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In this letter, air-induced passive intermodulation (PIM) modeling and cancellation schemes are presented in a multiple-input multiple-output (MIMO) frequency-division duplexing (FDD) transceiver context. PIM is distortion generated by nonlinear passive devices either within the transmitter chain or outside the transceiver system, as is the case in air-induced PIM. In FDD systems, the PIM products may lie on the receiver band, thus possibly desensitizing the receiver chain. Unlike previous PIM cancellation works, we consider a challenging rank-2 dual-carrier MIMO transceiver scenario, with two spatially multiplexed signals per component carrier (CC). Stemming from the PIM modeling, we first present a cancellation method based on a complete set of identified basis functions (BFs). Additionally, to relax the processing complexity, we propose an alternative canceller solution with a reduced number of BFs, inspired by the problem modeling. RF measurements conducted with real-life equipment indicate favorable PIM suppression levels of up to 20 dB using both introduced techniques. [ABSTRACT FROM AUTHOR]

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]

Eutrophication and rising water temperature in freshwaters may increase the total production of a lake while simultaneously reducing the nutritional quality of food web components. We evaluated how cyanobacteria blooms, driven by agricultural eutrophication (in eutrophic Lake Köyliöjärvi) or global warming (in mesotrophic Lake Pyhäjärvi), influence the biomass and structure of phytoplankton, zooplankton, and fish communities. In terms of the nutritional value of food web components, we evaluated changes in the ω‐3 and ω‐6 polyunsaturated fatty acids (PUFA) of phytoplankton and consumers at different trophic levels. Meanwhile, the lakes did not differ in their biomasses of phytoplankton, zooplankton, and fish communities, lake trophic status greatly influenced the community structures. The eutrophic lake, with agricultural eutrophication, had cyanobacteria bloom throughout the summer months whereas cyanobacteria were abundant only occasionally in the mesotrophic lake, mainly in early summer. Phytoplankton community differences at genus level resulted in higher arachidonic acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) content of seston in the mesotrophic than in the eutrophic lake. This was also reflected in the EPA and DHA content of herbivorous zooplankton (Daphnia and Bosmina) despite more efficient trophic retention of these biomolecules in a eutrophic lake than in the mesotrophic lake zooplankton. Planktivorous juvenile fish (perch and roach) in a eutrophic lake overcame the lower availability of DHA in their prey by more efficient trophic retention and biosynthesis from the precursors. However, the most efficient trophic retention of DHA was found with benthivorous perch which prey contained only a low amount of DHA. Long‐term cyanobacterial blooming decreased the nutritional quality of piscivorous perch; however, the difference was much less than previously anticipated. Our result shows that long‐term cyanobacteria blooming impacts the structure of plankton and fish communities and lowers the nutritional quality of seston and zooplankton, which, however, is mitigated at upper trophic levels. [ABSTRACT FROM AUTHOR]

Communication receivers that utilize I/Q downconversion are troubled by amplitude and phase mismatches between the analog I and Q branches. These mismatches are unavoidable in practice and reduce the obtainable image frequency attenuation to the 20--40-dB range in practical receivers. In wideband multichannel receivers, where the overall bandwidths are in the range of several megahertz and the incoming carriers Iocated at each other's mirror frequencies have a high dynamic range, the image attenuation of the analog front-end (FE) alone is clearly insufficient. In this paper, two novel blind low-complexity I/Q imbalance compensation techniques are proposed and analyzed to digitally enhance the analog FE image attenuation in wideband direct0-conversion receivers. The proposed algorithms are grounded on the concept of circular or proper complex random signals, and they are, by design, able to handle the often overlooked yet increasingly important case of frequency-dependent I/Q mismatches. The first technique is an iterative one, stemming from adaptive filtering principles, whereas the second one is a moment-estimation-based block method. The performance of the algorithms is evaluated through computer simulations, as well as real-world laboratory signal measurement examples in practical multicarrier receiver cases. Based on the obtained results, the proposed compensation techniques can provide very good compensation performance with low computational resources and are robust in the face of different imbalance levels and dynamics of the received signals, as well as many other crucial practical aspects such as the effects of the communications channel and carrier synchronization. Index Terms--Adaptive filtering, circular random signals, digital radios, direct-conversion transceivers, I/Q imbalance, mirror-frequency interference, second-order statistics.

