Adaptive signal processing
High Linearity RF Amplifier Design
High Linearity RF Amplifier Design
Modified clipped LMS algorithm
EURASIP Journal on Applied Signal Processing
Step size bound of the sequential partial update LMS algorithm with periodic input signals
EURASIP Journal on Audio, Speech, and Music Processing
Design of an adaptive predistorter for solid state power amplifier in wireless OFDM systems
Research Letters in Signal Processing
Complexity reduction of the NLMS algorithm via selectivecoefficient update
IEEE Transactions on Signal Processing
A new Volterra predistorter based on the indirect learningarchitecture
IEEE Transactions on Signal Processing
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Digital predistortion is an effective means to compensate for the nonlinear effects of a memoryless system. In case of a cellular transmitter, a digital baseband predistorter can mitigate the undesirable nonlinear effects along the signal chain, particularly the nonlinear impairments in the radiofrequency (RF) amplifiers. To be practically feasible, the implementation complexity of the predistorter must be minimized so that it becomes a cost-effective solution for the resource-limited wireless handset. This paper proposes optimizations that facilitate the design of a low-cost high-performance adaptive digital baseband predistorter for memoryless systems. A comparative performance analysis of the amplitude and power lookup table (LUT) indexing schemes is presented. An optimized low-complexity amplitude approximation and its hardware synthesis results are also studied. An efficient LUT predistorter training algorithm that combines the fast convergence speed of the normalized leastmean squares (NLMSs) with a small hardware footprint is proposed. Results of fixed-point simulations based on the measured nonlinear characteristics of an RF amplifier are presented.