Behavioral Modeling of MIMO Nonlinear Systems With Multivariable Polynomials

Saffar, D.; Boulejfen, Noureddine; Ghannouchi, Fadhel M.; Gharsallah, Ali; Helaoui, Mohamed

doi:10.1109/tmtt.2011.2166977

Cited by 42 publications

(30 citation statements)

References 19 publications

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“…Table. I summarizes the basis functions of the candidate models [5,6,7] up to the third nonlinear order for a 2 × 2 RF MIMO transmitter, where m 1 denotes the diagonal memory and m 2 denotes the off diagonal memory.…”

Section: Theory and Backgroundmentioning

confidence: 99%

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

Khan

Händel

Isaksson

2017

2017 89th ARFTG Microwave Measurement Conference (ARFTG)

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Abstract-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.I. INTRODUCTION RF MIMO transmitters are the contemporary technology in wireless communication for achieving high date rate capacities. However, an energy efficient operation of RF MIMO transmitters results in hardware impairments that are more severe than SISO transmitter impairments. This severity is caused by additional distortion effects such as crosstalk between the MIMO transmission paths [1].Several mitigation models for SISO transmitter impairments have been proposed in literature [2]. Given an infinite order and complexity, these models can achieve a good error performance. However, at a given finite complexity, only part of the accuracy can be achieved [2]. Hence, it is necessary to analyze the complexity accuracy tradeoff in these models to get a complete picture of their effectiveness.The complexity of SISO RF transmitter mitigation models is often determined based on the number of parameters which can be determined form the nonlinear order and memory. However, this representation may not always be an appropriate measure for complexity since mitigation models for RF transmitters are implemented on digital signal processing (DSP) hardware [3]. The computational resources of such digital platforms are predominantly allocated for performing additions, subtractions and multiplications for which the number of floating point of operations (FLOPs) is an accurate measure and not the number of parameters. Hence, a complexity accuracy tradeoff analysis for SISO transmitter mitigation models in terms of the number of FLOPs has been presented in [3].Transitioning to RF MIMO transmitters, several mitigation models have also been proposed based on the MIMO Volterra series [4]. For example, the MIMO parallel Hammerstein (PH) model [5], the MIMO memory polynomial (MP) model [6] and the generalized (GMP) and extended generalized MIMO memory polynomial models (EGMP) [7]. These models incorporate higher complexity basis functions to account for the additional

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Section: Theory and Backgroundmentioning

confidence: 99%

“…For example, the MIMO parallel Hammerstein (PH) model [5], the MIMO memory polynomial (MP) model [6] and the generalized (GMP) and extended generalized MIMO memory polynomial models (EGMP) [7]. These models incorporate higher complexity basis functions to account for the additional…”

mentioning

confidence: 99%

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

Khan

Händel

Isaksson

2017

2017 89th ARFTG Microwave Measurement Conference (ARFTG)

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“…In particular, more computational resources are needed to estimate all the channel responses between the several transmitters and receivers, but no additional RF hardware is required. However, having several transmit chains on a single chip introduces another issue from the perspective of the digital canceller: the crosstalk between the transmitters, which occurs both before and after the power amplifiers (PAs) [22][23][24][25][26][27][28]. This phenomenon is illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear self-interference cancellation in MIMO full-duplex transceivers under crosstalk

Korpi

Anttila

Valkama

2017

J Wireless Com Network

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This paper presents a novel digital self-interference canceller for an inband multiple-input-multiple-output (MIMO) full-duplex radio. The signal model utilized by the canceller is capable of modeling the in-phase quadrature (IQ) imbalance, the nonlinearity of the transmitter power amplifier, and the crosstalk between the transmitters, thereby being the most comprehensive signal model presented thus far within the full-duplex literature. Furthermore, it is also shown to be valid for various different radio frequency (RF) cancellation solutions. In addition to this, a novel complexity reduction scheme for the digital canceller is also presented. It is based on the widely known principal component analysis, which is used to generate a transformation matrix for controlling the number of parameters in the canceller. Extensive waveform simulations are then carried out, and the obtained results confirm the high performance of the proposed digital canceller under various circuit imperfections. The complexity reduction scheme is also shown to be capable of removing up to 65% of the parameters in the digital canceller, thereby significantly reducing its computational requirements.

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“…In [9]- [13], reduced polynomial models have been proposed for modelling MIMO PAs. Saffar et al [14], addressed the joint mitigation of I/Q modulator impairment and PA nonlinearity in MIMO transmitters through an optimized memory polynomial model. However, all these published models suffer from the increasing numerical instability as the problem size increases.…”

Section: Introductionmentioning

confidence: 99%

Robust Modeling and Linearization of MIMO RF Power Amplifiers for 4G and 5G Applications

Zemzemi¹,

Lejnef²,

Boulejfen³

et al. 2018

ijacsa

Self Cite

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In this paper, a novel set of orthogonal crossover polynomials for the baseband modelling and linearization of MIMO RF Pas is presented. The proposed solution is applicable to WCDMA and LTE applications. The new modelling approach has considerably reduced the numerical instability problem associated with the conventional polynomial model identification. In order to validate the efficiency and the robustness of the proposed solution, a 2x2 MIMO LDMOS RF power amplifier has been measured modelled and linearized. A comparison with the conventional polynomial MIMO models showed clearly the superiority of the proposed solution in a fixed-point calculation environment such as DSP and FPGA boards. Keywords-MIMO transmitter; RF power amplifiers; orthogonal polynomials; nonlinear transmitters; digital predistortionI.The organization of the paper is as follows. In Section. 2, we introduce the reference crossover conventional polynomials

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Behavioral Modeling of MIMO Nonlinear Systems With Multivariable Polynomials

Cited by 42 publications

References 19 publications

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

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

Nonlinear self-interference cancellation in MIMO full-duplex transceivers under crosstalk

Robust Modeling and Linearization of MIMO RF Power Amplifiers for 4G and 5G Applications

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