INTERFERENCE REJECTION BASED ON HIGHER-ORDER STATISTICS AND GENETIC ALGORITHM IN DIRECT-SEQUENCE SPREAD SPECTRUM COMMUNICATION SYSTEMS

     This project is designed based on the concept of interference rejection filter, a new higher order statistics(H0S) and genetic algorithm (GA)-based filter is designed using Matlab. When a reference signal, which is highly correlated with the interference, is available, the new method uses GA to update the adaptive filter coefficients after the HOS of the primary and reference signal are computed. Compared with the adaptive filters based on second-order statistics, the HOS and GA-based filter can reject the interference more efficiently and is independent of uncorrelated Gaussian noise. The HOS and GA-based adaptive filter tends to convergence to the optimum and is much less sensitive to the choice of the step size parameter than the adaptive filters based on the gradient algorithm. Matlab simulations show that the method can reject narrowband interference efficiently.

Reference Paper: Interference Rejection in Direct-Sequence Spread Spectrum Communication Systems Based on Higher-Order Statistics and Genetic Algorithm

Author’s Name: Li Taijie, Hu Guangrui, and Gu Qing

Source: IEEE

Year:2000

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