Hardware Modeling

 1# In this example we simulate the effects of a non-ideal
 2# Radio-Frequency chain and analog-to-digital conversion on the bit error rate performance
 3# of a single-carrier communication system.
 4# We consider I/Q imbalance, a power amplifier following Rapp's model and an adc with
 5# mid-riser quantization and automatic gain control.
 6# 
 7# The performance is evaluated for a signal-to-noise ratio between zero and 20 dB.
 8
 9!<Simulation>
10
11# Physical device models within the simulated scenario
12Devices:
13
14  - &device_alpha !<SimulatedDevice>
15
16    # RF-Chain hardware model
17    rf_chain: !<RfChain>           
18
19      amplitude_imbalance: 1e-3          # I/Q amplitude imbalance
20      phase_offset: 1e-2                 # I/Q phase imbalance
21      power_amplifier: !<Rapp>           # Power amplifier model
22
23    # AD-Conversion hardware model
24    adc: !<ADC> 
25
26      quantizer_type: mid_riser
27      gain: !<AutomaticGainControl>
28
29# Operators transmitting or receiving signals over the devices
30Operators:
31
32  # A single modem operating the device #0
33  - &modem_alpha !<Modem>
34
35    device: *device_alpha           # Device the modem is operating on
36
37    # Waveform configuration
38    waveform: !<SC-RootRaisedCosine>
39
40        # Symbol settings
41        symbol_rate: 100e6
42        modulation_order: 16
43        oversampling_factor: 4
44
45        # Frame settings
46        num_preamble_symbols: 10
47        num_data_symbols: 1000
48        pilot_rate: 1e6
49        guard_interval: 1e-6
50
51# Performance indication evaluation configuration
52Evaluators:
53
54  # Evaluate the bit errors of `modem_alpha` communicating over `device_alpha`
55  - !<BitErrorEvaluator>
56
57    transmitting_modem: *modem_alpha
58    receiving_modem: *modem_alpha
59    confidence: .9
60    tolerance: 1e-4
61    plot_scale: log
62
63# Simulation parameters
64num_samples: 10000                 # Number of samples per simulation grid section
65min_num_samples: 50                # Minimum number of samples per simulation grid section before premature stopping
66snr_type: EBN0                     # SNR is defined as the ratio between bit energy and noise power
67plot_results: True                 # Visualize the evaluations after the simulation has finished
68
69# Scenario parameters over which the Monte-Carlo simulation sweeps
70Dimensions:
71
72  snr: [0, 1, ..., 20] dB