R. Neil Braithwaite

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This paper shows that digital predistortion (DPD) used to linearize an RF power amplifier (PA) can achieve wide bandwidth distortion cancellation using measurements obtained from a narrow bandwidth observation path. The DPD module creates a correction signal using a set of nonlinear basis waveforms, weighted by adjustable coefficients. The coefficients are(More)
This paper investigates the effects of Walsh code selection and baseband filtering on the statistical moments of the bandlimited forward-link CDMA signal. A normalized moment, the “power variance”, is proposed as a measure of the signal’s sensitivity to nonlinear amplification. The estimation of the power variance for the case of a bandlimited(More)
Strategies for reducing the number of basis waveforms used in a Volterra series model for digital predistortion (DPD) of RF power amplifiers (PAs) are proposed. Simple DPD models are generalized so that elemental terms within the Volterra series are grouped together or pruned. It is shown that grouping and pruning produce similar ACLR results when the(More)
This paper presents a new representation called “hierarchical G a b o r f i l ters” and associated novel local measures which are used t o detect potent ial objects of interest in images. The “first stage” of the approach uses a wavelet set of wide-bandwidth separable Gabor f i l ters t o extract local measures f r o m an image. The “second stage makes(More)
This paper describes algorithms used to improve linearity, efficiency, and peak power of a Doherty amplifier whose auxiliary transistor gate voltage is adjusted digitally as a function of the signal envelope. Two predistortion stages are used to compensate for high-order memoryless nonlinearities and low-order memory effects. The digital gate voltage(More)
A combined approach to digital predistortion (DPD) and crest factor reduction (CFR) is proposed. The new CFR is structured similar to DPD and is implemented by introducing a steady-state offset into the DPD coefficients. The DPD and CFR coefficients are estimated using separate adaptive processes but applied to the transmission path in a common module. The(More)
J.G. Daugman's (1988) neural network solution to the Gabor expansion of an image is reformulated as a steepest descent implementation. Nonlinear optimization theory is then applied to select an appropriate convergence factor. Two quasi-Newton-based nonlinear optimization techniques are applied to improve the convergence for certain types of lattice.