On the baseband representation of a bandpass nonlinearity

Zhou, G.T.; Qian, Hua; Ding, Lei; Raich, Raviv

doi:10.1109/tsp.2005.850383

Cited by 67 publications

(37 citation statements)

References 12 publications

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“…Herein, we only consider in-band distortion caused by nonlinear HPAs implemented at the relay nodes. In particular, the memoryless polynomial model [9], [10] is used here to describe the characteristics of nonlinear HPA. In a general way, the input-output relationship of the nonlinear HPA can be expressed as…”

Section: System Modelmentioning

confidence: 99%

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Two-way CSI-assisted AF relaying with HPA nonlinearity

Aissay

Alouiniz

2015

2015 IEEE International Conference on Communications (ICC)

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In this paper, we investigate half-duplex two-way dual-hop channel state information (CSI)-assisted amplify-andforward (AF) relaying in the presence of high-power amplifier (HPA) nonlinearity at relays. The expression for the end-toend signal-to-noise ratio (SNR) is derived as per the modified system model by taking into account the interference caused by relaying scheme and HPA nonlinearity. The system performance of the considered relaying network is evaluated in terms of average symbol error probability (SEP) in Nakagami-m fading channels, by making use of the moment-generating function (MGF) approach. Numerical results are provided and show the effects of several parameters, such as quadrature amplitude modulation (QAM) order, number of relays, HPA parameters, and Nakagami parameter, on performance.

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Section: System Modelmentioning

confidence: 99%

“…Note only odd-order product terms in (1) are considered due to the fact that the signals generated from the even-order terms are outside the frequency band of interest [10]. For simplicity of the analysis, the HPA coefficients are assumed to be perfectly known.…”

Section: System Modelmentioning

confidence: 99%

Two-way CSI-assisted AF relaying with HPA nonlinearity

Aissay

Alouiniz

2015

2015 IEEE International Conference on Communications (ICC)

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“…In reality, h is a smooth function which allows an approximation around the origin by a polynomial of degree P . Although the PA is a real-valued system which will introduce even as well as odd order nonlinear distortions, due to zonal filtering, in the baseband domain only the influence of the odd order terms remains [4]. Consequently, with u k ∈ C and This work has been funded by the NFN SISE (National Research Network "Signal and Information Processing in Science and Engineering").…”

Section: Simplified Wiener Modelmentioning

confidence: 99%

Stability analysis of an adaptive Wiener structure

Dallinger

Rupp

2010

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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In the context of digital pre-distortion, a typical requirement is to identify the power amplifier with stringently low computational complexity. Accordingly, we consider a simple gradient method which is used to adaptively fit a simplified Wiener model, i.e., a cascade of a linear filter followed by a memoryless nonlinearity, to a dispersive and saturating reference system which represents the power amplifier. For adaptation, the gradient method only relies on the difference between the output of the reference system and the Wiener model. We show that such a structure can be formulated as a proportionate normalised least mean squares (PNLMS) algorithm. As a consequence, conditions for stability in the mean square sense can be deduced. Although not proven in a strict sense, simulation results allow to conjecture robustness.

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“…Depending on the overall waveform structure and range of frequencies considered, these can also be divided into in-band and out-of-band distortion components. Typically, in-band distortion products result in an increased effective noise floor (from any individual waveform point of view), while out-of-band components introduce crosstalk and interference between different signal bands [40][41][42][43][44][45][46][47][48][49][50].…”

Section: Nonlinearitiesmentioning

confidence: 99%