Zain Ahmed Khan

Digital Predistortion for Joint Mitigation of I/Q Imbalance and MIMO Power Amplifier Distortion

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

Finding Structural Information About RF Power Amplifiers Using an Orthogonal Nonparametric Kernel Smoothing Estimator

2\times 2

Using Intrinsic Integer Periodicity to Decompose the Volterra Structure in Multi-Channel RF Transmitters

MIMO telecommunication setup.

Multitene design for third order MIMO volterra kernels

A nonparametric technique for modeling the behavior of power amplifiers (PAs) is presented. The proposed technique relies on the principles of density estimation using the kernel method and is suited for use in PA modeling. The proposed methodology transforms the input domain into an orthogonal memory domain. In this domain, nonparametric static functions are discovered using the kernel estimator. These orthogonal nonparametric functions can be fitted with any desired mathematical structure, thus facilitating its implementation. Furthermore, due to orthogonality, the nonparametric 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 PAs, therein yielding error performance similar to state-of-the-art parametric models. Furthermore, a parameter-efficient model structure with six coefficients was derived for a Doherty PA, therein significantly reducing the deployments computational complexity. Finally, the methodology can also be well exploited in digital linearization techniques.

A comparative analysis of the complexity/accuracy tradeoff in the mitigation of RF MIMO transmitter impairments

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.

Study of the Power Amplifier transfer function symmetry and its relation to dynamic effects

This paper proposes a technique for designing multitone signals that can separate the third order multiple input multiple output (MIMO) Volterra kernels. Multitone signals fed to a 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 output from the MIMO Volterra kernels does not overlap in the frequency domain, hence making it possible to separate these kernels from the output of the MIMO Volterra system. The proposed technique is applied to a 2×2 RF MIMO transmitter to determine its dominant hardware impairments. For input crosstalk, the proposed method reveals the dominant self and cross kernels whereas for output crosstalk, the proposed method reveals that only the self kernels are dominant.

Density estimation models for strong nonlinearities in RF power amplifiers

This paper presents a comparative analysis of the complexity accuracy tradeoff in state-of-the-art RF MIMO transmitter mitigation models. The complexity and accuracy of the candidate models depends on the basis functions considered in these models. Therefore, a brief description of the mitigation models is presented accompanied by derivations of the model complexities in terms of the number of FLOPs. Consequently, the complexity accuracy tradeoff in the candidate models is evaluated for a 2 × 2 RF MIMO transmitter. Furthermore, the model complexities are analyzed for increasing nonlinear orders and number of antennas.

Extraction of the Third-Order 3x3 MIMO Volterra Kernel Outputs Using Multitone Signals

Future wireless networks will employ unprecedentedly high number of transmitters along-with larger bandwidth signals. Therefore, complexity efficient Power Amplifier (PA) modelling methods with the ability to quantify memory effects are required. This paper presents a low complexity method to quantify memory effects by studying the symmetry in the PA transfer functions estimated with the density estimation method. It is shown that the symmetry helps in reducing the method complexity by more than two orders of magnitude. Further, it is verified that the symmetry can be used as a non-model based metric for quantifying memory effects in PAs.