Abstract: Techniques for correcting component mismatches in an M-channel time-interleaved Analog to Digital Converter (ADC). In order to obtain an error measure for offset, gain or phase, errors, outputs from each ADC are either summed or averaged over No samples. Calling each of the sums or averages as Xk where k=1, 2, . . . , M, there are M such values as a result. A single value representing the mean of these M values, Xmean, is chosen as a reference value. The offset, gain and phase errors for the M different ADCs are then obtained from Xk?Xmean. The sign of each offset error, i.e., sign (Xk?Xmean), is then used to drive an adaptive algorithm whose output represents an offset correction value for the corresponding ADC. The offset, gain, and phase correction outputs from the adaptive algorithm is fed to an array of Digital-to-Analog converters (DACs) whose outputs are voltages or currents that directly or indirectly controls the offset, gain or phase setting of each individual ADC.

Abstract: A two-channel time-interleaved analog-to-digital converter (TIADC) system that provides for estimation and correction of offset, gain, and sample-time errors. Error in the offsets of the two ADCs that form the TIADC produces a spurious signal at the Nyquist frequency that can be used to minimize the difference of offsets of the ADCs. The difference in gain between the two ADCs produces spurious signals reflected around the Nyquist frequency whose magnitudes can be reduced by minimizing the difference in signal power between the two ADCs. An Automatic Gain Control loop corrects the scaling of the input signal due to the average of the gains of the ADCs. Phase error produces spurious signals reflected around the Nyquist frequency that are ?/2 out of phase with those due to the gain error. Minimizing the difference between the correlation of consecutive signals from the ADCs reduces the magnitude of these image tones.

Abstract: Techniques for correcting component mismatches in an M-channel time-interleaved Analog to Digital Converter (ADC). In order to obtain an error measure for offset, gain or phase, errors, outputs from each ADC are either summed or averaged over No samples. Calling each of the sums or averages as Xk where k=1, 2, . . . , M, there are M such values as a result. A single value representing the mean of these M values, Xmean, is chosen as a reference value. The offset, gain and phase errors for the M different ADCs are then obtained from Xk?Xmean. The sign of each offset error, i.e., sign(Xk?Xmean), is then used to drive an adaptive algorithm whose output represents an offset correction value for the corresponding ADC. The offset, gain, and phase correction outputs from the adaptive algorithm is fed to an array of Digital-to-Analog converters (DACs) whose outputs are voltages or currents that directly or indirectly controls the offset, gain or phase setting of each individual ADC.

Abstract: A two-channel time-interleaved analog-to-digital converter (TIADC) system that provides for estimation and correction of offset, gain, and sample-time errors. Error in the offsets of the two ADCs that form the TIADC produces a spurious signal at the Nyquist frequency that can be used to minimize the difference of offsets of the ADCs. The difference in gain between the two ADCs produces spurious signals reflected around the Nyquist frequency whose magnitudes can be reduced by minimizing the difference in signal power between the two ADCs. An Automatic Gain Control loop corrects the scaling of the input signal due to the average of the gains of the ADCs. Phase error produces spurious signals reflected around the Nyquist frequency that are ?/2 out of phase with those due to the gain error. Minimizing the difference between the correlation of consecutive signals from the ADCs reduces the magnitude of these image tones.

Abstract: A packet detection technique is disclosed in which an average correlation signal is generated representative of the match between a repetitive sequence of symbols; an average power signal is generated representative of the average power in the sequence of symbols; a scaled magnitude of the average correlation signal scaled by a first predetermined scale factor is produced; and one of the average power signal and scaled magnitude of the average correlation signal are multiplied by the second scale factor and compared to determine whether there is a match between a repetitive sequence of symbols.