This article introduces a digital conversion and linearization unit (DCLU) that performs signal conversion and power amplifier (PA) linearization when the digital-to-analog converter (DAC) is constrained by limited bit resolution. The proposed structure applies an error-and-distortion-feedback (EDF) processing principle that integrates re-quantization, noise shaping, and digital predistortion (DPD) within a single digital unit and avoids explicit inverse modeling. The embedded PA forward description uses a polar look-up table (PLUT) representation of the PA static AM/AM and AM/PM characteristics and a linear filter that captures the measured dynamic response. More advanced approaches are also described in terms of incorporating more elaborate forward models within the DCLU, together with a parallel multi-channel realization that relaxes internal clock-rate requirements through time-interleaved processing. The concept is validated through two RF measurement experiments using a 5G New Radio (NR) transmit waveform at 3.5 GHz and 3.6 GHz (NR band n78). The first experiment uses a broadband Gallium-Nitride (GaN) HMC1114 PA to demonstrate the proof of concept and quantify system behavior under reduced bit resolutions. The second experiment uses the Qorvo QPA3503 GaN Doherty PA to evaluate the approach for an amplifier type that is typically more challenging to linearize. The measured results show that the proposed approach maintains good linearization capability under reduced bit resolutions and, in the reported cases, provides improved transmit waveform quality relative to conventional reference DPD schemes, particularly at lower bit widths.

High peak-to-average-power ratio (PAPR) is an inevitable challenge in orthogonal frequency-division multiplexing (OFDM) based networks, known to be particularly harmful to efficient utilization of practical power amplifiers (PAs). To preserve the waveform quality, PA back-off can be introduced which, however, directly limits the potential uplink (UL) coverage. This paper proposes a novel PAPR reduction method, by transmitting a peak-cancellation signal (PCS) spatially-precoded to the frequency resources within the operating channel, without introducing any overheads or receiver side interference. The proposed approach can be applied to codebook-based and non-codebook-based transmissions, while also allows for extending the PCS frequency allocation towards neighboring physical resource blocks (PRBs) without interference to other users. Extensive numerical results are provided, conforming with the 3GPP 5G NR transmitter requirements, while also incorporating realistic uplink PA models. The obtained numerical results at FR1 reveals up to 2.6 dB net gain in the effective uplink link budget via using the novel PCS, compared to the plain legacy OFDM signal. Such link budget gains translate to substantial uplink coverage improvements, which can be one major asset in future network deployments towards the 6G era.

Unlocking the potential of millimeter-wave (mmWave) phased array systems demands robust nonlinear transmitter modeling and digital pre-distortion (DPD) techniques. In this article, we present a novel behavioral modeling approach and the corresponding linearization solution for beamforming antenna arrays comprising multiple and mutually interacting nonlinear power amplifier (PA) units. Our non-recursive transmitter model simplifies numerical evaluations across diverse phased array/multiple-input multiple-output (MIMO) configurations under crosstalk-induced load modulation. We introduce a novel, nonlinear forward model parameter identification algorithm tailored for crosstalk-prone array systems and applicable in arbitrary MIMO transmitter configurations, enabling precise modeling and characterization using over-the-air (OTA) observations. Furthermore, we propose an offline direct learning architecture based DPD method, harnessing the estimated nonlinear array forward model and specific beam-sweeping procedure, for linearizing phased arrays under severe load modulation. Numerical assessments across various scenarios demonstrate superior performance, while physical validation on a measurement test bench reinforces our methodology’s real-world applicability. Overall, this work paves the way for advanced nonlinear array transmitter optimization and linearization, vital for next-generation wireless communication networks.

