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In this article, we study closed-loop digital predistortion (DPD) systems and associated learning algorithms. Specifically, we propose various low-complexity approaches to estimate and manipulate the inverse of the input data covariance matrix (CM) and combine them with the so-called self-orthogonalized (SO) learning rule. The inherent simplicity of the SO algorithm, combined with the proposed solutions, allows for remarkably reduced complexity in the DPD system while maintaining similar linearization performance compared to other state-of-the-art methods. This is demonstrated with thorough over-the-air (OTA) mmW measurement results at 28 GHz, incorporating a state-of-the-art 64-element active antenna array, and very wide channel bandwidths up to 800 MHz. In addition, complexity analyses are carried out, which together with the measured linearization performance demonstrates favorable performance–complexity tradeoffs in linearizing mmW active array transmitters through the proposed solutions. The techniques can find application in systems where the power amplifier (PA) nonlinearities are time-varying and thus frequent or even constant updating of the DPD is required, good examples being mmW adaptive antenna arrays as well as terminal transmitters in 5G and beyond networks. [ABSTRACT FROM AUTHOR]

Piecewise behavioral models are commonly adopted for modeling and linearization of RF power amplifiers (PAs) that exhibit strong amplitude-dependent nonlinear distortion characteristics, as global polynomial approximations tend to underperform in such scenarios. In this article, we consider a new piecewise model for PAs based on the mixture of experts (ME) approach, which builds on a probabilistic model that allows the different submodels to cooperate—as opposed to operating in an independent fashion that is commonly the case in existing reference methods. We first introduce the ME framework theory while also extend it such that it can be applied to model complex baseband signals and nonlinearities. Then, we show how the ME model allows overcoming some of the intrinsic shortcomings that existing piecewise behavioral models commonly exhibit, which translates into improved modeling accuracy and improved linearization performance. Furthermore, the extension of the ME approach to a tree-structured regression model, referred to as the hierarchical ME model, is also introduced and shown to provide further performance improvements over the basic ME approach. The proposed solutions are validated with extensive RF measurements, covering both PA direct modeling and digital predistortion (DPD)-based linearization, on a gallium nitride (GaN) load-modulated balanced PA, on a GaN Doherty PA, and on a class AB GaN high electron mobility transistor PA, while being compared against several state-of-the-art piecewise methods. The results demonstrate that the ME framework-based models outperform the state of the art. [ABSTRACT FROM AUTHOR]

In this article, we study digital predistortion (DPD)-based linearization with a specific focus on millimeter-wave (mmW) active antenna arrays. Due to the very large-channel bandwidths and beam-dependence of nonlinear distortion in such systems, we present a closed-loop DPD learning architecture, lookup table (LUT)-based memory DPD models, and low-complexity sign-based estimation algorithms such that even continuous DPD learning could be technically feasible. To this end, three different learning algorithms—sign, signed regressor, and sign–sign—are formulated for the LUT-based DPD models such that the potential rank deficiencies, experienced in earlier methods, are avoided while facilitating greatly reduced learning complexity. The injection-based LUT DPD structure is also shown to allow for low numbers and reduced dynamic range of the involved LUT entries. Extensive RF measurements utilizing a state-of-the-art mmW active antenna array system at 28 GHz are carried out and reported to validate the methods, incorporating very wide channel bandwidths of 400 and 800 MHz while pushing the array close to saturation. In addition, the processing and learning complexities of the considered techniques are analyzed, which, together with the measured linearization performance figures, allows to assess the complexity–performance tradeoffs of the proposed solutions. Overall, the results show that efficient mmW array linearization can be obtained through the proposed methods at very low complexity. [ABSTRACT FROM AUTHOR]

This article presents a power amplifier (PA) design, which consists of eight class-D PA units on a single 28-nm CMOS die and a coupled-line power combiner on printed circuit board. The PA utilizes tri-phasing modulation, which combines polar and outphasing components in a way that eliminates linearity-degrading effects of multilevel outphasing while maintaining the back off efficiency.Each PA unit contains a cascoded output stage with a 3.6-V supply voltage, and multilevel operation is enabled by ON/OFF logic circuitry. Our analysis shows that the choice of power-combiner type is vital for reducing PA supply and ground ripple and thus ensuring reliable operation.Accordingly, the power combiner is implemented with extended Marchand baluns, which consist of input transmission lines and coupled-line sections. Unlike the original Marchand balun, our new topology is feasible for implementation under the layout restrictions caused by the multiple-unit PA on a single die.Measurement results show the PA achieving a peak output power of 29.7 dBm with a 34.7% efficiency, and operation with aggregated Long Term Evolution (LTE) signals at 1.7-GHz carrier frequency is verified with bandwidths up to 100 MHz. [ABSTRACT FROM AUTHOR]

