MATLAB Implementation of Spread Spectrum Communication System

In a spread spectrum system, the process begins with generating a random binary sequence (0s and 1s). This sequence then undergoes spreading using spreading codes (typically PN sequences), pulse shaping for bandwidth control, and BPSK modulation before transmission. The receiver performs despreading using correlated codes and demodulation to recover the original signal. The complete spread spectrum system implementation includes these key stages: random sequence generation using MATLAB's randi() function, spreading through multiplication with spreading codes, pulse shaping using raised-cosine or rectangular filters, BPSK modulation through phase shifting, and synchronized despreading/demodulation at the receiver. This process ensures secure and reliable signal transmission between transmitter and receiver through spectral expansion and correlation detection. The MATLAB implementation typically involves generating orthogonal codes (like Walsh codes) or pseudo-random sequences for spreading, employing filter functions for pulse shaping, and using correlation operations for despreading. Key algorithms include code synchronization, matched filtering, and threshold detection for optimal signal recovery in noisy environments.