Abstract-Recently, a novel approach for PN code acquisition of direct sequence code division multipleaccess (DS-CDMA) systems in Rayleigh fading multipath channel was proposed in [1]. The authors considered a combination of adaptive thresholding constant false alarm rate (CFAR) and smart antennas to increase the system capacity and consequently enhance the detection performance. This paper considers still the problem of PN code acquisition for DS-CDMA communication systems over Rayleigh fading channels under the presence of multipath and multiple-access interference (MAI) signals. We propose and analyze an adaptive array acquisition system, which integrates an adaptive thresholding technique based on ordered data variability (ODV) index constant false alarm rate (ODV-CFAR) and digital beamforming where a low complexity least mean square (LMS) algorithm is used to calculate the optimal weighting coefficients. This approach is expected to mitigate interferences caused by the presence of multiple access interference and multipath. Unlike other approaches based on a fixed censoring point when the number of interferences is assumed known, ODV-CFAR processing does not require prior knowledge about the number of interferences. The simulation results show a robust performance of the proposed system in varying mobile communication channels.

Recently, cyclostationarity (CS) based detection methods exploiting the autocorrelation periodicity property of the orthogonal frequency division multiplexing (OFDM) signals attracted a lot of attention. These detection methods are more complex than energy detection but they have better detection performance in low-SNR regimes. The drawback, however, is their extensive computational complexity. In this paper, we propose a computationally efficient spectrum sensing method for detecting unsynchronized OFDM signals in additive white Gaussian noise (AWGN). The proposed method exploits the second-order CS property of OFDM signals to set an adaptive threshold, which achieves the desired constant false alarm rate (CFAR) property. The complexity of the proposed method is significantly reduced compared with the scheme proposed in [22]. Monte-Carlo simulations illustrate that the performance of the proposed detector outperforms the classical energy detector (ED), the sliding window detector (SW) and Axell's detector in addition to guaranteeing a low sensing time