Welcome to EQ2430/EQ2440 RF lecture
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Transcript of Welcome to EQ2430/EQ2440 RF lecture
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Welcome toEQ2430/EQ2440
RF lecture
Per Zetterberg
School of Electrical Engineering
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Objective of this lecture
• Give an overview of radio communications.• Review
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What is RF ?
• RF = Radio Frequency. • For us: 2-6GHz.
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What is the ”channel” ?
txTX RX
Propagation channel
TX = Transmitter chain
RX =receiver chain
D/A A/D
Communication channel
ty
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Transmitter chain (TX)
D/A
tfj TX2exp
LPF BPF HPA
LPF = Low Pass FilterBPF = Band Pass FilterHPA = High Power Amplifier
=Mixer
tfj TX2exp =Local oscillator
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Receiver chain (RX)
LPF = Low Pass FilterBPF = Band Pass FilterLNA =Low Noise Amplifier
=Mixer
tfj RX2exp =Local oscillator
A/D
tfj RX2exp
LPFBPF LNA
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Basic Channel Model
0PRFILT2exp ttxththftjty
Unknown offset between clocks at TX and TX
Propagation channel
Combined effect ot low-pass and band-pass filters in TX and RX.
Frequency offset between TX and RX.
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Handling basic channel model
knnknnsn IhnfTjy
002exp
Discrete time:
TRAIN TRAIN Data
Known:nI Unkown:nI
1. Sliding correlation.2. Sliding correlation, several frequency offsets, FFT.3. Several short correlations.4. Self-correlation.
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Inter-symbol interference
12.0 nnn IIy
-1.5 -1 -0.5 0 0.5 1 1.5-1.5
-1
-0.5
0
0.5
1
1.5
-4 -3 -2 -1 0 1 2 3 4-4
-3
-2
-1
0
1
2
3
4
QPSK: No problem. 16QAM: Blur.
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Inter-symbol interference sources
1. Radio propagation.2. Narrow and sharp low-pass and band-pass filters !!!!!!
(narrow=narrow compared with the bandwidth of the desired signal)3. Pulse-shaping, sampling offsets.
So why do we use these narrow filters ?
1. Limit spectrum of transmitted signal.2. Improve adjacent channel
performance.3. Reduce requirements on A/D
converters.
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Ways to combat inter-symbol interference• Interpolation between samples.• Equalizers (linear, decision feedback, viterbi, ...)• OFDM
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Next problem
Power amplifier non-linearity
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Power-Amplifier Non-linearity
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Input/output power
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AM/AM and AM/PM model
txjtxjStxSty expexp PA
AM/AM AM/PM
AM: Amplitude Modulation PM: Phase Modulation
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Intuition AM/AM and AM/PM model• Let’s say our communication signal has 1MHz
bandwidth.• The carrier frequency is 1GHz=1000MHz.• Then every symbol lasts 1000 cycles.• During one symbol the input signal can be seen as a
CW.• A CW which is sent through a non-linearity will always
appear at the output (together with harmonics), but with a different amplitude and phase.
• The AM/AM and AM/PM models are functions of this phase offset.
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Solid State Power Amplifier Model: SSPA
pp
A
F2
12
0
A
1
:Output saturation level (unit dependent e.g. volt, dBm, LSB)
:Smoothness parameter.0Ap
LSB: Least significant bit.
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Matlab function: SSPA.m
• Available on course homepage.• Applies non-linearity to the input signal.• The parameter A0 is hardcoded inside the function.• The patameter A0 is referenced i units of LSB (least-
significant bit) of the signal sent from the D/A converter.• The smoothness parameter p is an input to the function.• Three present values of p are proposed 1,10,100 (bad,
fair, good)
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Amplifier non-linearity effects
BS1
BS2
MS1
MS2
Link 1
Link 2
cf
MHz5cf
In-band disrtorion: Detoriation of own link.Out-of-band distortion: Detoration of the others link.
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In-band/out-of-bandIn-band distortion
Out-of-band distortion
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Example of in-band distortion influence
-4 -3 -2 -1 0 1 2 3 4-4
-3
-2
-1
0
1
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3
4
-4 -3 -2 -1 0 1 2 3 4-4
-3
-2
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0
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With distortionWithout distortion
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Next problem
Phase-noise
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Phase-noise: Imperfect LO
A/D
ttfjt RX2expLO
LPFBPF LNA
This phase offset is a stocastic process = phase noise.
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Phase-Noise Spectrum
tjt expF)(LOF FourierFourier
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Matlab-file: add_phase_noise.m•Link on course homepage
•Generates phase-noise from given phase-noise spectrum, and multiplies it to the desired signal.
•The phase-noise spectrum is specified by input parameters phase_noise_freq and phase_noise_power.
•Three different ”pre-set” values given on course homepage (bad, fair, good) given in phase_noise_param.m.
*
*) The function is written by Alex Bar-Guy and is available on matlab central.
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Example: Influence of phase-noise
-4 -3 -2 -1 0 1 2 3 4-4
-3
-2
-1
0
1
2
3
4
-4 -3 -2 -1 0 1 2 3 4-4
-3
-2
-1
0
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Without phase-noise With phase-noise
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How should you simulate ?
• Start with basic channel modelYou should be able to do this yourself.
• Introduce AM/AM and AM/PM using SSPA.m.• Introduce phase-noise using add_phase_noise.m.
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SNR and SINAD
SNR=Signal power
Thermal noise power
SINAD= Signal power
Distortion + Thermal noise
Dominates at close distance.Often proportional to transmitted power
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SINAD and SNR versus range
0 100 200 300 400 500 600 700 800 900 10000
10
20
30
40
50
60
70
80
90
Distance TX<->RX
dB
SNR
SINAD
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Estimating SNR and SINAD
1960 1980 2000 2020 2040 2060 2080 2100 2120 2140 2160
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Signal + noise
Signal + noise + distortion
Part1: Before transmission: Thermal noise only. Part2: Signal present
X= S + N + E
Estimate thermal noise power from part 1.
Estimate signal power and distortion power from part 2 e.g. Using training sequence.
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Theory versus Reality
What theory ?
Generally: Basic channel model.
Present results versus SNR not SINAD
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Voice Band Transmission
FM modulator
AM modulator
FM de-modulator
AM de-modulatorIn
OutIn
Out
Power of output may be unrelated power of input.Difficult to use previous slides in this scenario.
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Wrap-up
• Propagation channel versus communication channel distinction.
• Basic channel model.• Power amplifier distortion (AM/AM and AM/PM).• Phase-noise (in up-/down-converters)• Matlab functions• SINAD versus SNR• Voice-band transmission