In this article, we comprehensively investigate the potential of the digital polar radio transmitter architecture for multi-user massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) downlink system. In terms of throughput performance, we derive a lower bound for the average sum-rate achievable with Gaussian signaling inputs and zero-forcing (ZF) precoding based on Bussgang decomposition. By diagonal approximation, we derive an approximate, yet accurate, model for the distortion caused by uniform polar quantization, which can be used to evaluate the corresponding sum-rate in closed form. To assess the power efficiency, we provide power consumption models with realistic parameters and values for the quantized polar and Cartesian transmitters, based on state-of-the-art integrated circuit (IC) designs and measurements. Extensive numerical results demonstrate that the proposed quantized polar transmitter can enable excellent performance in terms of average sum-rate, symbol error rate (SER), and out-of-band (OOB) emission level, compared to the Cartesian architecture. Furthermore, the power consumption comparisons show that the digital polar transmitter can save more than 36% in the energy consumption under 64-antenna setting in typical 5G enhanced mobile broadband use cases, thus making it highly appealing for future power-efficient massive MIMO transmitter implementations.

This paper investigates the potential to leverage existing 5G NR signals for network-side integrated sensing and communications (ISAC). In general, the synchronization signal block (SSB) is a suitable candidate for always-on downlink sensing, due to its frequent periodical availability and because of its beam-sweeping nature. However, as this work demonstrates, using only the SSB has challenges related to radar ambiguity while being also limited in both distance and velocity resolution due to limited bandwidth and per-beam time duration, respectively. A novel solution is then introduced by combining SSB with downlink control information (DCI) and system information block 1 (SIB1) symbols. The corresponding implications and variants how SIB1 is optimized and configured are discussed, covering both 5G evolution and potential 6G solutions. The performance of the proposed approach is also assessed through realistic numerical evaluations at both 3.5 GHz and 28 GHz network deployments, and shown to yield up to 25 dB suppression in radar peak sidelobe level (PSL) compared to SSB-only based range-velocity profile. Also considerable improvements in the sensing resolution in the order of 120–190% are demonstrated.

This article investigates the feasibility of combinerless multilevel outphasing transmitter as a potential architecture for large millimeter-wave (mmWave) phased arrays. We consider two distinct ways of distributing the component signals to the antennas and develop a model for the received signal at each radiated spatial direction from a phased array. Based on the received signal model, we derive expressions for the signal-to-distortion ratio as well as total power experienced at each spatial direction. Furthermore, antenna branch mismatches, overload distortion and quantization are considered, and an analytical model for the signal-to-distortion ratio at the intended receiver is derived. We additionally establish a model for comparing the achievable energy efficiency to those of the relevant reference methods. Extensive numerical experiments are carried out to verify the analytical works, and to assess the commonly used metrics of error vector magnitude (EVM) and total radiated power adjacent channel leakage ratio (TRP-ACLR). It is shown that the combinerless architecture is a valid option for mmWave phased arrays, demonstrating favorable EVM results and TRP-ACLR beyond the 28 dBc limit imposed by the 3GPP, even in the presence of the considered distortions. The conducted energy efficiency assessment shows that efficiency of the reference methods can be exceeded with sufficient amount of outphasing levels. The considered architecture is thus an interesting alternative for addressing the linearity vs. energy-efficiency challenge in mmWave phased-array systems.

In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT) followed by a linear finite impulse response (FIR) filter. The second proposed method, the spline-based memory polynomial (SMP) approach, contains multiple parallel complex spline-interpolated LUTs together with an input delay line such that more versatile memory modeling can be achieved. For both structures, gradient-based learning algorithms are derived to efficiently estimate the LUT control points and other related DPD parameters. Large set of experimental results are provided, with specific focus on 5G New Radio (NR) systems, showing successful linearization of multiple PA samples as well as a 28 GHz active antenna array, incorporating channel bandwidths up to 200 MHz. Explicit performance-complexity comparisons are also reported between the SPH and SMP DPD systems and the widely-applied ordinary memory-polynomial (MP) DPD solution. The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