The current trend in building low-cost yet flexible radio transceivers is to use the so-called direct-conversion principle, which is based on complex (I/Q) up- and downconversions. Such transceivers are, however, sensitive to mismatches between the I and Q branches. These mismatches are unavoidable in any practical implementation, and result in finite attenuation of the mirror frequencies. In addition to the mirror-frequency interference problem, I/Q mismatches can severely compromise the performance of power amplifier linearization techniques based on pre-distortion. The effects of these impairments are becoming more pronounced as higher order modulated waveforms and/or more wideband multichannel signals are used. This brief focuses on digital-signal-processor-based I/Q mismatch calibration in wideband direct-conversion transmitters, assuming the challenging case of frequency-dependent I/Q mismatch. First, a novel widely linear (WL) calibration structure is introduced, suitable for frequency-dependent calibration. Then, two alternative principles for calibration parameter estimation are proposed. The first estimation approach stems from second-order statistics of complex communication signals, while the second technique is based on WL least-squares model fitting. Both estimators are shown by simulations to yield very good calibration performance. The obtainable performance is further assessed using laboratory RF signal measurements. Index Terms--Complex signals and systems, digital radios, direct-conversion transceivers, I/Q imbalance, mirror-frequency interference, digital calibration.

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. Index Terms--Adaptive filters, communication system nonlinearities, digital radios, harmonic and intermodulation distortion, radio receivers.

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-band full-duplex (IBFD) technology is a promising solution to boost the throughput of wireless networks. To bring IBFD to reality, the modem has to cancel the self-interference (SI) signal, which includes the strong direct Tx leakage signal and the weaker reflected Tx signal from the surroundings. Adaptive analog and digital SI cancelation schemes have been proposed. It becomes then interesting to understand, although, how the echoed SI could be exploited for enabling radar functionality while reusing the waveform and the already-existing hardware. This article formulates the monostatic radar system model starting from the communication system model. Beside simulation-based assessment, the performance is also evaluated by an IBFD system prototype, which consists of both analog and digital SI canceller modules, enabling > 85 dB Tx–Rx isolation. The system is enhanced with Doppler radar functionality, reusing as much as possible the existing IBFD functional blocks. The experimental result shows the accuracy of the proposed system to measure the velocity of mobile objects at various speeds between 0.2 and 1 m/s while the device is simultaneously served as a node to perform in-band bidirectional communication. This ability suits the proposed system for a broad spectrum of opportunistic remote sensing applications, such as body and hand gesture detection. [ABSTRACT FROM AUTHOR]

In this paper, we present a class of cascaded nonlinear models for complex-valued system identification, aimed at baseband modeling of nonlinear radio systems. The proposed models consist of serially connected elementary linear and nonlinear blocks, with the nonlinear blocks implemented as uniform spline-interpolated look-up tables (LUT) and the linear blocks as FIR filters. Wiener, Hammerstein, and Wiener-Hammerstein models are built, and simple but efficient gradient based adaptive learning rules are derived for all the models. This approach leads to remarkably simple solutions in terms of computational complexity, making the techniques suitable for real-time implementation. The proposed methods are then applied to full-duplex self-interference cancellation and digital predistortion in various real-life scenarios. First, evaluations with measured data from an in-band full-duplex prototype working at 2.4 GHz ISM band show that the algorithms are capable of obtaining similar cancellation performance as existing state-of-the-art solutions, regardless of the clearly reduced complexity. Second, a mmW active antenna array working at 28 GHz center frequency is digitally predistorted with the proposed solutions. The unwanted emissions and nonlinear distortion are suppressed to similar levels as with other state-of-the art solutions, and the corresponding linearity specifications are fulfilled in all cases, while the processing complexity is again drastically reduced. [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]

