This paper analyzes the joint effects of in-phase and quadrature (I/Q) imbalance and power amplifier (PA) distortion for RF multiple input multiple output (MIMO) transmitters in the presence of crosstalk. This paper proposes candidate models for the digital predistortion of static I/Q imbalanced sources exciting a dynamic MIMO Volterra system. The proposed models are enhanced using a novel technique based on subsample resolution to account for dynamic I/Q imbalance distortions. Finally, the computational complexity of the proposed models is analyzed for implementation suitability in digital platforms. It is shown that the error spectrum for the proposed models in subsample resolution reaches the noise floor of the measurements. The proposed models achieve a normalized mean squared error of -50 dB and an adjacent channel power ratio of -57 dB for signal bandwidths upto 65 MHz and crosstalk levels ranging to -10 dB. These results demonstrate the effectiveness of the proposed techniques in the joint mitigation of I/Q imbalance and PA distortion with crosstalk for a typical 2x2 MIMO telecommunication setup.

This paper presents a multiple-input multiple-output (MIMO) nonlinear mitigation technique for closely spaced concurrent aggregated carrier systems. The transmitter architecture considers band-limited sources, where the predistorter and signal bandwidth are the same, thus reducing transmitter hardware cost and power consumption. The technique relies on multirate processing and linear filtering and uses the carrier frequencies to isolate the contribution of linear and nonlinear basis functions to the desired bands. This approach can be used with any MIMO model structure. In particular, models are linear in the parameters of low computational complexity. The technique was evaluated using three concurrent carriers of 50 MHz each fed to a Doherty amplifier. The results show significant reduction in the error vector magnitude and improvements for the transmitter efficiency using the proposed compensation technique.

A method is proposed for determining the correlated and uncorrelated parts of phase noise spectra (PNS) of two continuous wave radio signals of different frequencies, ω1 and ω2. The PNS of the two signals and of mixed signals are measured. The PNS are modelled as having a correlated part that is the same for both signals, except for a multiplicative factor, and uncorrelated parts, that are different for the two signals. A property of the model that the PNS of some mixing products are linear combinations of the PNS of the signals at ω1, ω2, and ω1 − ω2 is experimentally verified. The difference of the PNS at ω1 + ω2 and ω1 − ω2 is proportional to the correlated part of the PNS and is a part of auxiliary functions that are used for finding the multiplicative factor and the correlated, partly correlated, and uncorrelated phase noise at different offset frequencies. A conventional spectrum analyser was used to characterise two signal generators, a phase-coherent and a non-phase-coherent one. For the phase-coherent generator the phase noise of two signals was found to be correlated for offset frequencies below 10 Hz, partly correlated for 10 Hz–1 kHz and uncorrelated above 1 kHz.

A non-parametric technique for modeling the behavior of power amplifiers is presented. The proposed technique relies on the principles of density estimation using the kernel method and is suited for use in power amplifier modeling. The proposed methodology transforms the input domain into an orthogonal memory domain. In this domain, non-parametric static functions are discovered using the kernel estimator. These orthogonal, non-parametric functions can be fitted with any desired mathematical structure, thus facilitating its implementation. Furthermore, due to the orthogonality, the non-parametric functions can be analyzed and discarded individually, which simplifies pruning basis functions and provides a tradeoff between complexity and performance. The results show that the methodology can be employed to model power amplifiers, therein yielding error performance similar to state-of-the-art parametric models. Furthermore, a parameter-efficient model structure with 6 coefficients was derived for a Doherty power amplifier, therein significantly reducing the deployment’s computational complexity. Finally, the methodology can also be well exploited in digital linearization techniques.

A technique to extend the effective measurement bandwidth of a non-coherent vector receiver is presented. This bandwidth extension technique relies on the use of a pilot signal (known a priori), which is added on the signal of interest and is measured in a single receiver. Compared to other bandwidth extension techniques referred as stitching techniques, the proposed approach avoids error propagation in the measurement bandwidth and simultaneously enables the measurement of signals that do not contain energy in certain spectral bands.

The pilot signal is created in digital stages, which tackles to large extent the requirement of the a priori knowledge of this signal. Further, the pilot signal is designed to minimize estimation errors of the proposed technique, providing enhanced performance. It is analytically shown that the error incurred by the proposed method is always lower than the error from the measurement noise.

Measurement results show the method functionality with an error in the range of −50 dB of the signal measured. Finally, the usefulness of the proposed technique is illustrated by measuring the input and output of an amplifier with dynamic range in excess of 80 dB over 290 MHz using an 18 MHz bandwidth receiver. This measurement could not have been performed by existing stitching techniques.

An instrumentation, measurement and post-processing technique is presented to characterize transmitters by multiple input multiple output (MIMO) Volterra series. The MIMO Volterra series is decomposed as the sum of nonlinear single-variable self-kernels and a multi-variable cross-kernel. These kernels are identified by sample averages of the outputs using inputs of different sample periodicity. This technique is used to study the HW effects in a RF MIMO transmitter composed by input and output coupling filters (cross-talk) sandwiching a non-linear amplification stage. The proposed technique has shown to be useful in identifying the dominant effects in the transmitter structure and it can be used to design behavioral models and compensation techniques.