In this paper, we present a novel nonlinear digital self-interference canceller algorithm, its implementation details on a software-defined radio (SDR) platform, and performance results of real-time full-duplex experiments on both device and link level. The canceller algorithm is based on an augmented Hammerstein model, with a nonlinear part modeling the transmitter non-idealities followed by a linear filter to model the self-interference (SI) channel. The nonlinear part includes a spline-based model for the nonlinear power amplifier, a polynomial model for baseband nonlinearities, as well as models for I/Q mismatch and LO leakage. The canceller is implemented on an FPGA as a part of an OFDM transceiver testbed for real-time measurements. Extensive real-time measurements show excellent performance: (1) the digital canceller, together with an RF isolator, can suppress the SI to within 1-2 dB's of the receiver noise floor, with total SI suppression of up to 103 dB; (2) digital cancellation of up to 46 dB is evidenced, which is among the highest real-time cancellations in literature; (3) system-level measurements with OFDM signals demonstrate the benefit of utilizing the proposed canceller in a two-way communication scenario, showing up to 90 % increase in sum-rate compared to half-duplex communication.

The large available bandwidths at millimeter-wave (mmW) frequencies enable very high data rates and reduced latencies while can also facilitate high-resolution radio-based sensing. In this paper, we address the problem of providing the communications and sensing functionalities simultaneously at the same frequencies, with specific emphasis on the emerging 5G New Radio (NR) networks. To this end, a novel RF beamforming design and optimization approach is proposed, for dual-functional joint radar-communication systems, providing multiple simultaneous transmit beams to support efficient beamformed communications while an additional beam simultaneously senses the environment around the base-station. The proposed beamforming approach jointly optimizes the transmitter and receiver beamforming weights in order to maximize the sensing performance and mitigate the possible interference stemming from the communication beam, while guaranteeing also the target beamforming gain for the communications link. The performance of the proposed approach is assessed through comprehensive numerical evaluations, demonstrating that substantial gains and benefits can be achieved compared to more ordinary beamforming approaches.

High-level synthesis (HLS) aims to improve the productivity of digital logic design over traditional register-transfer level (RTL) methods. This paper shows that HLS can replace RTL when implementing a complex data path oriented signal processing algorithm under strict throughput constraints. Our system is a nonlinear spline-based Hammerstein self-interference (SI) canceller for full-duplex transceiver capable of achieving high SI suppression, while maintaining low computational complexity. The achieved suppression of the SI is superb 45 dB, while consuming 29 026 of the available LUTs, 17992 of registers, and 655 of the DSP slices on Kintex-7 XC7K410T FPGA. Our paper also compares the usability of two commercial HLS tools that were used in this work.

This paper describes implementation details of a digital-intensive phase modulator architecture that does not require a frequency synthesizer to cover a wide carrier frequency range. The phase modulator operation is based on toggling the output accurately during the sample period to generate the phase-modulated signal. The toggling instants within the sample period are calculated by DSP solvers that utilize linear interpolation. The interpolation effectively multiplies the phase signal sample rate by the modulator phase resolution, which enables wider signal bandwidth and a completely digital method of defining the transmitter carrier frequency. The phase modulator concept is verified by implementing it as a part of an outphasing transmitter in 28 nm CMOS. With a constant sample rate of 1.5 GHz and without any predistortion, the transmitter achieves better than -28 dBc ACLR with 100 MHz aggregated LTE downlink signal between 0.8-2.0 GHz carrier frequency.

This paper examines one source of spectral degradation in polar and multilevel outphasing transmitters. The degradation is caused by the amplitude signal appearing at the transmitter output as a baseband component, in addition to the desired RF signal. This baseband component contains sampling images and quantization noise across the spectrum. Thus, it adds noise at the signal band where it cannot be filtered and limits the achievable ACLR, particularly in wideband LTE and 5G systems. We analyze the origin of this phenomenon and related effects of system and signal parameters, and propose three design solutions for eliminating or alleviating the problem. Our analysis and simulations demonstrate that using a voltage-subtracting power combiner cancels the described degradation, potentially leading to significant improvement in spectral performance.

