : Amplitude Modulation (AM)
– w: Frequency Modulation (FM)
– Φ: Phase Modulation (PM)
Introduction – Cont’d
• RF Spectrum divided into ranges. Example:– MF (300 KHz – 3 MHz): AM Radio
– VHF (30-300 MHz): FM Radio, some TV, some cellphones
– UHF (300MHz – 3 GHz): TV, cellphones, WiFi, microwaves
• See Table 1-1 for complete details
Figure 1-1 A communication system block diagram.
The Decibels (dB) in Communications
• Used to specify measured and calculated values of voltage, power and gain
• Power Gain: dB = 10 log P2 / P1
• Voltage Gain: dB = 20 log V2 / V1
• dB using a 1W reference: dBW = 10 log P / 1 W
• dB using a 1mW reference: dBm = 10 log P / 1 mW
• dB using a 1mW reference with respect to a load: dBm(RL) = 20 log V / V0dBm
Noise
• Any undesired voltages/currents that appear in a signal
• Often very small (~uV)
• Can be introduced by the transmitting medium (external noise):– human-made (e.g. sparks, lights, electric motors)
– atmosphere (e.g. lightning)
– space (e.g. sun)
• Can be introduced by the receiver (internal noise):– physical properties of electronic components
Figure 1-2 Noise effect on a receiver s first and second amplifier stages.
Thermal Noise
• Aka Johnson or White Noise
• Random voltage fluctuations across a circuit component caused by random movement of electrons due to heat
• Contains “all” frequencies (all colors = white)
• Power from Thermal Noise: Pn = KT ∆f– K = 1.38 x 10-23 J/K (Boltzman’s Constant)
– T: resistor temperature, in Kelvins
– ∆f: bandwidth of system
Figure 1-3 Resistance noise generator.
Thermal Noise – Cont’d
• Pn = (en / 2)2 / R = KT ∆f
• Noise Voltage (rms value):
en = 𝟒𝑲𝑻∆𝒇𝑹
• Textbook assumes room temperature is 17C = 290.15 K, so 𝟒𝑲𝑻 = 1.6 x 10-20 J
Other Noise Sources
• Shot Noise – caused by the fact that electrons are discrete particles and take their own random paths
• Transit-Time Noise – occurs at high frequencies near the device cutoff frequency
• Excess Noise – occurs at low frequencies (<1 KHz), caused by crystal surface defects
Figure 1-4 Device noise versus frequency.
Signal-to-Noise Ratio (S/R or SNR)
• Very important & common measure
• The higher, the better
• Formula: SNR = Ps / Pn
– Ps: Signal Power
– Pn: NoisePower
• Typically in dB: SNR(dB) = 10 log (Ps / Pn)
Noise Figure (NF)
• Measure of a device degradation to SNR
• The lower, the better
• Formula: NF = 10 log SNRin / SNRout
– SNRin : SNR at device’s input
– SNRout : SNR at device’s output
• Noise Ratio: NR = SNRin / SNRout
• Useful Relationship: SNRout = SNRin – NF (all in dB)
Information & Bandwidth
• Amount of information transmitted in a given time is limited by noise & bandwidth
• Harley’s Law: information α bandwidth x time of transmission
• In USA, bandwidth is regulated by FCC– AM Radio: 30 KHz
– FM Radio: 200 KHz
– TV: 6 MHz
Fourier Analysis
• Any signal can be expressed as the sum of pure sinusoids.
• See Table 1-4 for selected waveforms• For a square wave:
v = 4V/π (sin wt + 1/3 sin 3wt + 1/5 sin 5wt + …)– sin wt : fundamental frequency– 1/3 sin 3wt: 3rd harmonic– 1/5 sin 5wt: 5th harmonic
• The more bandwidth, the better representation
Figure 1-9 (a) Fundamental frequency (sin t); (b) the addition of the first and third harmonics (sint + 1/3 sin 3t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3t + 1/5 sin 5t).
Figure 1-9 (continued) (a) Fundamental frequency (sin t); (b) the addition of the first and third harmonics (sint + 1/3 sin 3t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3t + 1/5 sin 5t).
Figure 1-9 (continued) (a) Fundamental frequency (sin t); (b) the addition of the first and third harmonics (sint + 1/3 sin 3t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3t + 1/5 sin 5t).
Figure1-10 Square waves containing: (a) 13 harmonics; (b) 51 harmonics.
Figure1-10 (continued) Square waves containing: (a) 13 harmonics; (b) 51 harmonics.
Fast Fourier Transform (FFT)
• Signal processing technique that converts time-varying signals to frequency components using samples
• Allows Fourier analysis when using oscilloscopes and spectrum analyzers
Figure 1-11 (a) A 1-kHz sinusoid and its FFT representation; (b) a 2-kHz sinusoid and its FFT representation.
Figure 1-11 (continued) (a) A 1-kHz sinusoid and its FFT representation; (b) a 2-kHz sinusoid and its FFT representation.
Figure 1-12 A 1-kHz square wave and its FFT representation.
Figure 1-13 (a) A low-pass filter simulating a bandwidth-limited communications channel; (b) the resulting time series and FFT waveforms after passing through the low-pass filter.