190 research outputs found

    Transformer NN-based behavioral modeling and predistortion for wideband pas

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    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

    Digital predistortion of RF amplifiers using baseband injection for mobile broadband communications

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    Radio frequency (RF) power amplifiers (PAs) represent the most challenging design parts of wireless transmitters. In order to be more energy efficient, PAs should operate in nonlinear region where they produce distortion that significantly degrades the quality of signal at transmitter’s output. With the aim of reducing this distortion and improve signal quality, digital predistortion (DPD) techniques are widely used. This work focuses on improving the performances of DPDs in modern, next-generation wireless transmitters. A new adaptive DPD based on an iterative injection approach is developed and experimentally verified using a 4G signal. The signal performances at transmitter output are notably improved, while the proposed DPD does not require large digital signal processing memory resources and computational complexity. Moreover, the injection-based DPD theory is extended to be applicable in concurrent dual-band wireless transmitters. A cross-modulation problem specific to concurrent dual-band transmitters is investigated in detail and novel DPD based on simultaneous injection of intermodulation and cross-modulation distortion products is proposed. In order to mitigate distortion compensation limit phenomena and memory effects in highly nonlinear RF PAs, this DPD is further extended and complete generalised DPD system for concurrent dual-band transmitters is developed. It is clearly proved in experiments that the proposed predistorter remarkably improves the in-band and out-of-band performances of both signals. Furthermore, it does not depend on frequency separation between frequency bands and has significantly lower complexity in comparison with previously reported concurrent dual-band DPDs

    Joint compensation of I/Q impairments and PA nonlinearity in mobile broadband wireless transmitters

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    The main focus of this thesis is to develop and investigate a new possible solution for compensation of in-phase/quadrature-phase (I/Q) impairments and power amplifier (PA) nonlinearity in wireless transmitters using accurate, low complexity digital predistortion (DPD) technique. After analysing the distortion created by I/Q modulators and PAs together with nonlinear crosstalk effects in multi-branch multiple input multiple output (MIMO) wireless transmitters, a novel two-box model is proposed for eliminating those effects. The model is realised by implementing two phases which provide an optimisation of the identification of any system. Another improvement is the capability of higher performance of the system without increasing the computational complexity. Compared with conventional and recently proposed models, the approach developed in this thesis shows promising results in the linearisation of wireless transmitters. Furthermore, the two-box model is extended for concurrent dual-band wireless transmitters and it takes into account cross-modulation (CM) products. Besides, it uses independent processing blocks for both frequency bands and reduces the sampling rate requirements of converters (digital-to-analogue and analogue-to-digital). By using two phases for the implementation, the model enables a scaling down of the nonlinear order and the memory depth of the applied mathematical functions. This leads to a reduced computational complexity in comparison with recently developed models. The thesis provides experimental verification of the two-box model for multi-branch MIMO and concurrent dual-band wireless transmitters. Accordingly, the results ensure both the compensation of distortion and the performance evaluation of modern broadband wireless transmitters in terms of accuracy and complexity

    Linearizing Radio Frequency Power Amplifiers Using an Analog Predistortion Technique

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    As critical elements of the physical infrastructure that enables ubiquitous wireless connectivity, radio frequency power amplifiers (RFPAs) are constantly pushed to the limits of linear but efficient operation. Digital predistortion, as a means of circumventing the limitations of this inherent linearity – efficiency trade-off, has been a subject of prolific research for well over a decade. However, to support the unrestrained growth of broadband mobile traffic, wireless networks are expected to rely increasingly on heterogeneously-sized small cells which necessitate new predistortion solutions operating at a fraction of the power consumed by digital predistortion approaches. This thesis pertains to an emerging area of research involving analog predistortion (APD) – a promising, low-power alternative to digital predistortion (DPD) for future wireless networks. Specifically, it proposes a mathematical function that can be used by the predistorter to linearize RFPAs. As a preliminary step, the challenges of transitioning from DPD to APD are identified and used to formulate the constraints that APD imposes on the predistorter function. Following an assessment of the mathematical functions commonly used for DPD, and an analysis of the physical mechanisms of RFPA distortion, a new candidate function is proposed. This function is both compatible with and feasible for an APD implementation, and offers competitive performance against more complex predistorter functions (that can only be implemented in DPD). The proposed predistorter function and its associated coefficient identification procedure are experimentally validated by using them to linearize an RFPA stimulated with single-band carrier aggregated signals of progressively wider bandwidths. The solution is then extended to the case of dual-band transmission, and subsequently validated on an RFPA as well. The proposed function is a cascade of a finite impulse response filter and an envelope memory polynomial and has the potential to deliver far better linearization results than what has been demonstrated to date in the APD literature