This article studies the processing principles, implementation challenges, and performance of orthogonal frequency-division multiplexing (OFDM)-based radars, with particular focus on the fourth-generation Long-Term Evolution (LTE) and fifth-generation (5G) New Radio (NR) mobile networks’ base stations and their utilization for radar/sensing purposes. First, we address the problem stemming from the unused subcarriers within the LTE and NR transmit signal passbands and their impact on frequency-domain radar processing. In particular, we formulate and adopt a computationally efficient interpolation approach to mitigate the effects of such empty subcarriers in the radar processing. We evaluate the target detection and the corresponding range and velocity estimation performance through computer simulations and show that high-quality target detection as well as high-precision range and velocity estimation can be achieved. In particular, 5G NR waveforms, through their impressive channel bandwidths and configurable subcarrier spacing, are shown to provide very good radar/sensing performance. Then, a fundamental implementation challenge of transmitter–receiver (TX–RX) isolation in OFDM radars is addressed, with specific emphasis on shared-antenna cases, where the TX–RX isolation challenges are the largest. It is confirmed that from the OFDM radar processing perspective, limited TX–RX isolation is primarily a concern in the detection of static targets, while moving targets are inherently more robust to transmitter self-interference (SI). Properly tailored analog/RF and digital SI cancellation solutions for OFDM radars are also described and implemented and shown through RF measurements to be key technical ingredients for practical deployments, particularly from static and slowly moving targets’ point of view. [ABSTRACT FROM AUTHOR]

This paper proposes an active radio frequency (RF) cancellation solution to suppress the transmitter (TX) passband leakage signal in radio transceivers supporting simultaneous transmission and reception. The proposed technique is based on creating an opposite-phase baseband equivalent replica of the TX leakage signal in the transceiver digital front-end through adaptive nonlinear filtering of the known transmit data, to facilitate highly accurate cancellation under a nonlinear power amplifier (PA). The active RF cancellation is then accomplished by employing an auxiliary TX chain to generate the actual RF cancellation signal, and combining it with the received signal at the receiver (RX) low-noise amplifier (LNA) input. A closed-loop parameter learning approach, based on the decorrelation learning rule, is also developed to efficiently estimate the coefficients of the nonlinear cancellation filter in the presence of a nonlinear PA with memory, finite passive isolation, and a nonlinear LNA. The performance of the proposed cancellation technique is evaluated through comprehensive RF measurements adopting commercial LTE-Advanced transceiver hardware components. The results show that the proposed technique can provide an additional suppression of up to 54 dB for the TX passband leakage signal at the LNA input, even at very high transmit power levels and with wide transmission bandwidths. Such a novel cancellation solution can, therefore, substantially improve the TX–RX isolation, hence reducing the requirements on passive isolation and RF component linearity, as well as increasing the efficiency and flexibility of the RF spectrum use in the emerging 5G radio networks. [ABSTRACT FROM PUBLISHER]

In this paper, a novel decorrelation-based concurrent digital predistortion (DPD) solution is proposed for dual-band transmitters (TXs) employing a single wideband power amplifier (PA), and utilizing only a single feedback receiver path. The proposed decorrelation-based parameter learning solution is both flexible and simple, and operates in a closed-loop manner, opposed to the widely applied indirect learning architecture. The proposed decorrelation-based learning and DPD processing can also be effectively applied to more ordinary single carrier/band transmissions, as well as generalized to more than two transmit bands. Through a comprehensive analysis covering both the DPD parameter learning and the main path processing, it is shown that the complexity of the proposed concurrent DPD is substantially lower compared with the other state-of-the-art concurrent DPD methods. Extensive set of simulation and RF measurement results are also presented, using base-station PAs as well as a commercial LTE-Advanced mobile PA, to evaluate and validate the effectiveness of the proposed DPD solution in various real world scenarios, incorporating both single-band and dual-band TX cases. The simulation and RF measurement results demonstrate excellent linearization performance of the proposed concurrent DPD, even outperforming current state-of-the-art methods, despite the significantly lower complexity. [ABSTRACT FROM AUTHOR]

In this paper, we provide detailed modeling of the spurious intermodulation distortion products appearing in the own receiver (RX) operating band as a result of coexisting transmitter (TX) and RX nonlinearities with noncontiguous carrier aggregation transmissions. Furthermore, an efficient digital front-end signal processing technique is proposed, which can flexibly mitigate the resulting RX in-band self-interference caused either by individual or simultaneously coexisting TX and RX nonlinearities. The technique is based on accurately estimating the effective leakage channel that models the nonlinearities of the TX and RX chains and the duplexer filters characteristics. In the parameter estimation stage, an observation RX chain is adopted for separately estimating the TX passband leakage response, which facilitates efficient joint estimation and regeneration of the TX- and RX-induced self-interference. In the online digital cancellation, the actual transmit data are used in conjunction with the estimated channel responses to generate a replica of the overall nonlinear self-interference, which is subsequently suppressed by subtracting it from the actual observation. In general, the proposed technique can efficiently estimate and suppress the self-interference at arbitrary spurious sub-bands located at the RX band. The performance evaluations with comprehensive numerical simulations and practical RF measurements indicate highly accurate and efficient operation, with up to 28 dB of measured self-interference suppression. [ABSTRACT FROM PUBLISHER]

