A Set-Membership NLMS Algorithm with Time-Varying Error Bound

Galdino, Juraci Ferreira; Apolinario, J.A.; Campos, Marcello L. R. de

doi:10.1109/iscas.2006.1692576

Cited by 23 publications

(24 citation statements)

References 5 publications

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“…The SNR was set in 20 dB and the upper bound γ for the construction of the constraint sets related to the SM-PUAP was chosen to be γ = 2 σ 2 z . This value coincides with those suggested in the literature [24]. The simulations consisted of 1000 independent runs, and the average performance is computed.…”

Section: Simulation Results and Discussionsupporting

confidence: 86%

“…Setting a value too small for γ might lead to an empty set of feasible solutions, whereas setting a value too big might lead to inconsistent estimates. Some rules of the thumb have been suggested in the setmembership filtering literature in order to choose this upper bound properly [23], [24].…”

Section: B Set-membership Filteringmentioning

confidence: 99%

“…From the results presented in [14], one is able to infer that the update of RLS has a computational complexity of O N T M 2 L . Considering (24), the SM-PUAP has computation complexity at most equal to O N T Q 2 ML , the complexity of the classical affine projection algorithm [23]. Generally, the number of reuses Q M, so the affine projection algorithm is computationally less complex than RLS.…”

Section: E Computational Complexitymentioning

confidence: 99%

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Performance Evaluation of a Joint Precoding and Channel Prediction scheme for Multiuser MIMO OFDM Systems in Time Varying Wireless Channel

Leite¹,

Carvalho²,

Vieira³

2011

Journal of Communication and Information Systems

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Abstract-Multiple-input, multiple-output (MIMO) communications have attracted considerable attention in the last years. In particular, multiuser MIMO (MU MIMO) systems are able to offer higher link capacity of MIMO systems as long as channel state information (CSI) is available at the transmitter, so that the spatial properties of the channel can be exploited by precoding. However, the time varying nature of the channel may cause CSI to be outdated, thus degrading the overall performance of the system. Within this context, channel prediction can provide up-to-date channel CSI and reduce the performance loss. This paper presents a channel predictor based on the setmembership partial update affine projection (SM-PUAP) filtering as way to compensate the outdated CSI caused by the temporal variations of the communication channel in a multiuser MIMO OFDM (orthogonal frequency division multiplexing) system. A realistic standardized channel model is considered to evaluate the predictor and its influence on the broadcast channel of a multiuser MIMO scenario. The performance of the predictor is also compared to the well-known adaptive algorithm recursive least squares (RLS). Simulation results show that the SM-PUAP predictor has lower computational cost and superior performance when compared to the classical algorithm.Index Terms-Adaptive filters, broadcast channel, channel prediction, multiuser multiple-input multiple-output communications, orthogonal frequency division multiplexing, time-varying channels.

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Section: Simulation Results and Discussionsupporting

confidence: 86%

Section: B Set-membership Filteringmentioning

confidence: 99%

Section: E Computational Complexitymentioning

confidence: 99%

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Performance Evaluation of a Joint Precoding and Channel Prediction scheme for Multiuser MIMO OFDM Systems in Time Varying Wireless Channel

Leite¹,

Carvalho²,

Vieira³

2011

Journal of Communication and Information Systems

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“…The first inequality follows from the fact that we do not know exactly what will happen with w(k +1) 2 when an update occurs andẽ 2 (k) < n 2 (k) at the same time 1 , and therefore, it corresponds to a pessimistic bound. The second inequality is trivial and the subsequent equality follows from [29] by parameterizingγ asγ = τ σ 2 n , where τ ∈ R + (typically τ = 5) and by modeling the error e(k) as a zero-mean Gaussian random variable with variance σ 2 n . From (16), one can observe that the probability of obtaining w(k + 1) 2 > w(k) 2 is small.…”

Section: Corollary 2 When An Update Occurs (Ie F (E(k)γ )mentioning

confidence: 99%

On the robustness of set-membership adaptive filtering algorithms

Yazdanpanah

Lima

Diniz

2017

EURASIP J. Adv. Signal Process.

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In this paper, we address the robustness, in the sense of l 2 -stability, of the set-membership normalized least-meansquare (SM-NLMS) and the set-membership affine projection (SM-AP) algorithms. For the SM-NLMS algorithm, we demonstrate that it is robust regardless of the choice of its parameters and that the SM-NLMS enhances the parameter estimation in most of the iterations in which an update occurs, two advantages over the classical NLMS algorithm. Moreover, we also prove that if the noise bound is known, then we can set the SM-NLMS so that it never degrades the estimate. As for the SM-AP algorithm, we demonstrate that its robustness depends on a judicious choice of one of its parameters: the constraint vector (CV). We prove the existence of CVs satisfying the robustness condition, but practical choices remain unknown. We also demonstrate that both the SM-AP and SM-NLMS algorithms do not diverge, even when their parameters are selected naively, provided the additional noise is bounded. Numerical results that corroborate our analyses are presented.

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“…Moreover, a judicious choice of the error bound may not even assure optimal performance due to the nonstationarity of the underlying system. To overcome the error-bound estimation problem of the SM-NLMS algorithm [5], different solutions have been proposed in [6][7][8][9][10]. The error-bound estimation methods in [6][7][8][9] are not straightforward to apply to the SM-AP algorithm as they are application specific.…”

Section: Introductionmentioning

confidence: 99%

A set-membership affine projection algorithm with adaptive error bound

Bhotto

Antoniou

2009

2009 Canadian Conference on Electrical and Computer Engineering

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A new set-membership affine projection (SM-AP) algorithm for adaptive filtering applications is proposed. The new SM-AP algorithm eliminates the error-bound estimation problem of the conventional SM-AP algorithm. The poor tracking performance in nonstationary environments of the conventional SM-AP algorithm is also considered. A solution to this problem is proposed by incorporating a switching mechanism in the proposed SM-AP algorithm. The new SM-AP algorithm has better convergence efficiency and yields lower misadjustment than the conventional AP algorithm. On the other hand, with the switching mechanism it has better convergence efficiency and yields lower misadjustment than the conventional SM-AP algorithm in nonstationary environments.Index Terms-Adaptive filters, set-membership affine projection algorithms, adaptive error bound.

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A Set-Membership NLMS Algorithm with Time-Varying Error Bound

Cited by 23 publications

References 5 publications

Performance Evaluation of a Joint Precoding and Channel Prediction scheme for Multiuser MIMO OFDM Systems in Time Varying Wireless Channel

Performance Evaluation of a Joint Precoding and Channel Prediction scheme for Multiuser MIMO OFDM Systems in Time Varying Wireless Channel

On the robustness of set-membership adaptive filtering algorithms

A set-membership affine projection algorithm with adaptive error bound

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