Investigation into intermodulation distortion in HEMTs using a quasi-2-D physical model

The need for both linear and efficient pseudomorphic high electron-mobility transistors (pHEMTs) for modern wireless handsets necessitates a thorough understanding of the origins of intermodulation distortion at the device level. For the first time, the dynamic large-signal internal physical behavior of a pHEMT is examined using a quasi-two-dimensional physical device model. The model accounts fully for device-circuit interaction and is validated experimentally for a two-tone experiment around 5 GHz

Design and demonstration of digital pre-distortion using software defined radio

Abstract. High data rates for large number of users set tight requirements for signal quality measured in terms of error vector magnitude (EVM). In radio transmitters, nonlinear distortion dominated by power amplifiers (PAs) often limits the achievable EVM. However, the linearity can be improved by linearization techniques. Digital pre-distortion (DPD) is one of these widely used linearization techniques for an effective distortion reduction over a wide bandwidth. In DPD, the nonlinearity of the transmitter is pre-compensated in the digital domain to achieve linear output. Moreover, DPD is used to enable PAs to operate in the power-efficient region with a decent linearity. As we are moving towards millimetre-wave frequencies to enable the wideband communications, the design of the DPD algorithm must be optimized in terms of performance and power consumption. Moreover, continuous development of wireless infrastructure motivates to make research on programmable and reconfigurable platforms in order to decrease the demonstration cost and time, especially for the demonstration purposes. This thesis illustrates and presents how software defined radio (SDR) platforms can be used to demonstrate DPD. Universal software defined peripheral (USRP) X300 is a commercial software defined radio (SDR) platform. The chosen model, X300, has two independent channels equipped with individual transceiver cards. SIMULINK is used to communicate with the device and the two channels of X300 are used as transmitter and receiver simultaneously in full-duplex mode. Hence, a single USRP device is acting as an operational transmitter and feedback receiver, simultaneously. The implemented USRP design consists of SIMULINK based transceiver design and lookup table based DPD in which the coefficients are calculated in MATLAB offline. An external PA, i.e. ZFL-2000+ together with a directional coupler and attenuator are connected between the TX/RX port and RX2 port to measure the nonlinearity. The nonlinearity transceiver is measured with and without the external PA. The experimental results show decent performance for linearization by using the USRP platform. However, the results differ widely due to the used USRP transceiver parameterization and PA operational point. The 16 QAM test signal with 500 kHz bandwidth is fed to the USRP transmit chain. As an example, the DPD algorithm improves the EVM from 7.6% to 2.1% and also the ACPR is reduced around 10 dB with the 16 QAM input signal where approximately + 2.2 dBm input power applied to the external PA

Considering even-order terms in stochastic nonlinear system modeling with respect to broadband data communication

As a tradeoff between efficiency and costs modern communication systems contain a variety of components that can at least be considered weakly nonlinear. A critical element in evaluating the degree of nonlinearity of any underlying nonlinear system is the amount of undesired signal strength or signal power this system is introducing outside the transmission bandwidth. This phenomenon called spectral regrowth or spectral broadening is subject to stringent restrictions mainly imposed by the given specifications of the particular communication standard. Consequently, achieving the highest possible efficiency without exceeding the linearity requirements is one of the main tasks in system design. Starting from this challenging engineering problem there grows a certain need for specialized tools that are capable of predicting linearity and efficiency of the underlying design. Besides a multitude of methods aiming at the prediction of spectral regrowth a statistical approach in modeling and analyzing nonlinear systems offers the advantage of short processing times due to closed form mathematical expressions in terms of input and output power spectra and is therefore further examined throughout this article

Modeling nonlinear power amplifiers in OFDM systems from subsampled data: a comparative study using real measurements

A comparative study among several nonlinear high-power amplifier (HPA) models using real measurements is carried out. The analysis is focused on specific models for wideband OFDM signals, which are known to be very sensitive to nonlinear distortion. Moreover, unlike conventional techniques, which typically use a single-tone test signal and power measurements, in this study the models are fitted using subsampled time-domain data. The in-band and out-of-band (spectral regrowth) performances of the following models are evaluated and compared: Saleh’s model, envelope polynomial model (EPM), Volterra model, the multilayer perceptron (MLP) model, and the smoothed piecewise-linear (SPWL) model. The study shows that the SPWL model provides the best in-band characterization of the HPA. On the other hand, the Volterra model provides a good trade-off between model complexity (number of parameters) and performance

Experimental demonstration of digital predistortion for orthogonal frequency-division multiplexing-radio over fibre links near laser resonance

Radio over fibre (RoF), an enabling technology for distribution of wireless broadband service signals through analogue optical links, suffers from non-linear distortion. Digital predistortion has been demonstrated as an effective approach to overcome the RoF non-linearity. However, questions remain as to how the approach performs close to laser resonance, a region of significant dynamic non-linearity, and how resilient the approach is to changes in input signal and link operating conditions. In this work, the performance of a digital predistortion approach is studied for directly modulated orthogonal frequency-division multiplexing RoF links operating from 2.47 to 3.7 GHz. It extends previous works to higher frequencies, and to higher quadrature amplitude modulation (QAM) levels. In addition, the resilience of the predistortion approach to changes in modulation level of QAM schemes, and average power levels are investigated, and a novel predistortion training approach is proposed and demonstrated. Both memoryless and memory polynomial predistorter models, and a simple off-line least-squares-based identification method, are used, with excellent performance improvements demonstrated up to 3.0 GHz

Transformer NN-based behavioral modeling and predistortion for wideband pas

Abstract. This work investigates the suitability of transformer neural networks (NNs) for behavioral modeling and the predistortion of wideband power amplifiers. We propose an augmented real-valued time delay transformer NN (ARVTDTNN) model based on a transformer encoder that utilizes the multi-head attention mechanism. The inherent parallelized computation nature of transformers enables faster training and inference in the hardware implementation phase. Additionally, transformers have the potential to learn complex nonlinearities and long-term memory effects that will appear in future high-bandwidth power amplifiers. The experimental results based on 100 MHz LDMOS Doherty PA show that the ARVTDTNN model exhibits superior or comparable performance to the state-of-the-art models in terms of normalized mean square error (NMSE) and adjacent channel power ratio (ACPR). It improves the NMSE and ACPR up to −37.6 dB and −41.8 dB, respectively. Moreover, this approach can be considered as a generic framework to solve sequence-to-one regression problems with the transformer architecture