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 uses multitone signals to simplify the analysis of 3×3 multiple-input multiple-output (MIMO) Volterra systems by isolating the third-order kernel outputs from each other. Multitone signals fed to an MIMO Volterra system yield a spectrum that is a permutation of the sums of the input signal tones. This a priori knowledge is used to design multitone signals such that the third-order kernel outputs are isolated in the frequency domain. The signals are designed by deriving the conditions for the offset and spacing of the input frequency grids. The proposed technique is then validated for the six possible configurations of a 3 × 3 RF MIMO transmitter impaired by crosstalk effects. The proposed multitone signal design is used to extract the third-order kernel outputs, and their relative contributions are analyzed to determine the dominant crosstalk effects for each configuration.
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.Index Terms-Power amplifier, non-parametric model, kernel, basis functions, power amplifier linearization, Digital predistortion.
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