A digital predistorter, modeled by an augmented real-valued time-delay neural network (ARVTDNN), has been proposed and found suitable to mitigate the nonlinear distortions of the power amplifier (PA) along with modulator imperfections for a wideband direct-conversion transmitter. The input signal of the proposed ARVTDNN consists of Cartesian in-phase and quadrature phase (I/Q) components, as well as envelope-dependent terms. Theoretical analysis shows that the proposed model is able to produce a richer basis function containing both the desired odd- and even-order terms, resulting in improved modeling capability and distortion mitigation. Its actual performance has been validated through extensive simulations and experiments. The results show that the compensation and hardware impairment mitigation capabilities of the ARVTDNN are superior to the existing state-of-the-art real-valued focused time-delay neural network (RVFTDNN) by 3-4 dB for the adjacent channel power ratio and by 2-3 dB in terms of the normalized mean square error. Other important features of the proposed model are its reduced complexity, in terms of the number of parameters and floating-point operations, and its improved numerical stability compared to the RVFTDNN model.

The behavior of a power amplifier (PA) is substantially affected by the output mismatch and mutual coupling in modern compact transmitters. To date, different works in the literature address the problem of coupling and mismatch separately, which are limited in terms of performance with a higher level of mismatch and mutual coupling. This paper identifies the reflection at the PA-antenna interface to be an effective parameter to unify the problem of mismatch and mutual coupling. Thus, a reflection-aware PA modeling and linearization method is proposed to compensate the adverse effect of mismatch and/or mutual coupling. The performance of the proposed method is investigated with a class AB and a Doherty PA under wide range of output mismatch and/or mutual coupling conditions with a 20-MHz WCDMA signal. The proposed method shows robust performance with an average adjacent channel power ratio better than 45 dBc. Such robust linearization performance under diverse output mismatch and mutual coupling conditions is highly desirable for modern and future communication systems that are subject to undergo rapid fluctuations under antenna matching and cross-coupling conditions.

The majority of techniques that deal with the mitigation of in-phase and quadrature-phase (I/Q) imbalance at the transmitter (pre-compensation) require long training sequences, reducing the throughput of the system. These techniques also require a feedback path, which adds more complexity and cost to the transmitter architecture. Blind estimation techniques are attractive for avoiding the use of long training sequences. In this paper, we propose a blind frequency-independent I/Q imbalance compensation method based on the maximum likelihood (ML) estimation of the imbalance parameters of a transceiver. A closed-form joint probability density function (PDF) for the imbalanced I and Q signals is derived and validated. ML estimation is then used to estimate the imbalance parameters using the derived joint PDF of the output I and Q signals. Various figures of merit have been used to evaluate the efficacy of the proposed approach using extensive computer simulations and measurements. Additionally, the bit error rate curves show the effectiveness of the proposed method in the presence of the wireless channel and Additive White Gaussian Noise. Real-world experimental results show an image rejection of greater than 30 dB as compared to the uncompensated system. This method has also been found to be robust in the presence of practical system impairments, such as time and phase delay mismatches.

Power amplifier (PA) nonlinearity and in-phase and quadrature-phase (I/Q) imbalance are major concerns for wireless transmitters. In this paper, we present a new closed-form expression for the probability density function (PDF) of I and Q components in the presence of transmitter's impairments and propose a blind post-compensation approach for the mitigation of these impairments. These impairments include static PA nonlinearity and frequency-independent I/Q imbalance. The accuracy of the analytical PDF is evaluated using Kullback-Leibler divergence and Hellinger square distance. Simulation results show a reasonable correspondence between the derived PDF and non-parametric kernel density estimation-based PDF. After a closed-form PDF is obtained, higher order statistics-based method is used to estimate PA nonlinearity in the presence of I/Q impairments. Finally, a maximum-likelihood estimation of I/Q imbalance parameters is obtained using the analytical PDF. Simulation results show a normalized mean-squared error (NMSE) of around -40 dB and an adjacent channel power ratio of around -53 dBc, along with an error vector magnitude (EVM) of around 1%, for a 3-MHz local thermal equilibrium signal. Using laboratory measurements, an NMSE of around -35 dB and an EVM of 1.5% are achieved.

Reconfigurable and multi-standard RF front-ends for wireless communication and sensor networks have gained importance as building blocks for the Internet of Things. Simpler and highly-efficient transmitter architectures, which can transmit better quality signals with reduced impairments, are an important step in this direction. In this regard, mixer-less transmitter architecture, namely, the three-way amplitude modulator-based transmitter, avoids the use of imperfect mixers and frequency up-converters, and their resulting distortions, leading to an improved signal quality. In this work, an augmented memory polynomial-based model for the behavioral modeling of such mixer-less transmitter architecture is proposed. Extensive simulations and measurements have been carried out in order to validate the accuracy of the proposed modeling strategy. The performance of the proposed model is evaluated using normalized mean square error (NMSE) for long-term evolution (LTE) signals. NMSE for a LTE signal of 1.4 MHz bandwidth with 100,000 samples for digital combining and analog combining are recorded as −36.41 dB and −36.9 dB, respectively. Similarly, for a 5 MHz signal the proposed models achieves −31.93 dB and −32.08 dB NMSE using digital and analog combining, respectively. For further validation of the proposed model, amplitude-to-amplitude (AM-AM), amplitude-to-phase (AM-PM), and the spectral response of the modeled and measured data are plotted, reasonably meeting the desired modeling criteria.