Narrowband interference suppression in DSSS system based on maximum entropy PDF estimation

In order to suppress the strong narrowband interference in the direct sequence spread spectrum (DSSS) system, a new locally optimal detector (LOD) based on maximum entropy probability density function (PDF) estimation is proposed. The maximum entropy PDF estimation used to predict and mathematically express the probability that density function of observation noise can be applied into LOD to reduce the error from PDF estimation. Meanwhile, a new nonlinear Gauss-Newton algorithm based on LMS initial parameter design was adopted to estimate the Lagrange weights of maximum entropy PDF. This interference rejection technology didn't need any exercise data and signal amplitude message. The simulation results indicated that the LOD based on maximum entropy PDF estimation can forcefully suppress narrowband interference and represent the triangle relation characteristic of DS signal. When the input JNR is 20 dB, the JNR improvement after this LOD is respectively improved for 30 dB and 26 dB compared with linearly adaptive FIR filter and nonlinearly adaptive ACM filter, meanwhile the SNR is respectively improved for 3.1 dB and 1.6 dB, and the JNR improvement is larger for larger input JNR.