Abstract: The present invention is a method and apparatus for mitigating phase noise in data communication systems. The present invention provides effective phase noise mitigation with very low latency by combining the decision feedback equalizer and carrier recovery loop effectively. The phase noise estimate is obtained by calculating the phase difference between the input and output of the decision device (DD) in the decision feedback equalizer (DFE) and then applying a digital phase locked loop (DPLL) on the phase difference. Deriving the phase noise estimate from the phase noise estimation process, phase noise mitigation is obtained by multiplying the phase noise estimate at the input signal of the feedforward filter (FFF) and at the input signal of the DD in DFE. An accurate signal-to-noise ratio (SNR) estimate is also obtained in the process of the filter coefficient update process in the DFE.

Abstract: An improved Pseudo Noise (PN) code acquisition apparatus and method for Code Division Multiple Access (CDMA) Direct Sequence Spread Spectrum (DSSS) systems which utilize a Fourier Transform and which operate in both additive white Gaussian noise and frequency offset environments. The signal to noise ratio (SNR) is generated and used not only to make the decision of when to stop the signal search process but also to adjust the search rate. The Fourier transform is implemented in ASIC hardware to estimate frequency offset. To further speed up its processing, the Fourier transform is performed using shift and add operations by employing canonic sign digit representation of the eigen vector of the Fourier transform. Detection probability is increased and false alarm probability is reduced significantly, especially in a frequency offset environment.

Abstract: A decoding method for use in a communications system employing a communication channel in which a message is convolutionally encoded by a base station encoder and transmitted to a remote terminal during a time slot allocated to at least that remote terminal. The encoder is not completely reset immediately prior to the allocated time slot such the encoder state is unknown at the onset thereof. The decoding method includes assigning a most likelihood probability for an initial encoder state as being one of a number of predetermined encoder states; and, convolutionally decoding ensuing bits of the message based on the assumption of the initial encoder state as one of the predetermined states. The method affords low error rate decoding, and allows for improved power conservation by a mobile station, since the mobile station need not awaken significantly prior to its allocated time slot. Preferably, a Viterbi decoder is used to perform the convolutional decoding.

Abstract: In the front end of a mobile phone receiver for operation in a network using DSSS signals, detection of a carrier frequency offset in a received PN-modulated signal is performed by first correlating the received signal with a local replica of the PN codes generated within the receiver. The resulting despread signal is integrated over a fixed period, or dwell, of time, then run through a square-law envelope detector. The integration is divided into a plurality of sub-dwells, the values of which are each provided as an input to a Fast Fourier Transform (FFT) to generate a plurality of frequency bins. The magnitude for each FFT frequency bin is computed and a maximum value is selected. The maximum value and its corresponding bin number are saved in the signal processor's memory. The next PN code phase is tested and, depending on the search scheme, this sequence continues until the decision algorithm terminates the search.

Abstract: A PN code acquisition system for Code Division Multiple Access (CDMA) Direct Sequence Spread Spectrum (DSSS) systems, with automatic decision threshold, is based on the combination of the Maximum Likelihood (ML) and Serial Search (SS) acquisition approaches. In contrast to the conventional SS acquisition system, the disclosed system adaptively estimates optimal threshold by exploiting the statistics of the signal and noise, and makes an optimal decision based on the threshold. The system estimates the threshold by employing ML estimation and applies the threshold as in SS acquisition and makes a decision by comparing the updated threshold with the current signal strength. Together with post detection verification logic, this approach will increase detection probability and reduce false alarm probability significantly. An optimum system parameter design approach and the advantages of this approach as compared to conventional approaches (ML or SS acquisition) are demonstrated.

Abstract: There is disclosed a system and method for generating coefficients for use in a digital filter. The coefficients are generated utilizing an iterative adaptive process employing a least mean square process wherein the filter coefficients are updated by an amount during each iteration dependent upon the stochastic average of the gradient generated during prior iterations. The response of a filter standard to an applied input signal is combined with a response of the adaptive filter coefficients to generate, during each iteration, an error signal. If the error signal is less than a predetermined standard, the iterative process is stopped, and the last used filter coefficients are utilized as the final filter coefficients of the digital filter.