Since they appeared, wireless technologies have deeply transformed our society. Today, wireless internet access and other wireless applications demandincreasingly more traffic. However, the continuous traffic increase can be unbearableand requires rethinking and redesigning the wireless technologies inmany different aspects. Aiming to respond to the increasing needs of wirelesstraffic, we are witnessing a rapidly evolving wireless technology scenario.This thesis addresses various aspects of the transmitters used in wireless communications.Transmitters present several hardware (HW) impairments thatcreate distortions, polluting the radio spectrum and decreasing the achievabletraffic in the network. Digital platforms are now flexible, robust and cheapenough to enable compensation of HW impairments at the digital base-bandsignal. This has been coined as ’dirty radio’. Dirty radio is expected in future transmitters where HW impairments may arise to reduce transmitter cost or to enhance power efficiency. This thesis covers the software (SW) compensation schemes of dirty radio developed for wireless transmitters. As describedin the thesis, these schemes can be further enhanced with knowledge of thespecific signal transmission or scenarios, e.g., developing cognitive digital compensationschemes. This can be valuable in today’s rapidly evolving scenarioswhere multiple signals may co-exist, sharing the resources at the same radiofrequency (RF) front-end. In the first part, this thesis focuses on the instrumentation challenges andHWimpairments encountered at the transmitter. A synthetic instrument (SI)that performs network analysis is designed to suit the instrumentation needs.Furthermore, how to perform nonlinear network analysis using the developedinstrument is discussed. Two transmitter HW impairments are studied: themeasurement noise and the load impedance mismatch at the transmitter, asis their coupling with the state-of-the-art digital compensation techniques.These two studied impairments are inherent to measurement systems and areexpected in future wireless transmitters. In the second part, the thesis surveys the area of behavioral modeling and digital compensation techniques for wireless transmitters. Emphasis is placed on low computational complexity techniques. The low complexity is motivated by a predicted increase in the number of transmitters deployed in the network, from base stations (BS), access points and hand-held devices. A modeling methodology is developed that allows modeling transmitters to achieve both reduced computational complexity and low modeling error. Finally, the thesis discusses the emerging architectures of multi-channel transmittersand describes their digital compensation techniques. It revises the MIMOVolterra series formulation to address the general modeling problem anddrafts possible solutions to tackle its dimensionality. In the framework of multi-channel transmitters, a technique to compensate nonlinear multi-carrier satellite transponders is presented. This technique is cognitive because it uses the frequency link planning and the pulse-shaping filters of the individual carriers. This technique shows enhanced compensation ability at reduced computational complexity compared to the state-of-the-art techniques and enables the efficient operation of satellite transponders.

Aiming to reduce the power/mass requirements in satellite transponders and toreduce mission costs, joint amplification of multiple-carriers using a singleHigh-Power Amplifier (HPA) is being considered. In this scenario, a carefulinvestigation of the resulting power efficiency is essential as amplification isnonlinear, and multicarrier signals exhibit enlarged peak-to-average power ratio.Thus, operating the amplifier close to saturation vastly increases signal distortionresulting in a severe degradation of performance, especially for higher ordermodulations. This paper proposes a reduced-complexity digital pre-distortion(DPD) scheme at the transmitter and a corresponding equalizer (EQ) at thereceiver to mitigate these nonlinear effects. Scenarios include both the forward aswell as the return links. In particular, the paper exploits the MIMO Volterrarepresentation and builds on a basis pursuit approach using a LASSO (leastabsolute shrinkage and selection operator) algorithm to achieve an effienct basisrepresentation, avoiding large computational complexity, to describe the selectionof pre-distorter/ equalizer model. The work further compares and contrasts thetwo mitigation techniques taking various system aspects into consideration. Thegains, in performance and amplification efficiency, demonstrated by the use ofDPD/ EQ motivate their inclusion in next generation satellite systems.

A digital predistortion (DPD) scheme is presented for non-linear distortion mitigation in multi-carrier satellite communication channels. The proposed DPD has a multiple-input multiple-output architecture similar to data DPD schemes. However, it enhances the mitigation performance of data DPDs using a multi-rate processing algorithm to achieve spectrum broadening of non-linear operators. Compared to single carrier (single-input single-output) signal (waveform) DPD schemes, the proposed DPD has lower digital processing rate reducing the required hardware cost of the predistorter. The proposed DPD outperforms, in total degradation, both data and signal DPD schemes. Further, it performs closest to a channel bound described by an ideally mitigated channel with limited maximum output power.

This paper analyzes the effects of load impedancemismatch in power amplifiers which linearity has been enhancedusing various digital predistortion (DPD) algorithms. Two different power amplifier architectures are considered: a class AB and a Doherty amplifier and three model structures for the DPD model are compared: memoryless polynomial (MLP), general memory polynomial (GMP) and Kautz-Volterra functions (KV). This paper provides a sensitivity analysis of the linearized amplifiers under load mismatch conditions and reports the performance when dynamic parameter identification for the DPD is used to compensate for the changes in the load impedance. In general,power amplifiers linearity is sensitive to load impedance mismatch. Linearity may degrade as much as 10 dB (in normalized mean square error) according to the magnitude and the phase of the reflection coefficient provided by the load impedance. However, depending on the amplifier design, the sensitivity toload impedance mismatch varies. While the Doherty amplifier studied show significant linearity degradations in the in-band and out-of-band distortions, the out-of-band distortions of the studied class AB were less sensitive to the load impedance mismatch. In adaptive DPD schemes, the performance obtained in the MLP model does not benefit from the updating scheme and the performance achieved is similar to a static case, where no updates are made. This stresses the memory requirements in the predistorter. When employing the GMP and the KV models in an adaptive DPD scheme, they tackle to a larger extent the linearity degradations due to load impedance mismatch.