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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]

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 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]

This paper presents a novel digital self-interference canceller for an inband multiple-input-multiple-output (MIMO) full-duplex radio. The signal model utilized by the canceller is capable of modeling the in-phase quadrature (IQ) imbalance, the nonlinearity of the transmitter power amplifier, and the crosstalk between the transmitters, thereby being the most comprehensive signal model presented thus far within the full-duplex literature. Furthermore, it is also shown to be valid for various different radio frequency (RF) cancellation solutions. In addition to this, a novel complexity reduction scheme for the digital canceller is also presented. It is based on the widely known principal component analysis, which is used to generate a transformation matrix for controlling the number of parameters in the canceller. Extensive waveform simulations are then carried out, and the obtained results confirm the high performance of the proposed digital canceller under various circuit imperfections. The complexity reduction scheme is also shown to be capable of removing up to 65% of the parameters in the digital canceller, thereby significantly reducing its computational requirements. [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]

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]

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 predistortion (DPD) solution based on a direct learning approach, which is capable of reducing the unwanted emissions resulting from the power amplifier (PA) at any prespecified frequency located in the transmitter's out-of-band or spurious domain. The proposed scheme is based on evaluating the power spectral density (PSD) of the PA output signal and optimizing the DPD coefficients iteratively in order to minimize the output PSD around the prespecified frequency. To highlight the feasibility of the proposed implementation, the predistortion processing is kept as simple as possible, deploying quasi-memoryless polynomial models. Efficient mitigation of unwanted emissions around the target frequency is demonstrated via simulations and actual RF measurements, in both single- and dual-carrier waveform scenarios, using memoryless and memory-based PAs. The proposed DPD solution could be potentially employed in applications such as mobile devices utilizing noncontiguous multicarrier transmission, where the intermodulation spurs may overlap with the device's own receiver band, or could be potentially violating the spurious emission limits. Another target application is cognitive radio, where the PA may produce unwanted emissions that are interfering with primary-user transmissions. To the best of the authors' knowledge, there does not exist a similar technique in the open literature, and thus, the purpose of this paper is to encourage scientific discussions and technological innovations toward the creation of relatively low-complexity frequency-optimized predistortion techniques employed against selected unwanted emissions produced by the transmitter. [ABSTRACT FROM AUTHOR]

Direct-conversion architecture-based orthogonal frequency division multiplexing (OFDM) systems are\ troubled by impairments such as in-phase and quadrature-phase (I/Q) imbalance and carrier frequency offset (CFO). These impairments are unavoidable in any practical implementation and severely degrade the obtainable link performance. In this contribution, we study the joint impact of frequency-selective I/Q imbalance at both transmitter and receiver together with channel distortions and CFO error. Two estimation and compensation structures based on different pilot patterns are proposed for coping with such impairments. The first structure is based on preamble pilot pattern while the second one assumes a sparse pilot pattern. The proposed estimation/compensation structures are able to separate the individual impairments, which are then compensated in the reverse order of their appearance at the receiver. We present time-domain estimation and compensation algorithms for receiver I/Q imbalance and CFO and propose low-complexity algorithms for the compensation of channel distortions and transmitter IQ imbalance. The performance of the compensation algorithms is investigated with computer simulations as well as with practical radio frequency (RF) measurements. The performance results indicate that the proposed techniques provide close to the ideal performance both in simulations and measurements. [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]

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 multi-channel receivers, where the overall bandwidths are in the range of several megahertz and the incoming carriers located 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 direct-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. [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 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]

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]

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]

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]

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]

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]

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]

In-band full-duplex relays transmit and receive simultaneously at the same center frequency, hence offering enhanced spectral efficiency for relay deployment. In order to deploy such full-duplex relays, it is necessary to efficiently mitigate the inherent self-interference stemming from the strong transmit signal coupling to the sensitive receive chain. In this article, we present novel state-of-the-art antenna solutions as well as digital self-interference cancellation algorithms for compact MIMO fullduplex relays, specifically targeted for reduced-cost deployments in local area networks. The presented antenna design builds on resonant wavetraps and is shown to provide passive isolations on the order of 60?70 dB. We also discuss and present advanced digital cancellation solutions, beyond classical linear processing, specifically tailored against nonlinear distortion of the power amplifier when operating close to saturation. Measured results from a complete demonstrator system, integrating antennas, RF cancellation, and nonlinear digital cancellation, are also presented, evidencing close to 100 dB of overall self-interference suppression. The reported results indicate that building and deploying compact full-duplex MIMO relays is already technologically feasible. [ABSTRACT FROM PUBLISHER]