MATLAB Implementation of Beamforming in Array Systems: Uniform Linear Array (ULA) Conventional Beamforming

We have developed a MATLAB-based simulation program for generating beam patterns and Direction of Arrival (DOA) spatial spectrum estimation using Uniform Linear Array (ULA) Conventional Beamforming (CBF). This program runs on computers and simulates signal processing operations through algorithmic implementations. The code structure includes array signal processing modules, beamforming calculations, and spectral estimation functions, allowing users to study and understand signal processing techniques in wireless communications, thereby enhancing knowledge in this field.

The program implements the latest algorithms and techniques for computing beam patterns and DOA spatial spectrum estimation. These algorithms employ matrix operations for steering vector calculations, utilize Fast Fourier Transform (FFT) for spectral analysis, and implement covariance matrix computations for signal processing. The technical implementation helps users analyze signals more effectively and extract valuable information through proper parameter configuration. Additionally, we incorporated customizable options through configurable input parameters, enabling users to adjust and optimize settings according to their specific requirements.

The program features straightforward usage through a main execution script that processes user-defined input parameters. Users can configure signal and noise types and parameters through dedicated input functions, and adjust ULA CBF parameters including array element spacing, number of elements, and beamforming weights. The simulation framework supports multiple operation modes through mode selection parameters, allowing testing of various scenarios and conditions. The code architecture includes modular functions for signal generation, array processing, and visualization outputs.

In summary, this simulation program provides comprehensive understanding of signal processing techniques in wireless communications and serves as an experimental platform for research and practical implementation. The MATLAB implementation includes complete code documentation and example usage scenarios. We hope users can effectively utilize this tool to achieve better learning outcomes and research results.