Chapter 1: Introduction EET-223: RF Communication Circuits Walter - PowerPoint PPT Presentation

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 = 𝟓𝑳𝑼∆𝒈𝑺 • Textbook assumes room temperature is 17C = 290.15 K, so 𝟓𝑳𝑼 = 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.