Description
Part 1: baseband digital transmission
Objectives: To understand the basic concepts of
• analog‐to‐digital & digital‐to‐analog conversions.
• baseband digital transmission over AWGN channels.
• SNR and BER.
Preparation
For this lab, the following Simulink blocks will be used.
ADC/DAC System
Build the ADC/DAC system as illustrated.
ADC/DAC System: Parameter setup
Sine Wave: Sine type: Time based | Amplitude: 2 | Frequency (rad/sec): 500*2*pi
Rate Transition: Output port sample time: 1e‐5
Pulse Generator: Pulse type: Time based | Amplitude: 1 | Period (secs): 0.001/8 |
Pulse Width (% of period): 50
Scalar Quantizer Encoder: Partitioning: Bounded | Boundary points: ‐2:0.5:2 |
Output codeword | Codebook: [‐1.75:0.5:1.75]
Scalar Quantizer Decoder: Codebook values: [‐1.75:0.5:1.75]
Analog Filter Design: Design method: Butterworth | Filter type: Lowpass | Filter
order: 20 | Passband edge frequency (rad/s): 500*2*pi
ADC/DAC System: Experiments
1. Compare the outputs on Scope (ADC) and Scope(S/H). Explain how the Scalar
Quantizer Encoder converts the analog input to the digital output.
2. Compare the outputs on Spectrum (Source) and Spectrum (Sample). Comment on
the effect on the spectrum of the source signal when multiplying with a pulse train.
Explain why the output of the analog lowpass filter is the recovered source signal.
3. Observe the output on Scope (ADC). Comment on the number of quantization levels
and quantization bits utilized. Repeat for the following parameter setup: Scalar
Quantizer Encoder Boundary points: [‐2:2] | Codebook values: [‐1.5:1:1.5]; Scalar
Quantizer Decoder Codebook values: [‐1.5:1:1.5]. Comment on the performance
difference.
Baseband Transmission over AWGN Channel
Build the baseband transmission and reception model as illustrated.
Baseband Transmission over AWGN Channel:
Experiment
Parameter setup:
Bernoulli Binary Generator (Source): Sample time: 0.001
Constant (DC Bias): Constant value: 0.5
Gain Gain: 10
AWGN Channel: Initial seed: randseed | Mode: Signal to noise ratio (Eb/No) |
Number of bits per symbol: 1 | Input signal power, referenced to 1 ohm (watts):
25 | Symbol period (s): 0.001
Pulse Generator: Pulse type: Sample based | Amplitude: 1 | Period (number of
samples): 2 | Pulse width (number of samples): 1 | Phase delay (number of
samples): 1 | Sample time: 0.5e‐3
Lookup Table: Table data: [‐5,‐5,5] | Breakpoints specification: Explicit values |
Breakpoint 1: [‐1,0,1]
Error Rate Calculation: Receive delay: 1 | Output data: Port
Plot the BER‐versus‐Eb/No curve with Eb/No (dB)= 0, 2, 4, 6, 8, 10.
Part 2: basic digital modulation schemes
Objectives: To understand the basic concepts of digital modulation
schemes: binary PSK, ASK,FSK, and 4QAM, and the modulated signal
power spectra
Preparation
For this lab, the following Simulink blocks will be used.
Binary ASK Modulation
Build the Binary ASK modulation and demodulation model as illustrated.
Binary ASK Modulation: Experiment
Parameter setup:
Bernoulli Binary Generator (Source): Probability of zero: 0.5 | Source of initial
seed: Parameter | Initial seed: randseed | Sample time: 0.001
Sine Wave (Mod): Sine type: Sample based | Samples per period: 5000 | Sample time:
1e‐7
Sine Wave (Demod): Sine type: Sample based | Samples per period: 5000 | Sample
time: 1e‐7
Rate Transition: Output port sample time: 0.5e‐4
1‐D Lookup Table: Table data: [0,0,1]| Breakpoints 1: [‐1,0,1]
1. Consider binary ASK. Observe the output on Scope (Mod). Describe how the
transmitted signal is generated from the binary data streams.
Binary PSK Modulation
Build the Binary PSK modulation model as illustrated.
Binary PSK Modulation: Experiment
Build the Binary PSK modulation model as illustrated.
Bernoulli Binary Generator (Source): Probability of zero: 0.5 | Initial seed: randseed |
Sample time: 0.001
1‐D Lookup Table1: Table data: [‐1,1]| Breakpoints 1: [0,1]
1‐D Lookup Table: Table data: [0,0,1]| Breakpoints 1: [‐1,0,1]
Sine Wave (Mod): Sine type: Sample based | Samples per period: 5000 | Sample time:
1e‐7
Sine Wave (Demod): Sine type: Sample based | Samples per period: 5000 | Sample
time: 1e‐7
Rate Transition: Output port sample time: 0.5e‐4
2. Consider binary PSK. Observe the output on Scope (Mod). Describe how the
transmitted signal is generated from the binary data streams.
Binary FSK Modulation
Build the Binary FSK modulation model as illustrated.
Binary FSK Modulation: Experiment
Parameter setup:
Bernoulli Binary Generator (Source): Probability of zero: 0.5 | Initial seed: randseed |
Sample time: 0.001
1‐D Lookup Table (Mod): Table data: [‐1,1]| Breakpoints 1: [0,1]
1‐D Lookup Table (Demod): Table data: [0,0,1]| Breakpoints 1: [‐1,0,1]
Sine Wave(Mod/Lower): Sine type: Sample based | Samples per period: 4000 | Sample
time: 1e‐7
Sine Wave(Mod/Upper): Sine type: Sample based | Samples per period: 2857 | Sample
time: 1e‐7
Sine Wave(Demod/Lower): Sine type: Sample based | Samples per period: 4000 | Sample
time: 1e‐7
Sine Wave(Demod/Upper): Sine type: Sample based | Samples per period: 2857 | Sample
time: 1e‐7
Switch: Threshold: 0
Rate Transition: Output port sample time: 0.5e‐4
3. Consider binary FSK. Observe the output on Scope (Mod). Describe how the
transmitted signal is generated from the binary data streams. Specify the carrier
frequencies used for modulation and the corresponding frequency separation.
