Bernhard Sogl

Advanced transmitters with combined crest factor reduction and digital predistortion techniques

This paper analyses the benefits of combining crest factor reduction (CFR) technique and digital predistortion (DPD). DPD and CFR have been mainly investigated separately, and this is the contribution to the state of the art given here. The combination is attractive in modern wireless transmission systems due to the high peak-to-average-power-ratio (PAPR) of the signals employed. In these cases, the compression of the signal peaks performed by the amplifier in strong saturation region causes uncontrolled in-band and out-of-band distortion that degrades ACLR and EVM of the output signal. The joint architecture can take advantage from the improved linear output power given by DPD together with a controlled reduction of the peaks performed by CFR. The PA can in this way deliver a higher linear output power having at the same time a predictable linearity of the output RF signal. The concept has been implemented and tested on a commercial GaAs PA, obtaining an increased linear output power of 1.9 dB compared to the standalone PA when a WCDMA signal with PAPR of 3.47 dB is employed.

A Memoryless Semi-Physical Power Amplifier Behavioral Model Based on the Correlation Between AM–AM and AM–PM Distortions

A new semi-physical memoryless computationally effective behavioral model (BM) capable of predicting amplitude-modulation-to-amplitude-modulation (AM-AM) and amplitude-modulation-to-phase-modulation (AM-PM) distortions is proposed. In recent years, AM-AM and AM-PM distortions have been separately studied in literature. Here, we investigate the correlation between AM-AM and AM-PM distortions first. Based on the observed correlation, a novel AM-PM model is derived from the well-known Rapp AM-AM model. On the basis of the close relationship between the AM-AM and AM-PM model, a highly accurate and computationally effective large-signal BM is obtained. The newly developed model addresses the current needs of the mobile industry that requires BMs of the power amplifier (PA), which can be interpreted by the designers. In addition, the models must be computationally effective due to the limited computation power in mobile handset. Therefore, only memoryless BMs can be taken into account and larger errors are accepted for the sake of computational effectiveness. In this paper, it is shown that the newly introduced model achieves excellent results, when it is applied to actual industrial applications of two GaAs-based class-AB PAs in 65-nm technology and one CMOS-based class AB PA in 28-nm technology, which are designed for mobile communications.

An extension of power amplifier behavioral models for optimizing battery current at system level

One of the most significant figures of merit concerning a power amplifier is its efficiency. However, the behavioral models of power amplifiers are mainly focused on the functional aspects, but not on current consumption. Therefore, simulations with respect to the efficiency of a power amplifier cannot be accomplished at the system level. To close the gap of simulation capabilities, this article proposes a time efficient and accurate extension of behavioral models to predict current consumption. For a commercial handset power amplifier, an average error of 1.9% between the fast high-level model and the measurement results is obtained.

A novel, fast, and precise method to perform time alignment estimation and compensation

In this paper, a novel procedure to estimate and compensate the delay between power amplifiers input and output waveforms is described. The proposed method has been developed in order to achieve fast computation and simple implementation that are required in state of the art mobile applications. In addition, the modular approach adopted offers high flexibility and enables further future improvements. Comparison with a traditional method like cross-correlation shows up to four times faster estimation time with the same precision. Resolution is furthermore improved estimating the fractional delay mismatch to increase the precision of the results with reduced sampling rate of the signals.

A semi-physical power amplifier behavioral model capable of predicting gain expansion effects

A novel semi-physical power amplifier (PA) behavioral model (BM) that describes the input-output characteristic of PAs exhibiting gain expansion (GE) is introduced. The accurate prediction of GE is of particular importance because GE typically improves the power added efficiency (PAE) at high input powers. Though, GE impacts the spectral regrowth. Therefore, BMs that are capable of predicting GE, like the one introduced in this work, are highly desirable. In a case study, the proposed model is employed to predict the AM-AM distortions of a GaAs class AB PA designed for LTE applications. Excellent agreement between measurement and simulation results is obtained. The computational efficient model allows system-level simulations of advanced transmitter systems in order to optimize their modes of operation.