A suboptimal approach to channel equalization based on the nearest neighbor rule

Savazzi, Pietro; Favalli, L.; Costamagna, E.; Mecocci, A.

doi:10.1109/49.737633

Cited by 27 publications

(18 citation statements)

References 24 publications

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“…In our simulations we assumed that the value of C was known. We compared our type-2 FL equalizer with the Patra and Mulgrew's type-1 FL equalizer [42] and Savazzi, et al's K-nearest neighbor (NN) equalizer [47]. In our simulations, we used a training sequence of length 121, a testing sequence of length 879, and additive Gaussian noise.…”

Section: Digital Communication Examplementioning

confidence: 99%

Uncertainty, fuzzy logic, and signal processing

2000

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In this paper we focus on model-based statistical signal processing and how some problems that are associated with it can be solved using fuzzy logic. We explain how uncertainty (which is prevalent in statistical signal processing applications) can be handled within the framework of fuzzy logic. Type-1 singleton and non-singleton fuzzy logic systems (FLSs) are reviewed. Type-2 FLSs, which are relatively new, and are very appropriate for signal processing problems, because they can handle linguistic and numerical uncertainties, are overviewed in some detail. The output of a type-2 FLS is a type-2 fuzzy set. Using a new operation called type-reduction, the type-2 set can be reduced to a type-1 set } the type-reduced set } which plays the role of a con"dence interval for linguistic uncertainties. No such result can be obtained for a type-1 FLS. We demonstrate, by means of examples, that a type-2 FLS can outperform a type-1 FLS for one-step prediction of a Mackey}Glass chaotic time series whose measurements are corrupted by additive noise, and equalization of a nonlinear time-varying channel.2000 Elsevier Science B.V. All rights reserved. ZusammenfassungIn diesem Artikel setzen wir den Schwerpunkt auf modellbasierte statistische Signalverarbeitung und zeigen MoK glichkeiten zur LoK sung von Problemen dieses Umfeldes mit Hilfe der Fuzzy Logik auf. Wir erlaK utern, wie Entscheidungsunsicherheit (die in saK mtlichen Anwendunger der statistischen Signalverarbeitung vorherrscht) im Rahmen der Fuzzy Logik behandelt werden kann. ZunaK chst werden Typ-1 Singleton und Nicht-Singleton Fuzzy Logik Systeme (FLS) besprochen. Typ-2 FLS, die relativ neu sind, werden etwas detaillierter behandelt. Sie eignen sich sehr zur LoK sung von Signalverarbeitungsproblemen, da sie linguistische und numerische Unsicherheit handhaben koK nnen. Die Ausgabe eines Typ-2 FLS stellt die Typ-2 Fuzzy-Menge dar. Mit Hilfe einer neuen, als Typ-Reduktion bezeichneten Operation, kann die Typ-2 Menge auf eine Typ-1 Menge } die Typ-reduzierte Menge } uK berfuK hrt werden. Sie entspricht einem Kon"denzintervall fuK r linguistische Unsicherheit. Kein derartiges Resultat kann fuK r eine Typ-1 FLS abgeleitet werden. Anhand von Beispielen zeigen wir, da{ eine Typ-2 FLS eiher Typ-1 FLS zum einen als Einschritt-PraK diktion uK berlegen sein kann, wenn, sie auf eine chaotische Mackey}Glass Zeitreihe angwandt wird, deren Me{werte durch additives Rauschen gestoK rt sind oder wenn sie zum anderen bei der Entzerrung eines nichtlinearen zeitvarianten Kanals angewandt wird.2000 Elsevier Science B.V. All rights reserved. Re2 sume2Dans cet article, nous nous concentrons sur le traitement statisque de signaux a`base de mode`les et sur la fac7 on dont certains proble`mes qui lui sont associeH s peuvent e( tre reH solus en utilisant de la logique #oue. l'incertitude (qui preH vaut en traitement statistique des signaux) peut e( tre manipuleH oe dans le cadre de la logique #oue. Nous passons en revue des systeH mes a`logique #oue (SLF) a`singletones de type 1 et sans s...

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Section: Digital Communication Examplementioning

confidence: 99%

Uncertainty, fuzzy logic, and signal processing

2000

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“…ANN using nonlinear decision boundaries [21] via the multilayer perceptron has been considered as a promising alternative for combating impairments in wireless communications [22], [23]. In ANN, complex mapping between input and output spaces could be achieved, however, at the cost of complexity [14,24].…”

Section: Ann and Ivstf Nonlinear Equalizersmentioning

confidence: 99%

Reduced-Complexity Artificial Neural Network Equalization for Ultra-High-Spectral-Efficient Optical Fast-OFDM Signals

Jarajreh¹

2019

Applied Sciences

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Digital-based artificial neural network (ANN) machine learning is harnessed to reduce fiber nonlinearities, for the first time in ultra-spectrally-efficient optical fast orthogonal frequency division multiplexed (Fast-OFDM) signals. The proposed ANN design is of low computational load and is compared to the benchmark inverse Volterra-series transfer function (IVSTF)-based nonlinearity compensator. The two aforementioned schemes are compared for long-haul single-mode-fiber-based links at 9.69 Gb/s direct-detected optical Fast-OFDM signals. It is shown that an 80 km extension in transmission-reach is feasible when using ANN compared to IVSTF. This occurs because ANN can tackle stochastic nonlinear impairments, such as parametric noise amplification. Using ANN, the dynamic parameters requirements of the sub-ranging quantizers can also be relaxed compared to linear equalization, such as the reduction of the optimum clipping ratio and quantization bits by 2 dB and 2-bits, respectively, and by 2 dB and 2 bits when compared to the IVTSF equalizer.

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“…The NN rule is described in several places in the literature [8][9][10]. Assume there are M pattern classes, numbered 1,2,…M.…”

Section: A Nn Rulementioning

confidence: 99%

Composite Pulse-Multipath Channel Estimation for IR-UWB Communication System

Liu

Zhang

2009

2009 5th International Conference on Wireless Communications, Networking and Mobile Computing

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In this paper, we develop a composite pulse-multipath channel estimation approach for impulse radio-ultra wideband (IR-UWB) system. The approach is realized by means of the nearest neighbor (NN) estimation algorithm. This reconstructed signal is subsequently used as a reference template in a correlator-based detector. The bit error rate (BER) performance of the proposed approach is analyzed and compared to that of traditional correlator-based detector. Extensive simulations show that for different propagation scenarios and transfer rates, detectors based on NN composite pulse-multipath channel estimation outperform traditional correlator-based detector.

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A suboptimal approach to channel equalization based on the nearest neighbor rule

Cited by 27 publications

References 24 publications

Uncertainty, fuzzy logic, and signal processing

Uncertainty, fuzzy logic, and signal processing

Reduced-Complexity Artificial Neural Network Equalization for Ultra-High-Spectral-Efficient Optical Fast-OFDM Signals

Composite Pulse-Multipath Channel Estimation for IR-UWB Communication System

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