Suppression of narrow band interference in cdma cellular radio telephone using higher order statistics

الملخص EN

In this paper, the performance of a Code Division Multiple Access (CDMA) cellular communication system in the presence of narrowband interference is investigated when an interference canceller is employed.

The interference canceller consists of an adaptive transversal filter whose coefficients are determined by using linear prediction and the least mean kurtosis (LMK) algorithm, which is an adaptive algorithm based on higher order statistics (HOS).

The standard LMK algorithm is very responsive to large values of prediction errors; it may quickly become unstable unless a very small adaptation gain parameter is employed.

In this study, we first show that the LMK algorithm can simply be viewed as a variable step size least-mean square (LMS) algorithm where the step size adjustment is controlled by the square of prediction error and its variance.

Second, we provide a modification to the LMK algorithm to ensure that the mean-square error of the algorithm remains bounded.

Simulation results are presented to demonstrate the effectiveness of the use of such an adaptive filter in mitigating narrowband interference in direct sequence spread spectrum (DS-SS) systems.

Speed of convergence, signal-to-noise ratio improvement (SNRI), and error rate performance of a receiver that employs the modified LMK algorithm are examined.

In addition, the results obtained by the modified LMK algorithm are compared with the results obtained by the commonly-used LMS algorithm.