In this article, the adoption and performance of a constant envelope (CE) type spatial precoder is addressed in large-scale multiuser MIMO based cellular network. We first formulate an efficient computing solution to obtain the antenna samples of such CE precoder. We then evaluate the achievable CE precoder based multiuser downlink (DL) system performance and compare it with the corresponding performance of more ordinary zero-forcing (ZF) spatial precoder. We specifically also analyze how realistic highly nonlinear power amplifiers (PAs) affect the achievable DL performance, as the individual PA units in largearray or massive MIMO systems are expected to be small, cheap and operating close to saturation for increased energy-efficiency purposes. It is shown that the largely reduced peak-to-average power ratio (PAPR) of the PA input signals in the CE precoder based system allows for pushing the PA units harsher towards saturation, while allowing to reach higher signal-to-interference-plus-noise ratio (SINRs) at the intended receivers compared to the classical ZF precoder based system. The obtained results indicate that the CE precoder can outperform the ZF precoder by up to 5-6 dBs, in terms of the achievable SINRs, when the PA units are pushed towards their saturating region. Such large gains are a substantial benefit when seeking to improve the spectral and energy-efficiencies of the mobile cellular networks.

A novel reduced-complexity digital predistortion (DPD) solution is presented in this paper. The proposed DPD can suppress the unwanted distortions due to power amplifier (PA) nonlinearity and I/Q modulator impairments in direct conversion transmitters using reduced-bandwidth filtered basis functions. Moreover, the DPD parameter estimation is based on very simple decorrelation based closed-loop processing and reduced-bandwidth observation, thus further reducing the overall complexity. The proposed DPD can be used in large array or massive MIMO systems with large number of radio transceivers and PAs, where reducing the complexity of the DPD processing is very critical.

Digital predistortion (DPD) is an effective way of mitigating spurious emission violations without the need of a significant backoff in the transmitter, thus providing better power efficiency and network coverage. In this paper, the IM3 subband DPD, proposed earlier by the authors, is extended to more than two component carriers (CCs) through a sequential learning solution. The DPD learning is iterated over each spurious emission generated by each pair and trio of CCs. We train and apply the DPD coefficients for the intermodulation distortion (IMD) products until a satisfactory performance is achieved. The algorithm is tested in simulations using MATLAB and in a novel, real-time implementation on a CPU via a software version of the algorithm using GNURadio.

In this paper, we develop new models and methods for exploring multidimensional design spaces associated with digital predistortion (DPD) systems. DPD systems are important components for power amplifier linearization in wireless communication transceivers. In contrast to conventional DPD implementation methods, which are focused on optimizing a single objective — most commonly, the adjacent channel power ratio (ACPR) — without systematically taking into account other relevant metrics, we consider DPD system implementation in a multiobjective optimization context. In our targeted multiobjective context, trade-offs among power consumption and multiple DPD performance metrics are jointly optimized subject to performance constraints imposed by the given modulation scheme. Through synthesis and simulation results, we demonstrate that DPD systems derived through our design space exploration techniques exhibit significantly improved trade-offs among multidimensional implementation criteria, including energy consumption, ACPR, and symbol error-rate. Additionally, we perform experiments using three different LTE modulation schemes, and we demonstrate that our multiobjective optimization approach significantly enhances system adaptivity in response to changes in the employed modulation scheme.

In this paper, we present a class D power amplifier (PA) design in 28 nm CMOS for a multilevel outphasing transmitter. For increased output power, the design consists of eight unit PAs with cascoded output stages. In order to improve back-off efficiency from conventional outphasing, the PAs are switched on and off in pairs for different amplitude levels, which is challenging to implement with cascoded class D. As a solution, we introduce a new on/off switching method based on logic gates utilizing two square wave voltages to produce either a similar square wave or a constant voltage. This method enables a higher level of integration by using low-voltage digital signals for on/off control, while eliminating the timing mismatch between output transistors caused by a level shifter. The simulated peak output power of the PA is 32.4 dBm, and its peak efficiency is 34.1%.

