With the rising number of modulation types used in multi-user and multi-service digital communication systems, the need to find efficient methods for their discrimination in the presence of noise has become increasingly important. Here, we present a new approach based on a recently developed pattern recognition method previously applied to word spotting problems in binary images [ 11. In this approach, a large number of spatial moments are arranged in a symmetric positive definite matrix for which eigendecomposition and noise subspace processing methods can be applied. The resultant denoised moment matrix has entries which are used in place of the raw moments for improved pattern classification. In this paper, we generalize the moment matrix technique to grey scale images and apply the technique to discrimination between M-ary PSK and QAM constellations in signal space. Invariance to unknown phase angle and signal amplitude is achieved by representing the in-phase and quadrature components of the signal in the complex plane, and computing joint moments of normalized magnitude and phase components.
Since the transmitted signals in the downlink of a CDMA system can be time synchronized, orthogonal spreading codes are often used to separate the users' signals. In systems supporting different data-rates, sets of orthogonal codes of different periods can be applied. An important example are the Orthogonal Variable Spreading Factor (OVSF) codes in the 3GPP-WCDMA (UTRA) standard. Since the number of orthogonal codes is limited and a capacity restriction in a CDMA downlink due to code shortage should be avoided, additional (non-orthogonal) spreading codes must be available. In recent years, several construction methods for these codes have been discussed in connection with the development of CDMA-based mobile communication systems. In this paper, the resulting performance when nonorthogonal spreading codes are used is discussed for an AWGN and a fading scenario.
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