Comparison of neural network adaptive predistortion techniques for satellite down links

Langlet, F.; Abdulkader, H.; Roviras, Daniel; Mallet, Alain; Castanié, F.

doi:10.1109/ijcnn.2001.939111

Cited by 16 publications

(14 citation statements)

References 3 publications

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“…They have been successfully used in many applications related to digital communication such as coding and decoding [7], equalization [2], etc. In [1] and [6], NN have been successfully used to identify and predistort high power amplifiers. In [9], a NN is implemented on an ASIC for use in on-board regenerative satellites [9].…”

Section: Neural Network Structurementioning

confidence: 99%

Mitigation of Multipath Influence on Tracking Errors in LEO Navigation Applications

Abdulkader

Roviras²,

Chaggara³

et al. 2006

The 2006 IEEE International Joint Conference on Neural Network Proceedings

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This paper presents a solution to enhance the navigation of LEO satellites by mitigating the multipath influence. In several cases, Navigation of LEO satellites needs a very high accuracy in positioning, while GPS receivers suffer from leak of accuracy. As multipath is a major source of inaccuracy, we propose to use a neural networks (NN) technique in the range domain in order to estimate and compensate for Phase and code (delay) tracking errors. In this paper we present a rich discussion of the NN application in the range domain and the major factors influencing its performance.

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Section: Neural Network Structurementioning

confidence: 99%

Mitigation of Multipath Influence on Tracking Errors in LEO Navigation Applications

Abdulkader

Roviras²,

Chaggara³

et al. 2006

The 2006 IEEE International Joint Conference on Neural Network Proceedings

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“…In the past, tuning for specific performance metrics such as IQ mismatch have been developed [6][7][8][9]. These are not suitable for concurrently tuning and trading off multiple device specifications.…”

Section: Bist For Computing Multiple Performance Metrics Of Rf Circuitsmentioning

confidence: 99%

BIST-assisted power aware self healing RF circuits

Devarakond

Natarajan

Sen

et al. 2009

2009 IEEE 15th International Mixed-Signals, Sensors, and Systems Test Workshop

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In this paper, a novel methodology for post manufacture tuning of RF circuits is presented. The procedure uses an iterative test-tune-test algorithm that applies a compact alternative test to the DUT and modulates circuit level tuning knobs (bias/supply values) based on the DUT specification values predicted from the test. The test procedure is repeated until convergence to the desired spec values is achieved with minimal impact on circuit power consumption. A key benefit of this approach is that tuning of multiple specifications can be performed concurrently due to the use of the alternative test methodology allowing upto 10X savings in test/tuning time.

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“…We know that the main features of artificial neural networks (ANNs) are their learning and generalization capabilities, which have been shown to be effective for the HPA predistortion schemes, as described in [2][3][4][5]. However, those approaches have slow convergence rates that are easily trapped into local minima; thus optimum compensation results were difficult to obtain.…”

Section: Introductionmentioning

confidence: 98%

An adaptive predistorter using modified neural networks combined with a fuzzy controller for nonlinear power amplifiers

Deng

2003

Int J RF and Microwave Comp Aid Eng

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In digital radio systems, high data transmission rates require the use of spectrally efficient linear modulation techniques; however, these techniques are generally sensitive to nonlinearity caused by the high-power amplifier (HPA) employed in transmitter systems. The nonlinearity of HPA is potentially responsible for spectral spreading, adjacent channel interference (ACI), and degradation of bit-error rates (BERs). This article proposes an adaptive predistortion scheme to compensate for the HPA's nonlinearity by combining adaptive structure-varying neural networks and a fuzzy controller. Simulations show that this predistortion scheme can very effectively prevent the warping of the signal constellations, thus reducing the system's BER and learning time.

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Comparison of neural network adaptive predistortion techniques for satellite down links

Cited by 16 publications

References 3 publications

Mitigation of Multipath Influence on Tracking Errors in LEO Navigation Applications

Mitigation of Multipath Influence on Tracking Errors in LEO Navigation Applications

BIST-assisted power aware self healing RF circuits

An adaptive predistorter using modified neural networks combined with a fuzzy controller for nonlinear power amplifiers

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