This article investigates novel adaptive self-interference cancellation solutions and the total integrated cancellation performance of a mobile single-antenna inband full-duplex transceiver. First, novel self-adaptive digital self-interference cancellation algorithms are described, with an emphasis on tracking of time-varying self-interference coupling channel in a mobile device as well as on structural ability to suppress also nonlinear self-interference with highly nonlinear mobile power amplifiers. This leads to an advanced self-adaptive nonlinear digital canceller which utilizes a novel orthogonalization procedure for nonlinear basis functions, together with low-cost LMS-based parameter learning. The achievable self-interference cancellation performance is then evaluated with actual RF measurements using mobile device scale RF components, in particular a highly nonlinear PA. The measurements also incorporate a novel self-adaptive RF cancellation circuit in order to realistically assess the total integrated cancellation performance. The reported results show that highly efficient self-interference cancellation can be achieved also in a mobile device, despite a heavily nonlinear PA and limited computing and hardware resources. The proposed cancellation solutions, when integrated together, show that 100 dB of self-interference can be cancelled using a 20 MHz LTE waveform, while the SI can be attenuated by over 110 dB with a narrower bandwidth of 1.4 MHz, all measured at 2.4 GHz ISM band. Furthermore, these results are achieved using a highly nonlinear transmitter power amplifier and fully adaptive canceller structures which can track a rapidly changing coupling channel in a mobile full-duplex device.

In this article, we focus on the RF and digital front-end design and implementation challenges associated with future 5G radio access systems with special emphasis on spectrally contained waveforms and small-cell system scenarios. In general, filter bank based multicarrier (FBMC) type of techniques have various potential benefits due to their excellent spectral containment compared to classical OFDM(A). However, these spectrally contained waveforms lose their intriguing spectral properties when power amplifier (PA) nonlinearities are considered. Flexible and efficient digital predistortion (DPD) algorithms are thus considered an interesting solution in order to restore the spectral containment of such advanced 5G waveforms. Noncontiguous spectrally-agile transmission is another key feature of future 5G systems for increasing data rates and spectral allocation flexibility. However, the PA nonlinearities impose even more severe challenges in such noncontiguous transmission scenarios due to the resulting spurious intermodulation emissions that can easily violate the emission limits or even desensitize the own receiver in frequency division duplexing based systems. Furthermore, at the network deployment level, different small-cell concepts are expected to play a major role in future 5G networks. Unlike the ordinary macro base-stations, the digital computing capabilities in small-cell base-stations are much more limited. Furthermore, they should also adopt lower-cost and small-size analog RF components, while still maintaining high energy-efficiency. The afore-mentioned constraints, along with advanced 5G waveforms, call for flexible and low-complexity DPD solutions, a challenge addressed in this article. We report novel DPD methods with built-in capability to direct the linearization performance to pre-defined frequencies or subbands in a flexible manner, and demonstrate their good performance and complexity benefits in the context of non-contiguous FBMC transmission.

Filter bank multicarrier (FBMC) is considered as one of the strong 5G waveform candidates due to better spectral containment compared to orthogonal frequency division multiplexing (OFDM). However, when considering the spectral leakage effects appearing in practical devices due to transmitter non-idealities, such as power amplifier (PA) nonlinearity and inphase-quadrature (I/Q) imbalance, the nice spectral properties of FBMC may be severely degraded, thus questioning the additional complexity needed to generate such waveforms in baseband. In this paper, digital pre-distortion (DPD) is investigated as a practical solution for both of these problems. We extend the study also to potential applications of spectrum sensing based cognitive radio in future wireless communications. We utilize the benefits of the analysis filter bank of FBMC receiver in wideband multichannel spectrum sensing. In this context, the power leakage due to transmitter non-idealities also makes it difficult to identify spectral gaps amongst relatively strong primary transmissions. It is demonstrated that effective DPD greatly facilitates both spectrum sensing and spectrum utilization functions and thus enhances the overall spectral efficiency in opportunistic dynamic spectrum use scenarios.

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.