4-QAM Modulation
Build the 4‐QAM modulation model as illustrated.
4-QAM Modulation: Experiment
Parameter setup:
Random Integer Generator (Source): Set size: 4 | Sample time: 0.001
Integer to Bit Converter: Number of bits per integer(M): 2
1‐D Lookup Table (I): Table data: [‐sqrt(0.5),sqrt(0.5)] | Breakpoints 1: [0,1]
Sine Wave (I): Sine type: Sample based | Samples per period: 5000 | Number of offset
samples: 1250 | Sample time: 1e‐7
1‐D Lookup Table (Q): Table data: [‐sqrt(0.5),sqrt(0.5)] | Breakpoints 1: [0,1]
Sine Wave (Q): Sine type: Sample based | Samples per period: 5000 | Number of offset
samples: 0 | Sample time: 1e‐7
Rate Transition: Output port sample time: 0.5e‐4
4. Consider 4‐QAM. Observe the output on Scope (Mod). Describe how the transmitted
signal is generated from the binary data streams. Explain how 4‐QAM can be
implemented from binary PSK. Explain how the power spectrum of 4‐QAM is related
to that of binary PSK.
ASK, PSK, FSK: bandwidth comparison
5. What are the transmission bandwidths of binary ASK and
binary PSK? Explain how their power spectra are related.
6. What is the transmission bandwidth of binary FSK? For binary
ASK, PSK, and FSK, which one(s) is most bandwidth efficient?
Part 3:
M
‐QAM modulation
& demodulation
Objectives: To understand
• the basic principles of 16‐QAM modulation and demodulation.
• the effect of noise through scatterplots.
• the relationship between SNR and BER.
• M‐QAM: power and bandwidth efficiencies
Preparations
For this lab, the following Simulink blocks will be used.
16-QAM Modulation
Build the 16‐QAM modulation model as illustrated.
16-QAM: Parameter setup
Bernoulli Binary Generator (Source): Probability of zero: 0.5 | Sample time: 1e‐6 |
Samples per frame: 4
Rectangular QAM Modulator: Baseband M‐ary number: 16 | Input type: Bit |
Normalization method: Average power | Average power, referenced to 1 ohm
(watts): 1
AWGN Channel: Initial seed: randseed | Mode: Signal to noise ratio (Es/No) | Es/No
(dB): 15 | Input signal power, referenced to 1 ohm (watts): 1 | Symbol period (s): 6e‐
6
Constellation Diagram: → Main → Samples per symbol: 1 | Reference
constellation → Reference constellation: 16‐QAM | Average reference power: 1
Rectangular QAM Demodulator Baseband: M‐ary number: 16 | Input type: Bit |
Normalization method: Average power | Average power, referenced to 1 ohm
(watts): 1
Sine Wave (I): Frequency 100 | Phase offset (rad): pi/2 | Sample time: 1e‐6
Sine Wave (Q): Frequency 100 | Phase offset (rad): 0 | Sample time: 1e‐6
Gain: Gain: ‐1
Error Rate Calculation: Stop simulation: Target number of errors → 100, Maximum
number of symbols: 1e6
16-QAM: Experiment
1. Observe the output on Constellation. How many bits does each symbol carry?
Describe the mapping between bits and symbols. Explain how 16‐QAM can be
expressed as an orthogonal superposition of two lower‐order real modulation
schemes.
2. Describe how a noisy received signal is demodulated.
3. Observe the output on Constellation Diagram. Explain the effect of additive white
Gaussian noise on the transmitted signals.
4. Change Es/No (dB) in AWGN Channel. Run the simulation. Observe the output on
Constellation Diagram. Explain how SNR affects the received constellation and
therefore the BER.
5. Plot the BER‐versus‐ Es/No curve for Es/No from 5 dB to 20 dB.
M-QAM: Experiment
6. Repeat Step 5 for 64‐QAM (Es/No from 5 dB to 25 dB).
Bernoulli Binary Generator (Source): Samples per frame: 6
Rectangular QAM Modulator Baseband: M‐ary number: 64 | Input type: Bit |
Normalization method: Average power | Average power, referenced to 1 ohm
(watts): 1
Rectangular QAM Demodulator Baseband: M‐ary number: 64 | Output type:
Bit | Normalization method: Average power | Average power, referenced to 1
ohm (watts): 1
AWGN Channel: Symbol period (s): 6e‐6
Constellation Diagram: → Main → Samples per symbol: 1 | Reference
constellation → Reference constellation: 64‐QAM | Average reference power: 1
7. Repeat Step 5 for 256‐QAM (Es/No from 10 dB to 30 dB, AWGN Channel: Symbol
period (s): 8e‐6).
How to set Bernoulli Binary Generator (Source), Rectangular QAM Modulator
Baseband, Rectangular QAM Demodulator Baseband, AWGN Channel, and
Constellation Diagram? Comment on the differences in BERs. Observe the outputs
on Constellation Diagram and Spectrum. Explain why the BER performances are
different from the viewpoint of transmission bandwidth and the distance between
constellation symbols.