In this letter, we propose an efficient solution to linearize mmWave active antenna array transmitters that suffer from beam-dependent load modulation. We consider a dense neural network that is capable of modeling the correlation between the nonlinear distortion characteristics among different beams. This allows providing consistently good linearization regardless of the beamforming direction, thus avoiding the necessity of executing continuous digital predistortion parameter learning. The proposed solution is validated, conforming to 5G new radio transmit signal quality requirements, with extensive over-the-air RF measurements utilizing a state-of-the-art 64-element active antenna array operating at 28-GHz carrier frequency. [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]

Conventional delay-based digital phase modulators use a zero-order hold (ZOH) phase control word to modulate the square-wave RF carrier. Recently, new architectures capable of performing first-order hold (FOH) digital phase modulation have been proposed, thus improving the wideband performance to a level suitable for 5G base stations. While currently available literature focuses on the generic operation principle, this brief details the first on-chip implementation of the DSP engine required for actual FOH computations. The circuit is based on a simple iterative algorithm, which can be pipelined for high-speed operation. The DSP engine has been integrated as part of a prototype 5G base-station outphasing transmitter, fabricated in 28-nm CMOS. When processing a 100-MHz orthogonal frequency-division multiplexing signal, the DSP achieves an adjacent-channel leakage ratio of −53 dBc, which is 12 dB better than with conventional ZOH phase modulation. Furthermore, the system enables flexible upconversion to any frequency between 0.35 and 2.1 GHz from a fixed 1.5-GHz reference clock. The power consumption of a single engine is lower than 18 mW. [ABSTRACT FROM AUTHOR]

This paper investigates digital predistortion (DPD) linearization of hybrid beamforming large-scale antenna transmitters. We propose a novel DPD processing and learning technique for an antenna subarray, which utilizes a combined signal of the individual power amplifier (PA) outputs in conjunction with a decorrelation-based learning rule. In effect, the proposed approach results in minimizing the nonlinear distortions in the direction of the intended receiver. This feature is highly desirable, since emissions in other directions are naturally weak due to beamforming. The proposed parameter learning technique requires only a single observation receiver, and therefore supports simple hardware implementation. It is also shown to clearly outperform the current state-of-the-art technique that utilizes only a single PA for learning. Analysis of the feedback network amplitude and phase imbalances reveals that the technique is robust even to high levels of such imbalances. Finally, we also show that the array system out-of-band emissions are well-behaving in all spatial directions, and essentially below those of the corresponding single-antenna transmitter, due to the combined effects of the DPD and beamforming. [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]

In wireless communication systems, high-power transmitters suffer from nonlinearities due to power amplifier (PA) characteristics, I/Q imbalance, and local oscillator (LO) leakage. Digital Predistortion (DPD) is an effective technique to counteract these impairments. To help maximize agility in cognitive radio systems, it is important to investigate dynamically reconfigurable DPD systems that are adaptive to changes in the employed modulation schemes and operational constraints. To help maximize effectiveness, such reconfiguration should be performed based on multidimensional operational criteria. With this motivation, we develop in this paper a novel evolutionary algorithm framework for multiobjective optimization of DPD systems. We demonstrate our framework by applying it to develop an adaptive DPD architecture, called the adaptive, dataflow-based DPD architecture (ADDA), where Pareto-optimized DPD parameters are derived subject to multidimensional constraints to support efficient predistortion across timevarying operational requirements and modulation schemes. Through extensive simulation results, we demonstrate the effectiveness of our proposed multiobjective optimization framework in deriving efficient DPD configurations for runtime adaptation. [ABSTRACT FROM AUTHOR]

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]