Spurious intermodulation components have recently been identified as a major problem in carrier aggregation mobile transmitters with multi-band power amplifiers (PAs). This article presents novel adaptive digital predistortion (DPD) solutions with reduced complexity in both the predistortion processing and the feedback paths, to tackle this problem. Compared with conventional DPDs which aim to linearize the whole transmit bandwidth, the proposed technique aims at mitigating only those intermodulation components which are most problematic from the spurious emission limit perspective. The proposed technique is verified with extensive simulations in various 3GPP LTE-A carrier aggregation scenarios, showing that the intermodulation spurs can be efficiently mitigated below the spurious emission limit with relatively small back-offs.

Power-constrained mobile radio communication transmitters drive their transmit power amplifiers close to their saturation regions, which results in nonlinear intermodulation distortion that is especially harmful in multi-cluster and carrier aggregation transmission scenarios. Digital predistortion is a method for linearizing the transmitter and suppressing the most harmful spurious emissions at the transmitter power amplifier output. This paper describes a programmable implementation of a digital predistortion filter on a heterogeneous Transport Trigger Architecture (TTA) multiprocessor. The predistortion algorithm is based on a parallel Hammerstein polynomial model and the experimental results show that the proposed programmable architecture is capable of linearizing a 20 MHz LTE carrier in realtime with a power consumption that is suitable for mobile devices.

We consider the multiuser frequency allocation problem in single-input single-out put (SISO) LTE-A type uplink with carrier aggregation (CA). The increased bandwidth in LTE-A system allows orthogonal allocation of subcarriers among users. We consider both consecutive and distributed frequency allocation strategies with per user transmit power constraints and more realistic power amplifier models accounting the dependence of the amplifier efficiency on the frequency allocation. A novel binary integer programming with water-filling power allocation is proposed for consecutive frequency allocation. The system level performance is evaluated via computer simulations. The results shed light to the problem of frequency allocation with real user devices both from theoretical and practical points of view.

A novel approach for the frequency response mismatch mitigation of a 4-channel Time-Interleaved ADC (TI-ADC) is proposed which enables the interleaving mismatch identification to be performed in a fully blind online manner. This is accomplished via generating an appropriate complex valued signal from the real valued TI-ADC output signal which allows deploying complex statistical signal processing methods for the mismatch identification in a manner similar to the I/Q imbalance correction. As proof of concept, the compensation architecture is implemented, demonstrated and tested using real RF-sampling 4-channel TI-ADC hardware data, evidencing spur reduction below 80 dBFS.

This paper addresses the modeling and cancellation of self-interference in full-duplex direct-conversion radio transceivers, operating under practical imperfect radio frequency (RF) components. First, detailed self-interference signal modeling is carried out, taking into account the most important RF imperfections, namely, transmitter power amplifier nonlinear distortion as well as transmitter and receiver IQ mixer amplitude and phase imbalances. The analysis shows that after realistic antenna isolation and RF cancellation, the dominant self-interference waveform at the receiver digital baseband can be modeled through a widely linear transformation of the original transmit data, opposed to classical purely linear models. Such widely linear self-interference waveform is physically stemming from the transmitter and receiver IQ imaging and cannot be efficiently suppressed by classical linear digital cancellation. Motivated by this, novel widely linear digital self-interference cancellation processing is then proposed and formulated, combined with efficient parameter estimation methods. Extensive simulation results demonstrate that the proposed widely linear cancellation processing clearly outperforms the existing linear solutions, hence enabling the use of practical low-cost RF front ends utilizing IQ mixing in full-duplex transceivers.

As the duplexing distances in emerging wireless systems are getting more and more narrow, achieving sufficient isolation between transmit and receive chains using radio frequency (RF) filtering alone becomes increasingly complex. Particularly challenging problem in this context is the spectral regrowth of nonlinear power amplifiers (PAs) in the transmit chain, and other transmitter out-of-band (OOB) emissions, which can heavily desensitize the receiver chain. In this letter, we first carry out detailed modeling of transmitter OOB emissions due to practical wideband PAs with memory effects. Stemming from this modeling, and using the known digital transmit data inside the transceiver as reference, we then propose an efficient nonlinear digital cancellation technique to suppress the transmitter OOB emissions in the receiver path. The proposed technique is verified and analyzed using extensive computer simulations, rendering excellent suppression properties, hence enabling sufficient TX-RX isolation in frequency division duplexing (FDD) transceivers without any extra analog/RF filtering or PA linearization.

