RF Testing and Calibration with TofuPilot

Every wireless product needs RF testing: output power, receiver sensitivity, frequency accuracy, spurious emissions. For products with WiFi, Bluetooth, LoRa, cellular, or custom RF, these measurements determine whether the product meets regulatory requirements and actually works in the field. TofuPilot stores RF test data for trending, calibration tracking, and compliance.

RF Test Parameters

Parameter	What it measures	Why it matters
TX output power (dBm)	Transmitted signal strength	Too high: regulatory violation. Too low: poor range
RX sensitivity (dBm)	Minimum receivable signal	Determines receive range
Frequency error (ppm)	Crystal/oscillator accuracy	Affects interoperability
EVM (Error Vector Magnitude)	Modulation quality	Affects data throughput
Spurious emissions	Unintended RF output	Regulatory compliance
RSSI accuracy	Received signal strength indicator	Affects link management

Logging RF Test Results

Basic RF Parametric Test

rf_test.py

from tofupilot import TofuPilotClient

client = TofuPilotClient()

def rf_production_test(serial, tx_power, rx_sensitivity, freq_error_ppm, evm_pct):
    client.create_run(
        procedure_id="RF-PARAMETRIC-BLE",
        unit_under_test={
            "serial_number": serial,
            "part_number": "IOT-SENSOR-V3",
        },
        run_passed=True,
        steps=[{
            "name": "TX Performance",
            "step_type": "measurement",
            "status": 0 <= tx_power <= 4,
            "measurements": [
                {"name": "tx_power_dbm", "value": tx_power, "unit": "dBm", "limit_low": 0, "limit_high": 4},
                {"name": "freq_error_ppm", "value": freq_error_ppm, "unit": "ppm", "limit_low": -20, "limit_high": 20},
                {"name": "evm_pct", "value": evm_pct, "unit": "%", "limit_high": 30},
            ],
        }, {
            "name": "RX Performance",
            "step_type": "measurement",
            "status": rx_sensitivity <= -90,
            "measurements": [
                {"name": "rx_sensitivity_dbm", "value": rx_sensitivity, "unit": "dBm", "limit_high": -90},
            ],
        }],
    )

Multi-Channel RF Test

Test across all operating channels to catch channel-specific issues.

rf_multi_channel.py

# BLE has 40 channels (0-39)
# Test a representative set
test_channels = [0, 12, 19, 20, 38, 39]

measurements = []
for ch in test_channels:
    set_channel(ch)
    power = measure_tx_power()
    measurements.append({
        "name": f"tx_power_ch{ch}_dbm",
        "value": power,
        "unit": "dBm",
        "limit_low": 0,
        "limit_high": 4,
    })

client.create_run(
    procedure_id="RF-MULTI-CHANNEL-BLE",
    unit_under_test={"serial_number": serial},
    run_passed=all(0 <= m["value"] <= 4 for m in measurements),
    steps=[{
        "name": "Multi-Channel TX Power",
        "step_type": "measurement",
        "status": True,
        "measurements": measurements,
    }],
)

RF Calibration

Many wireless products require per-unit RF calibration to compensate for component tolerances. The calibration process:

Measure actual TX power at a reference level
Calculate the offset from target
Write a calibration value to the DUT's flash/EEPROM
Verify calibrated output matches target

rf_calibration.py

def calibrate_rf(serial):
    # Step 1: Measure uncalibrated power
    raw_power = measure_tx_power()

    # Step 2: Calculate calibration offset
    target_power = 0.0  # dBm
    cal_offset = target_power - raw_power

    # Step 3: Write calibration to DUT
    write_cal_value(cal_offset)

    # Step 4: Verify
    calibrated_power = measure_tx_power()

    client.create_run(
        procedure_id="RF-CALIBRATION-BLE",
        unit_under_test={"serial_number": serial},
        run_passed=abs(calibrated_power - target_power) < 1.0,
        steps=[{
            "name": "TX Calibration",
            "step_type": "measurement",
            "status": True,
            "measurements": [
                {"name": "raw_tx_power_dbm", "value": raw_power, "unit": "dBm"},
                {"name": "cal_offset_db", "value": cal_offset, "unit": "dB"},
                {"name": "calibrated_tx_power_dbm", "value": calibrated_power, "unit": "dBm",
                 "limit_low": -1.0, "limit_high": 1.0},
            ],
        }],
    )

Tracking RF Performance Across Production

Calibration Offset Distribution

The distribution of calibration offsets tells you about your RF hardware consistency. A tight distribution (small offsets) means consistent PCB manufacturing. A wide or drifting distribution suggests:

Antenna placement variation
PCB impedance variation
Component lot changes (balun, matching network)

TX Power Over Time

Plot TX power across production. Look for:

Pattern	Cause
Gradual drift	Test equipment calibration drift
Step change	New component lot, PCB revision
Increased variance	Manufacturing process variation
Channel-dependent failures	Antenna or matching network issues

RX Sensitivity Monitoring

Receiver sensitivity is harder to measure in production (requires a shielded environment and calibrated signal source). Track it to catch:

LNA gain degradation
Filter mistuning
Increased noise figure from layout changes

Test Fixture Considerations

RF testing requires controlled RF environments:

Setup	Use case	Isolation
Shielded box	Production testing	60-80 dB
Anechoic chamber	Antenna characterization	80+ dB
RF cable (conducted)	Board-level testing	Direct connection

Log the fixture type and serial number with each test run. If RF test results shift, the fixture calibration or cable condition may have changed.

Regulatory Compliance Data

RF certification (FCC, CE, IC, MIC) requires specific test data. While certification testing is done at accredited labs, pre-compliance data from TofuPilot helps you:

Predict certification outcomes based on production margins
Compare production units to the original certified unit
Track any changes that could void certification

RF Testing and Calibration with TofuPilot