In this article, we address the challenges of transmitter-receiver isolation in mobile full-duplex devices, building on shared-antenna-based transceiver architecture. First, self-adaptive analog RF cancellation circuitry is required, since the ability to track time-varying self-interference coupling characteristics is of utmost importance in mobile devices. In addition, novel adaptive nonlinear DSP methods are also required for final self-interference suppression at digital baseband, since mobile-scale devices typically operate under highly nonlinear low-cost RF components. In addition to describing the above kind of advanced circuit and signal processing solutions, comprehensive RF measurement results from a complete demonstrator implementation are also provided, evidencing beyond 40 dB of active RF cancellation over an 80 MHz waveform bandwidth with a highly nonlinear transmitter power amplifier. Measured examples also demonstrate the good self-healing characteristics of the developed control loop against fast changes in the coupling channel. Furthermore, when complemented by nonlinear digital cancellation processing, the residual self-interference level is pushed down to the noise floor of the demonstration system, despite the harsh nonlinear nature of the self-interference. These findings indicate that deploying the full-duplex principle can indeed also be feasible in mobile devices, and thus be one potential technology in, for example, 5G and beyond radio systems. [ABSTRACT FROM PUBLISHER]

Spectrally non-contiguous transmissions pose serious transceiver design challenges due to the nonlinear PA. When two or more non-contiguous carriers with close proximity are amplified by the same PA, spurious emissions inside or in the vicinity of the transmitter RF band are created. These spurious emissions may violate emission limits or otherwise compromise network coverage and reliability. Lowering the transmit power is a straightforward remedy, but it will reduce throughput, coverage, and power efficiency of the device. To improve linearity without sacrificing performance, several DPD techniques have recently been proposed to target the spurious emissions explicitly. These techniques are designed to minimize the computational and hardware complexity of DPD, thus making them better suited for mobile terminals and other lowcost devices. In this article, these recent advances in DPD for non-contiguous transmission scenarios are discussed, with a focus on mitigating the spurious emissions in the concrete example case of non-contiguous dual-carrier transmission. The techniques are compared to more traditional DPD approaches in terms of their computational and hardware complexities, as well as linearization performance. [ABSTRACT FROM AUTHOR]

Single-carrier frequency-division multiple access (SC-FDMA), which is a modified form of orthogonal frequency-division multiple access (OFDMA), has been adopted as the uplink physical-layer radio access technique for the Third-Generation Partnership Project Long-Term Evolution (3GPP-LTE) and LTE-Advanced. Radio transceiver implementations for such OFDM-based systems with the direct-conversion architecture are desirable to enable small-size, low-cost, and low-power-consumption terminals. However, the associated circuit impairments stemming from the processing of analog radio frequency (RF) signals, such as in-phase and quadrature-phase (I/Q) imbalance and carrier frequency offset errors, can severely degrade the obtainable link performance. In this paper, we analyze the effects of these radio impairments in a multiuser SC-FDMA uplink system and present digital-signal-processing-based methods for the joint estimation and equalization of impairments and channel distortions on the receiver side with an arbitrary number of receiver antennas. For the equalization, linear equalizers such as the zero-forcing (ZF) and the minimum mean square error (MMSE) equalizers that utilize pairs of mirror subcarriers are formulated, and the MMSE equalizer is developed to effectively handle mirror subband users with different power levels. Furthermore, for reduced computational complexity, the joint channel and impairment filter responses are efficiently approximated with polynomial-based basis function models. The parameters of the basis functions are then estimated by exploiting the time-multiplexed reference symbols in the LTE uplink subframe structure. The performance of the proposed estimation and equalization methods is assessed with extensive multiuser link simulations, with both single-antenna and dual-antenna base-station receivers, and the results show that the proposed algorithms are able to significantly reduce the impact of channel distortions and radio impairments. The resulting receiver implementation with the proposed techniques enables improved uplink link performance, even when the mobile terminals fulfill their emission requirements, in terms of I/Q images, with no changes in the LTE standard's frame and pilot structures. [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]