Despite the intensive recent research on wireless single-channel full-duplex communications, relatively little is known about the transceiver chain nonidealities of full-duplex devices. In this paper, the effect of nonlinear distortion occurring in the transmitter power amplifier (PA) and the receiver chain is analyzed, beside the dynamic range requirements of analog-to-digital converters (ADCs). This is done with detailed system calculations, which combine the properties of the individual electronics components to jointly model the complete transceiver chain, including self-interference cancellation. They also quantify the decrease in the dynamic range for the signal of interest caused by self-interference at the analog-to-digital interface. Using these system calculations, we provide comprehensive numerical results for typical transceiver parameters. The analytical results are also confirmed with full waveform simulations. We observe that the nonlinear distortion produced by the transmitter PA is a significant issue in a full-duplex transceiver and, when using cheaper and less linear components, also the receiver chain nonlinearities become considerable. It is also shown that, with digitally intensive self-interference cancellation, the quantization noise of the ADCs is another significant problem.

This paper addresses the analysis of oscillator phase-noise effects on the self-interference cancellation capability of full-duplex direct-conversion radio transceivers. Closed-form solutions are derived for the power of the residual self-interference stemming from phase noise in two alternative cases of having either independent oscillators or the same oscillator at the transmitter and receiver chains of the full-duplex transceiver. The results show that phase noise has a severe effect on self-interference cancellation in both of the considered cases, and that by using the common oscillator in upconversion and downconversion results in clearly lower residual self-interference levels. The results also show that it is in general vital to use high quality oscillators in full-duplex transceivers, or have some means for phase noise estimation and mitigation in order to suppress its effects. One of the main findings is that in practical scenarios the subcarrier-wise phase-noise spread of the multipath components of the self-interference channel causes most of the residual phase-noise effect when high amounts of self-interference cancellation is desired.

In-phase/quadrature (I/Q) imbalance degrades heavily the image rejection performance of direct-conversion radios. I/Q imbalance also changes the statistics of the received signal, and in particular makes a circular signal non-circular. This fact has been utilized in compensating receiver I/Q imbalances, utilizing second-order statistics. In this article, we investigate whether moment circularity of order higher than two can be exploited in receiver I/Q imbalance compensation. It is established that the fourth-order moment E[x3x*] is a suitable statistic for measuring the circularity of common communications signals based on complex-valued alphabets such asM-QAM andM-PSK withM>; 2. Two blind algorithms, based on Newton's method, are then proposed for receiver I/Q imbalance compensation. They are shown by simulations to converge faster or, alternatively, to give lower steady-state variance, than the reference methods that are based on second-order statistics.

I/Q signal processing based communication systems suffer from analog front-end (FE) imperfections such as in-phase and quadrature-phase (I/Q) imbalance and carrier frequency offset (CFO). These impairments are commonly encountered in all practical implementations, and severely degrade the obtainable link performance. Moreover, orthogonal frequency division multiplexing (OFDM)-based systems are particularly sensitive to radio frequency (RF) impairments. In this paper, we analyze the impact of transmitter and receiver I/Q imbalance together with channel distortion and CFO error on an ideal transmit signal, and propose low-complexity DSP algorithms and compensation structure for coping with such imperfections. Based on our proposed estimation/compensation structure, we are able to decouple the impairments and process them individually with rather low-complexity. More specifically, we first apply a blind algorithm for receiver I/Q imbalance compensation, followed by an efficient time domain CFO estimator and compensator. The transmitter I/Q imbalance and channel are then equalized jointly, in the frequency domain, with maximum-likelihood (ML) or zero-forcing (ZF) schemes, respectively. The applied algorithms are either blind working without aid of any training symbol or use only one OFDM symbol for impairments estimation, providing an efficient alternative solution with reduced complexity. The computer simulation results indicate a close to ideal performance of ZF scheme, and suggest that additional performance improvement due to frequency diversity can be obtained when ML estimation technique is employed.