Noncontiguous transmission schemes combined with high power-efficiency requirements pose big challenges for radio transmitter and power amplifier (PA) design and implementation. Due to the nonlinear nature of the PA, severe unwanted emissions can occur, which can potentially interfere with neighboring channel signals or even desensitize the own receiver in frequency division duplexing transceivers. In this paper, to suppress such unwanted emissions, a low-complexity subband digital predistortion solution, specifically tailored for spectrally noncontiguous transmission schemes in low-cost devices, is proposed. The proposed technique aims at mitigating only the selected spurious intermodulation distortion components at the PA output, hence allowing for substantially reduced processing complexity compared with classical linearization solutions. Furthermore, novel decorrelation-based parameter learning solutions are also proposed and formulated, which offer reduced computing complexity in parameter estimation as well as the ability to track time-varying features adaptively. Comprehensive simulation and RF measurement results are provided, using a commercial LTE-Advanced mobile PA, to evaluate and validate the effectiveness of the proposed solution in real-world scenarios. The obtained results demonstrate that highly efficient spurious component suppression can be obtained using the proposed solutions. [ABSTRACT FROM PUBLISHER]

Carrier aggregation transmissions in frequency division duplexing devices reduce the duplexing distance between the transmitter (TX) and receiver (RX) bands. As a consequence, the spurious intermodulation distortion products created by the nonlinear RF front-end of the TX may easily extend over to the RX band, potentially causing own RX desensitization. In this paper, we propose an efficient and computationally feasible adaptive digital identification and cancellation technique to mitigate the RX desensitization. We first show that the spurious leakage signal at own RX band depends on an equivalent leakage channel that models the overall signal leakage path including the TX nonlinearities, duplexer filter responses, and RX path. The parameters of the equivalent leakage channel can be efficiently estimated with the least squares or the recursive least squares algorithm, using the actual digital transmit data as a reference, and then used to regenerate and cancel the leakage interference from the received signal. The performance of the proposed technique is evaluated with extensive computer simulations, as well as with practical real-world RF measurements, demonstrating excellent calibration properties with up to 19-dB improvement in singal-to-interference plus noise ratio of the desired received signal. [ABSTRACT FROM PUBLISHER]

In this paper, novel blind identification and compensation architectures for the frequency response mismatch of a two-channel time-interleaved analog-to-digital-converter (TI-ADC) are proposed. First, detailed modeling of the frequency response mismatch is carried out, establishing a direct connection and similarity to the well-known in-phase/quadrature mismatch problem. Stemming from this modeling, the proposed blind mismatch identification and compensation architectures are then developed building on complex statistical signal processing. Compared to the existing methods in the literature, the proposed solutions can identify and correct the frequency response mismatch in a fully blind manner for the full digital bandwidth (BW) of the ADC system, and are also applicable in sub-sampling TI-ADC devices and RF sampling. The efficiency of the proposed solutions is verified and demonstrated using comprehensive measurements of actual RF-sampling TI-ADC hardware with gigahertz-scale instantaneous BW. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel digital predistorter structure for joint mitigation of frequency-dependent power amplifier (PA) and in-phase and quadrature (I/Q) modulator impairments in direct-conversion radio transmitters. The predistorter is based on an extended parallel Hammerstein structure, yielding a predistorter that is fully linear in the parameters. In the parameter estimation stage, the indirect learning architecture is utilized. The proposed technique is the first technique in the literature to consider the joint estimation and mitigation of frequency-dependent PAand I/Q modulator impairments. Extensive simulation and measurement analysis is carried out to verify the operation and efficacy of the proposed predistortion structure. It is shown that the adjacent channel power ratio is increased by more than 20 dB in all experiments when using the proposed method, and that the performance of the reference techniques is clearly exceeded. [ABSTRACT FROM AUTHOR]

One of the main trends in the evolution of radio receivers and other wireless device is to implement more and more of the receiver functionalities using digital signal processing (DSP). However, due to practical limitations in the analog-to-digital conversion process, some analog signal processing stages are likely to remain also in the continuation. With the ever-increasing demands for the system performance and supported data rates on one side, and the terminal flexibility and implementation costs on the other, the requirements for these remaining analog front-end stages become extremely challenging to meet. Then, one interesting idea in this context is to apply sophisticated DSP-based techniques to compensate for some of the most fundamental nonidealities of the receiver analog front-ends. In this paper, we focus on developing and demonstrating novel digital techniques to mitigate the effects of harmonic and intermodulation distortion in wideband multicarrier or multichannel receivers using adaptive interference cancellation. The approach in general is practically oriented and largely based on analyzing and processing measured real-world receiver front-end signals. The obtained results indicate that the proposed compensation technique can be used to suppress nonlinear distortion due to receiver front-end sections under realistic signaling assumptions [ABSTRACT FROM PUBLISHER]