Orthogonal Matching Pursuit Source Code Implementation

The attached code provides the complete source implementation of Orthogonal Matching Pursuit (OMP) algorithm, written in MATLAB with a straightforward and practical programming approach. The implementation includes core components such as residual calculation, atom selection from the dictionary, and least-squares solution for sparse signal recovery.

Orthogonal Matching Pursuit is a widely used technique in communication systems that enables wireless signal reception and demodulation under multipath propagation conditions. This greedy algorithm iteratively selects the most correlated atoms from a dictionary to approximate sparse signals, making it particularly valuable in modern communication systems. The MATLAB code demonstrates key functions including correlation computation, orthogonal projection updates, and stopping criteria based on residual thresholds or sparsity levels. Beyond OMP, other signal processing techniques like adaptive filters and wavelet transforms also find extensive applications in communication systems. For readers interested in wireless communication technologies, studying OMP along with these complementary techniques offers valuable research directions. Through the provided OMP source code, readers can gain deeper insights into the algorithm's working principles and learn how to implement it in practical communication system designs, with features including customizable dictionary generation, step-by-step iteration visualization, and performance evaluation metrics.