Ati Technologies Inc.

Ati Research, Inc.

Stephen L Biracree

Christopher H Strolle

Thomas J Endres

Samir N Hulyalkar

Raul Alejandro Casas

Raúl Alejandro Casas

Azzedine Touzni

Binning Chen

Samuel Reichgott

Mark Hryszko

Punyabrata Ray

Rajan Aggarwal

Anand M Shah

Troy A Schaffer

Azzédine Touzni

An apparatus, for use in a receiver configured to receive electronic signals, for identifying digital signals that are available for reception, includes a timing recovery device configured to receive an incoming signal, related to a transmitted signal, the incoming signal having a first symbol rate, and to re-sample the incoming signal to provide a second symbol rate, and an analyzer that is in communication with the timing recovery device and that is configured to make a determination as to whether a difference between the second symbol rate and a third symbol rate of a transmitter providing the transmitted signal is within an acceptable tolerance and to use the determination in an analysis of whether the transmitted signal is available for reception.

Rapid channel signal identification

Carrier phase recovery employs a single-axis blind cost criterion from the Bussgang class of functions, and its stochastic gradient, to generate a carrier phase error used to adjust a received and demodulated signal to near baseband. For one implementation, the estimate is derived in accordance with a Single-Axis Constant Modulus (SA-CM) criterion and its stochastic gradient via a SA-CM algorithm (SA-CMA). The carrier phase error is then used to adjust the carrier frequency and phase of the received and demodulated signal toward the frequency and phase of the carrier used to modulate the transmitted symbols, driving the carrier phase error to zero. The values used for the phase recovery may be either i) an IIR filtered signal, ii) a processed signal (e.g., decisions for the signal symbols), or iii) an equalized and processed signal.

Carrier phase estimation based on single-axis constant modulus cost criterion and Bussgang criteria

A single-axis receiver processing, for example, complex vestigial sideband modulated signals with an equalizer with forward and feedback filters. Forward and feedback filters have parameters that are initialized and adapted to steady state operation. Adaptive equalization employs linear predictive filtering and error term generation based on various cost criteria. Adaptive equalization includes recursive update of parameters for forward and feedback filtering as operation changes between linear and decision-feedback equalization of either single or multi-channel signals. An adaptive, linear predictive filter generates real-valued parameters that are employed to set the parameters of the feedback filter. In an initialization mode, filter parameters are set via a linear prediction filter to approximate the inverse of the channel's impulse/frequency response and a constant modulus error term for adaptation of the filter parameters. In an acquisition mode, equalization is as linear equalization with a constant modulus error term, and possibly other error terms in combination, for adaptation of the filter parameters. In a tracking mode, equalization is as decision feedback equalization with decision-directed error terms for adaptation of the filter parameters. For some equalizer configurations, feedback filtering is applied to real-valued decisions corresponding to complex-valued received data, and includes real-part extraction of the error term employed for recursive update of filtering parameters. Where a training sequence is available to the receiver, initial parameters for forward filtering are estimated by correlation of the received signal with the training sequence.

Linear prediction based initialization of a single-axis blind equalizer for VSB signals

Symbol timing recovery employs a blind cost criterion from the Bussgang class of functions, and its stochastic gradient, to generate a timing phase error used to adjust sampling of received symbols. For one implementation, the estimate is derived in accordance with the Constant Modulus (CM) criterion and its gradient via the CM algorithm (CMA), and the estimate is calculated from a sequence of samples. This estimate is then used to adjust the period and phase of the sample sequence toward the period and phase of the transmitted symbols, driving the timing phase error to zero. The values used may be either i) samples themselves, ii) processed (e.g., interpolated) samples, or iii) equalized and processed samples. In addition, timing phase error estimates for other cost criteria, including the least mean squares algorithm, may be generated. These timing phase error estimates are selected either alone or in combination for deriving the timing phase error used to adjust the period and phase of the sample sequence.

Blind cost criterion timing recovery

A digital communication receiver includes a blind equalizer using the Constant Modulus Algorithm (CMA) to compensate for channel transmission distortion in digital communication systems. Improved CMA performance is obtained by using a partial trellis decoder to predict 1 bit or 2 bits of the corresponding 3-bit transmitted symbol. The predicted bits from the partial trellis decoder are used to reduce the effective number of symbols in the source alphabet, which reduces steady state jitter of the CMA algorithm. Specifically, the received input signal to the CMA error calculation is shifted up or down by a computed delta (&Dgr;), in accordance with the predicted bit(s). In addition, a different constant gamma (&ggr;), for the CMA error calculation is selected in accordance with the predicted bit(s). The disclosed technique is applicable to trellis and non-trellis codes in which at least one bit of the present symbol can be predicted in advance and used to reduce the effective number of symbols in the source alphabet.

Equalizer method and apparatus using constant modulus algorithm blind equalization and partial decoding

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Jamison, PA, United States of America

Stephen L Biracree