I/Q imbalance is one of the main practical obstacles in the implementation of direct-conversion receivers. This paper presents novel DSP-based techniques for the estimation and compensation of frequency-selective receiver I/Q imbalances in OFDM systems. The estimation is based on a special pilot or preamble structure, and frequency-domain smoothing is utilized to effectively reduce the effect of noise. Reliable estimation is attained with a minimum of two OFDM symbols. Further, it is shown that estimation of frequency-selective I/Q imbalance and the frequency-selective radio channel can be decoupled, which is beneficial from the computational complexity point of view. Simulation analysis shows impressive performance with fast convergence.

Gain and phase differences between the analog in-phase (I) and quadrature (Q) branches of a quadrature receiver are unavoidable, and seriously degrade its image rejection capabilities. Furthermore, this so-called I/Q imbalance problem is in general a frequency-dependent phenomenon, which is often ignored in many otherwise excellent work. In this paper, we take this frequency-dependency into account and study a class of I/Q imbalance compensators based on widely linear (WL) processing of the received mismatched signal, under the assumption that the ideal baseband signal is proper (or circular). In other words, the complementary autocorrelation function of the ideal baseband signal is assumed to vanish, which is a valid assumption for most practical communications signals. Under I/Q imbalance the observed baseband equivalent signal becomes improper, and I/Q imbalance compensation can be performed by making the observation proper again. We propose a simple blind (non-data aided) WL compensator structure for suppressing the mirror-frequency interference. It shows impressive performance and has many additional desirable features, such as immunity to channel noise and the fading channel.

The so-called single-carrier FDMA (SC-FDMA) waveform class, also known as DFT-spread OFDM, is a special form of multicarrier modulation, and has received a lot of interest in 3.9G system context recently. This paper addresses the radio implementation and RF impairment issues related to the reception of SC-FDMA waveforms. The main emphasis is on the so-called I/Q imbalance problem which in general results in imperfect attenuation of the mirror-frequencies. Here, the role of mirror-frequencies and mirror-frequency interference is addressed in detail from the SC-FDMA signals point of view, covering both the localized and distributed transmission modes. Furthermore, under perfect I/Q balance, it is shown that SC-FDMA signals satisfy certain circularity conditions related to the second-order statistics of complex random signals. This circularity, on the other hand, is lost due to I/Q imbalance which can then be used as a basis for developing efficient digital signal processing (DSP)-based algorithms to compensate for the I/Q imbalance effects. Comprehensive system simulations are carried out in both the localized and distributed spectral deployment cases, with and without digital compensation, to illustrate the relative effects of I/Q imbalances and the compensation stage on the overall system performance.

When targeting receiver integrability and flexibility, the choice of the front-end architecture is in key position. Instead of the traditional superheterodyne architecture, more recent I/Q or quadrature receiver front-ends are receiving increasingly more interest. One crucial aspect in quadrature receiver front-ends is the amplitude and phase matching of the analog I and Q signal branches. I/Q mismatches result in incomplete image signal or mirror frequency attenuation which must be enhanced using additional analog or digital signal processing. This paper presents and analyzes a novel DSP-based blind (non-data-aided) technique for I/Q imbalance compensation, utilizing a property of the ideal baseband equivalent called circularity. The weights of the compensator are computed directly from the estimates of the second-order moments of the mismatched baseband equivalent received signal. This algorithm is further simplified, with minimal loss in performance, yielding an extraordinarily simple yet effective compensation technique which ideally triples the dB value of the analog front-end image rejection ratio. The algorithms are applicable to any I/Q receiver structure, whether single-channel or multi-channel, and are in fact totally independent of any specific structure or characteristic (other than circularity) of the ideal baseband equivalent signal