【Advanced Chapter】Design and Simulation of Cognitive Radio Systems in MATLAB

# 2.1 Architecture and Components of Cognitive Radio Systems

A cognitive radio system is a complex system composed of multiple components that work together to achieve spectrum sensing and management.

### 2.1.1 Spectrum Sensing and Management

Spectrum sensing is a key component of a cognitive radio system, responsible for detecting and identifying available spectrum. Spectrum sensing algorithms employ various techniques, such as energy detection, matched filtering, and collaborative sensing, to detect unused frequency bands.

The spectrum management module is responsible for allocating and managing available spectrum. It uses spectrum sensing information to determine the optimal channels and power levels to maximize spectrum utilization and minimize interference.

# 2. Modeling Cognitive Radio Systems in MATLAB

### 2.1 Architecture and Components of Cognitive Radio Systems

#### 2.1.1 Spectrum Sensing and Management

Spectrum sensing is a vital part of cognitive radio systems, tasked with detecting and recognizing available spectrum. MATLAB offers various tools and libraries to implement spectrum sensing, including:

- `spectrum.SpectrumAnalyzer`: Used for analyzing spectrum data, detecting spectrum vacancies, and interference.
- `spectrum.OccupancyMonitor`: Monitors spectrum occupancy and triggers events in response to spectrum changes.
- `spectrum.SpectrumSensing`: Provides advanced spectrum sensing algorithms such as energy detection, covariance detection, and cyclostationary feature detection.

#### 2.1.2 Cognitive Engine and Decision Module

The cognitive engine is the core of cognitive radio systems, responsible for processing spectrum sensing information and making decisions about spectrum access and transmission. MATLAB provides the following tools to implement the cognitive engine:

- `comm.CognitiveRadioEngine`: Offers a configurable framework for building and simulating cognitive radio systems.
- `comm.CognitiveRadioDecision`: Provides a set of functions for implementing spectrum access and transmission decision algorithms.
- `comm.CognitiveRadioWaveform`: Offers a set of functions for generating and processing cognitive radio waveforms.

### 2.2 Cognitive Radio System Modeling Tools in MATLAB

#### 2.2.1 Wireless Channel Modeling

MATLAB provides a wide range of wireless channel modeling tools for simulating the wireless environment in cognitive radio systems. These tools include:

- `comm.RayleighChannel`: Used for generating Rayleigh fading channels.
- `comm.AWGNChannel`: Used for generating additive white Gaussian noise channels.
- `comm.PathLoss`: Used for calculating path loss.

#### 2.2.2 Cognitive Radio Algorithm Implementation

MATLAB provides various functions and toolboxes for implementing cognitive radio algorithms, such as:

- `comm.OFDMModulator`: Used for implementing orthogonal frequency-division multiplexing (OFDM) modulation.
- `comm.OFDMDemodulator`: Used for implementing OFDM demodulation.
- `comm.MIMOProcessor`: Used for implementing multiple-input multiple-output (MIMO) processing.

% Create a cognitive radio system object
crSystem = comm.CognitiveRadioSystem;

% Set spectrum sensing parameters
crSystem.SpectrumSensingMethod = 'EnergyDetection';
crSystem.SensingThreshold = -10;

% Set cognitive engine parameters
crSystem.DecisionMethod = 'MaxThroughput';
crSystem.AccessThreshold = 0;

% Set wireless channel parameters
channel = comm.RayleighChannel;
channel.PathDelays = [0 0.5 1];
channel.AveragePathGains = [0 -3 -6];

% Set modulation and demodulation parameters
modulator = comm.OFDMModulator;
demodulator = comm.OFDMDemodulator;

% Simulate the cognitive radio system
[receivedSignal, spectrumData] = crSystem(modulator(data), channel);
demodulatedData = demodulator(receivedSignal);

% Analyze system performance
throughput = sum(demodulatedData == data) / length(data);

**Logical Analysis:**

This code simulates a cognitive radio system where:

- The `crSystem` object performs spectrum sensing and decision-making.
- The `channel` object simulates the wireless channel.
- The `modulator` and `demodulator` objects perform modulation and demodulation.
- The `throughput` variable calculates the system throughput.

# 3. Cognitive Radio System Simulation

### 3.1 Cognitive Radio System Simulation Environment

#### 3.1.1 Simulation Tools and Libraries in MATLAB

MATLAB offers a wide range of simulation tools and libraries for modeling and simulating cognitive radio systems. These tools include:

- **Communications System Toolbox:** Provides functions for wireless channel modeling, modulation and demodulation, multiple access, and multiple-input multiple-output (MIMO) systems.
- **Radio Comm