NBI Parameter Estimation in DSSS Communications Based on Partial Reconstruction

The existing NBI parameter estimation algorithms for DSSS communications are confined to the high sampling rate. In order to solve the problem above, the compressive sensing (CS)is applied to the NBI parameter estimation in DSSS communications. A partial reconstruction algorithm is proposed to get the NBI feature vector from the compressed signal using the different feature of DSSS signal and NBI in compressed domain and the block sparsity feature of NBI in frequency domain. Besides, an edge location estimation method is proposed to realize the NBI parameter estimation by estimating the edge of the transformed feature vector. We will achieve the NBI bandwidth estimation after we get the edge location. Reported simulation results demonstrate that the proposed methods are effective to the NBI parameter estimation in DSSS communications. The performance is mainly affected by the variety of interference intensity and compression rate. Under the condition of same interference bandwidth, the larger the interference intensity is and the greater the compression rate is, the better the interference parameter estimation performance is.