Simulation of Anti-Jamming Performance Against White Gaussian Noise in Direct Sequence Spread Spectrum

In this paper, we investigate the simulation of anti-jamming performance of Direct Sequence Spread Spectrum (DSSS) technology in white Gaussian noise environments. First, we provide a brief introduction to the principles and applications of DSSS technology, including the fundamental process of spreading narrowband signals using pseudo-random codes and the correlation-based despreading mechanism. Then, we analyze in detail the impact of white Gaussian noise on signal transmission, examining how additive noise affects bit error rate (BER) performance and signal-to-noise ratio (SNR) degradation. The discussion further explores methods to enhance anti-jamming capability through DSSS improvements, such as optimizing pseudo-random sequence selection, implementing advanced correlation detectors, and employing error correction coding techniques. From an implementation perspective, we describe key algorithms including the generation of spreading codes using linear feedback shift registers, the mathematical modeling of AWGN channels using randn() functions in MATLAB, and the simulation of correlation receivers with integrate-and-dump filters. Finally, we demonstrate the effectiveness of the proposed approaches through comprehensive simulation experiments. The simulation framework includes MATLAB code structures for generating DSSS signals, adding Gaussian noise with varying power levels, and calculating performance metrics like BER curves and processing gain. We present comparative results showing improved noise resistance and discuss potential future research directions including multi-user interference mitigation and adaptive spreading factor optimization.