A Robust Auto-Adaptive Approach For Serial Acquisition Of Generalized Multi-Carrier Spread Spectrum In Multipath Fading Mobile Channels

In this paper, a new robust auto-adaptive approach for pseudo-noise (PN) code acquisition is proposed. It is applied to the generalized multi-carrier direct-sequence code-division multiple-access (MC DS-CDMA) systems communicating over frequency-selective multipath Rayleigh fading channels. This new approach is based on the constant false alarm rate (CFAR) detection algorithm, referred here as automatic selection partial sum ordered statistics (ASPSOS)-CFAR. The proposed approach does not require any prior information about the background environment and uses maximum likelihood estimation (MLE) method to detect the interfering signals group in the ranked cells for the full reference window. Once this group is identified and censored, the remaining smaller ranked cells are combined to form an estimate of the background noise level to compute the adaptive threshold. Through simulations, the performance of the proposed detector is analyzed and compared with traditional CFAR detectors based on fixed or automatic censoring algorithms. The obtained results show that the proposed detector eliminates the drawbacks of the previously related detectors and offers a robust detection performance to enhance the acquisition process in heterogeneous background environments.