Chapter 1: Introduction. EET-223: RF Communication Circuits Walter Lara

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Transcription:

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) = V p sin(wt + Φ) V p : peak value w: angular velocity Φ: phase angle Can modulate by varying: V p : 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 P 2 / P 1 Voltage Gain: db = 20 log V 2 / V 1 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(r L ) = 20 log V / V 0dBm

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: P n = 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 P n = (e n / 2) 2 / R = KT f Noise Voltage (rms value): e n = 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 = P s / P n P s : Signal Power P n : NoisePower Typically in db: SNR(dB) = 10 log (P s / P n )

Noise Figure (NF) Measure of a device degradation to SNR The lower, the better Formula: NF = 10 log SNR in / SNR out SNR in : SNR at device s input SNR out : SNR at device s output Noise Ratio: NR = SNR in / SNR out Useful Relationship: SNR out = SNR in 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: 3 rd 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 (sin t + 1/3 sin 3 t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3 t + 1/5 sin 5 t).

Figure 1-9 (continued) (a) Fundamental frequency (sin t); (b) the addition of the first and third harmonics (sin t + 1/3 sin 3 t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3 t + 1/5 sin 5 t).

Figure 1-9 (continued) (a) Fundamental frequency (sin t); (b) the addition of the first and third harmonics (sin t + 1/3 sin 3 t); (c) the addition of the first, third, and fifth harmonics (sin t + 1/3 sin 3 t + 1/5 sin 5 t).

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.