Adaptive digital predistortion for wideband high crest factor applications based on the WACP optimization objective

Modern digital communication systems utilize OFDM and DS-CDMA signals because of their superior spectral efficiency and multiple access properties respectively. Examples of such systems include digital television (DVB-T), digital radio (DAB) and 3ʳᵈ Generation mobile (WCDMA). A downside to using these signals however is the need to accommodate their very high Crest Factor, also known as Peak-to-Average Power Ratio, during transmission. Compared to other communication signals transmitted with the same average power, these signals generate greater transmitter distortion since their larger signal peaks drive the transmitter power amplifier into regions of greater nonlinearity. Reducing this Crest Factor related distortion, whilst concurrently maintaining power amplifier efficiency, requires the power amplifier's transfer characteristic to be externally linearized. For OFDM and DS-CDMA signals, digital predistortion is the favored linearization technique given its cost effectiveness, superior signal processing capability, potential to adapt and ability to linearize the entire transmitter. In this research thesis, a new digital predistortion technique is proposed. By employing frequency-domain information feedback, rather than traditional time-domain signal feedback, the new technique avoids bandwidth limitations in the feedback path and is hence more suited to wideband applications than current generation techniques. This frequency-domain information feedback is based on the novel Weighted Adjacent Channel Power (WACP) linearization objective. By incorporating frequency dependent weighting into the standard accumulation of Adjacent Channel Power (ACP), this novel linearization objective is able to discriminate between spectral distortion components and hence control the location of spectral distortion reduction. This makes linearization more robust in the presence of residual predistortion filtering inaccuracies. To accommodate the power amplifier memory effects associated with wideband signal modulation, the new technique uses a predistortion filter architecture based on the classic nonlinear dynamic Volterra Series. Mindful of Volterra kernel efficiency, the technique further applies a novel hybridized triple-stage pruning strategy, leaving the kernel size not only linear with respect to memory, but also independent of hardware sampling rate implementation. This pruning activity ultimately reduces the number of dynamic filter parameters needing to be estimated. This new digital predistortion technique utilizes generic mathematical optimization to estimate the resulting predistortion filter kernel, with frequency-domain WACP interpreted as the linearizing optimization objective. In line with theory, the objective is assumed to be nonconvex and hence both global and local optimization algorithms are employed to achieve true global convergence. This is in direct contrast to the traditional and competing Direct Learning technique which is more focused on quick local convergence, and less focused on guaranteeing maximum linearization performance corresponding to the objective global minimum. Since predistortion filter kernel estimation is performed using the transmitted wideband signal, the new technique is ultimately on-air adaptive. This means any transmitter using the technique will be both on-air and optimally linearized for its entire operational life