[Practical Exercise] Capturing and Analyzing Wireless Signals with MATLAB

# 2.1 Introduction to Wireless Signal Capture Hardware

Wireless signal capture hardware primarily includes:

- **Radio Frequency Frontend (RFE):** Responsible for receiving and amplifying wireless signals, and converting them into digital signals.
- **Analog-to-Digital Converter (ADC):** Converts analog signals into digital signals.
- **Digital Signal Processor (DSP):** Executes signal processing algorithms, such as filtering, demodulation, and parameter estimation.
- **Memory:** Stores captured signal data.
- **Interface:***

***mon wireless signal capture hardware includes:

- **Software Defined Radio (SDR):** A programmable hardware platform capable of capturing and processing various wireless signals.
- **Oscilloscope:** Used for measuring and analyzing electronic signals, including wireless signals.
- **Spectrum Analyzer:** Used for measuring and analyzing the spectrum of wireless signals.
- **Network Analyzer:** Used for measuring and analyzing the characteristics of networks, including wireless networks.

# 2. MATLAB Wireless Signal Capture

### 2.1 Introduction to Wireless Signal Captur***

***mon wireless signal capture hardware includes:

- **Spectrum Analyzer:** Used for measuring and analyzing the spectral characteristics of wireless signals, providing a view of the frequency domain.
- **Vector Signal Analyzer (VSA):** More advanced than a spectrum analyzer, offering both frequency and time domain views, and supporting deeper signal analysis.
- **Software-Defined Radio (SDR):** A flexible and programmable radio platform that can be used for receiving and processing various wireless signals.

### 2.2 MATLAB Wireless Signal Capture Toolbox

MATLAB provides a wireless signal capture toolbox for capturing and processing wireless signals from various hardware devices. The toolbox includes the following main features:

- **Support for Multiple Hardware:** Supports connections to MATLAB-compatible spectrum analyzers, VSAs, and SDRs.
- **Data Acquisition:** Provides functions for capturing wireless signal data from hardware, including I/Q data and metadata.
- **Signal Processing:** Contains functions for processing captured signals, including filtering, demodulation, and parameter estimation.
- **Visualization:** Offers functions for visualizing captured signals, including spectrum plots, constellation diagrams, and time-domain plots.

### 2.3 Wireless Signal Capture Practice

Using the MATLAB wireless signal capture toolbox to capture wireless signals involves the following steps:

1. **Connect Hardware:** Connect the wireless signal capture hardware to the computer and configure MATLAB to recognize it.
2. **Configure Capture Parameters:** Set parameters such as capture frequency range, sampling rate, bandwidth, and gain.
3. **Begin Capture:** Start capturing wireless signal data using the `spectrumCapture` function.
4. **Stop Capture:** Stop capturing using the `spectrumCapture` function.
5. **Process Captured Data:** Use functions in the MATLAB wireless signal capture toolbox to process the captured data, including filtering, demodulation, and parameter estimation.

**Code Block:**

% Connect Hardware
spectrumAnalyzer = spectrumAnalyzer('Vendor', 'Keysight', 'Model', 'N9020A');
connect(spectrumAnalyzer);

% Configure Capture Parameters
captureParameters = struct(...
     'FrequencyRange', [900e6, 1100e6], ...
     'SampleRate', 10e6, ...
     'Bandwidth', 10e6, ...
     'Gain', 0 ...
);

% Begin Capture
data = spectrumCapture(spectrumAnalyzer, captureParameters, 10);

% Stop Capture
stop(spectrumAnalyzer);

**Code Logic Analysis:**

* The `spectrumAnalyzer` function connects to the Keysight N9020A Spectrum Analyzer.
* The `captureParameters` structure sets the capture parameters, including frequency range, sampling rate, bandwidth, and gain.
* The `spectrumCapture` function begins capturing data for a duration of 10 seconds.
* The `stop` function stops the capture.

**Table:**

| Parameter | Description |
|---|---|
| FrequencyRange | Capture frequency range |
| SampleRate | Sampling rate |
| Bandwidth | Capture bandwidth |
| Gain | Capture gain |

# 3. MATLAB Wireless Signal Analysis

### 3.1 Wireless Signal Spectrum Analysis

**Spectrum analysis** is a fundamental task in wireless signal analysis, revealing the spectral characteristics of signals, including bandwidth, center frequency, power spectral density, etc. MATLAB provides powerful spectrum analysis tools, including functions like `pspectrum`, `spectrogram`, and `periodogram`.

**The `pspectrum` function** is used to calculate the power spectral density (PSD) of a signal, which can display the frequency distribution and power levels of the signal. Its syntax is as follows:

[Pxx,F] = pspectrum(x,Fs)

Where:

* `x`: Input signal
* `Fs`: Sampling frequency
* `Pxx`: Power spectral density
* `F`: Frequency vector

**Code Logic Analysis:**

The `pspectrum` function uses the Welch method to calculate the power spectral density. It segments the signal, applies windowing to each segment, and then calculates the power spectrum for each segment. Finally, it averages the power spectra of all segments to obtain the final power spectral density.

**The `spectrogram` function** is used to compute the time-frequency spectrum of a signal, displaying the frequency characte