Describes the design and the implementation of a fully-digital spread-spectrum code division multiple access (CDMA) receiver. Its specification are based on the requirements of a S-band Data Relay Satellite User which represents one of the most drastic requirements for a CDMA receiver. The receiver is divided into two parts: a rad-hard ASIC, which implements most of the power-consuming digital functions and a general-purpose microprocessor, which is in charge of the final monitoring of the recovery loops. The presented architecture is reusable for many other applications using spread spectrum communications.>

The problem of adapting linear and nonlinear recursive filters through a gradient-based optimization procedure is considered. The rigorous application of this technique implies a time-growing computation load. Recently, a method for estimating the weight updates was introduced, leading to a new class of algorithms. The convergence properties of these algorithms, when applied to a linear and then a nonlinear recursive filter, are exhibited through a dynamical analysis of the adaptation process. Since the general analysis is very difficult, the case of a first-order filter with a constant input is considered. Significant results are obtained in this particular application.>

The stability of the classical differential pulse code modulation (DPCM) transmission systems is considered in the sense of having a bounded prediction error e=s-s for a bounded input s. The difficulty stems from the nonlinear and recursive nature of the predictor, due to the inclusion of quantization in the filtering loop that achieves prediction. The classical stability constraints of linear filters are currently imposed on the loop filter. It is shown that these constraints are unnecessarily restrictive. For instance, when the loop filter is a one-order cell, its unique coefficient can overcross the value 1. In the second-order case, the coefficients a/sub 1/, a/sub 2/ may lie outside the stability triangle. This is a consequence of the amplitude limitation at the quantizer output.>

The authors consider adaptive prediction with an IIR (infinite impulse response) moving average (MA) part, controlled either by the recursive least-mean squares (LMS) algorithm or by an extended least squares (ELS) algorithm based on a posteriori errors. The predictor input is either the sum of bandpass components or a nonstationary speech sentence. The bounded input/bounded output (BIBO) stability is a major issue. Although both algorithms enjoy the self-stabilization property when the input is stationary, it is shown that with a nonstationary input the LMS algorithm can be unstable due to power jumps in the speech. The ELS algorithm always ensures BIBO stability.>