    Digital Front-End Signal Processing with Widely-Linear Signal Models in Radio Devices

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    Necessitated by the demand for ever higher data rates, modern communications waveforms have increasingly wider bandwidths and higher signal dynamics. Furthermore, radio devices are expected to transmit and receive a growing number of different waveforms from cellular networks, wireless local area networks, wireless personal area networks, positioning and navigation systems, as well as broadcast systems. On the other hand, commercial wireless devices are expected to be cheap, be relatively small in size, and have a long battery life. The demands for flexibility and higher data rates on one hand, and the constraints on production cost, device size, and energy efficiency on the other, pose difficult challenges on the design and implementation of future radio transceivers. Under these diametric constraints, in order to keep the overall implementation cost and size feasible, the use of simplified radio architectures and relatively low-cost radio electronics are necessary. This notion is even more relevant for multiple antenna systems, where each antenna has a dedicated radio front-end. The combination of simplified radio front-ends and low-cost electronics implies that various nonidealities in the remaining analog radio frequency (RF) modules, stemming from unavoidable physical limitations and material variations of the used electronics, are expected to play a critical role in these devices. Instead of tightening the specifications and tolerances of the analog circuits themselves, a more cost-effective solution in many cases is to compensate for these nonidealities in the digital domain. This line of research has been gaining increasing interest in the last 10-15 years, and is also the main topic area of this work. The direct-conversion radio principle is the current and future choice for building low-cost but flexible, multi-standard radio transmitters and receivers. The direct-conversion radio, while simple in structure and integrable on a single chip, suffers from several performance degrading circuit impairments, which have historically prevented its use in wideband, high-rate, and multi-user systems. In the last 15 years, with advances in integrated circuit technologies and digital signal processing, the direct-conversion principle has started gaining popularity. Still, however, much work is needed to fully realize the potential of the direct-conversion principle. This thesis deals with the analysis and digital mitigation of the implementation nonidealities of direct-conversion transmitters and receivers. The contributions can be divided into three parts. First, techniques are proposed for the joint estimation and predistortion of in-phase/quadrature-phase (I/Q) imbalance, power amplifier (PA) nonlinearity, and local oscillator (LO) leakage in wideband direct-conversion transmitters. Second, methods are developed for estimation and compensation of I/Q imbalance in wideband direct-conversion receivers, based on second-order statistics of the received communication waveforms. Third, these second-order statistics are analyzed for second-order stationary and cyclostationary signals under several other system impairments related to circuit implementation and the radio channel. This analysis brings new insights on I/Q imbalances and their compensation using the proposed algorithms. The proposed algorithms utilize complex-valued signal processing throughout, and naturally assume a widely-linear form, where both the signal and its complex-conjugate are filtered and then summed. The compensation processing is situated in the digital front-end of the transceiver, as the last step before digital-to-analog conversion in transmitters, or in receivers, as the first step after analog-to-digital conversion. The compensation techniques proposed herein have several common, unique, attributes: they are designed for the compensation of frequency-dependent impairments, which is seen critical for future wideband systems; they require no dedicated training data for learning; the estimators are computationally efficient, relying on simple signal models, gradient-like learning rules, and solving sets of linear equations; they can be applied in any transceiver type that utilizes the direct-conversion principle, whether single-user or multi-user, or single-carrier or multi-carrier; they are modulation, waveform, and standard independent; they can also be applied in multi-antenna transceivers to each antenna subsystem separately. Therefore, the proposed techniques provide practical and effective solutions to real-life circuit implementation problems of modern communications transceivers. Altogether, considering the algorithm developments with the extensive experimental results performed to verify their functionality, this thesis builds strong confidence that low-complexity digital compensation of analog circuit impairments is indeed applicable and efficient
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