Offset windowing for FIR fractional-sample delay

Cain, G.D.; Yardim, A.; Henry, P.

doi:10.1109/icassp.1995.480472

Cited by 18 publications

(8 citation statements)

References 4 publications

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“…The fractional delay operation can be realized by a FIR FDDF with fixed coefficients. A number of design techniques such as windowing method [20,21], and convex programming [22] are available in the literature. However, this approach may not be suitable for real-time applications because h[n 0 ,!…”

Section: Fractional Delay Digital Filtersmentioning

confidence: 99%

A Versatile Iterative Framework for the Reconstruction of Bandlimited Signals from Their Nonuniform Samples

Tsui

Chan

2010

J Sign Process Syst

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In this paper, we study a versatile iterative framework for the reconstruction of uniform samples from nonuniform samples of bandlimited signals. Assuming the input signal is slightly oversampled, we first show that its uniform and nonuniform samples in the frequency band of interest can be expressed as a system of linear equations using fractional delay digital filters. Then we develop an iterative framework, which enables the development and convergence analysis of efficient iterative reconstruction algorithms. In particular, we study the Richardson iteration in detail to illustrate how the reconstruction problem can be solved iteratively, and show that the iterative method can be efficiently implemented using Farrow-based variable digital filters with few general-purpose multipliers. Under the proposed framework, we also present a completed and systematic convergence analysis to determine the convergence conditions. Simulation results show that the iterative method converges more rapidly and closer to the true solution (i.e. the uniform samples) than conventional iterative methods using truncation of sinc series.

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Section: Fractional Delay Digital Filtersmentioning

confidence: 99%

A Versatile Iterative Framework for the Reconstruction of Bandlimited Signals from Their Nonuniform Samples

Tsui

Chan

2010

J Sign Process Syst

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“…In a comparison of windowing functions for fractional-delay filters the authors suggest to use the Hann window [4] as thereby the maximum error is minimal. We followed this recommendation in our fractional-delay filter implementation.…”

Section: πXmentioning

confidence: 99%

Deterministic Models of the Physical Layer through Signal Simulation

Maier¹,

Moser²,

Slomka³

2015

Proceedings of the Eighth EAI International Conference on Simulation Tools and Techniques

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Current wireless network simulators provide very detailed and deterministic models of the network protocol layers, whereas rather simple and stochastic models, based on the signal-to-noise ratio, are used for the simulation of the physical layer. Although this approach can be sufficient to study the behavior of different upper layer protocol variations, it prevents an easy alteration of the physical layer because a stochastic abstraction of the physical layer must be provided in advance. In particular, the simulation of distributed systems with physical layers that are designed to have several senders transmitting signals at the same time intentionally, is hardly possible with current approaches. A further problem of stochastic physical layer simulations is the fact that the radio channel's influence must also be carried out stochastically, which limits the advantage of accurate rayoptical channel models. We present a novel approach for the accurate simulation of the physical layer by utilizing existing software-defined radio implementations to create signals, to calculate interference and to decode signals. This technique enables us to simulate wireless networks holistically and, furthermore, we can fully exploit the possibilities of available ray-optical channel models.

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“…Based on this theory, the optimal filter coefficients are obtained by sampling a delayed sinc function. This ideal low-pass filter is however not realizable because of its non-causality and instability, and hence many studies have focused their attention on approximating the ideal filter by, for example, windowed sinc functions [15], [16], maximally-flat FIR approximation [17], [18], [19], [20], [21], all-pass approximation [22], [23], and minmax (Chebyshev) optimization [24].…”

Section: Introductionmentioning

confidence: 99%

$H^{\infty}$-Optimal Fractional Delay Filters

Nagahara

Yamämoto²

2013

IEEE Trans. Signal Process.

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Abstract-Fractional delay filters are digital filters to delay discrete-time signals by a fraction of the sampling period. Since the delay is fractional, the intersample behavior of the original analog signal becomes crucial. In contrast to the conventional designs based on the Shannon sampling theorem with the bandlimiting hypothesis, the present paper proposes a new approach based on the modern sampled-data H ∞ optimization that aims at restoring the intersample behavior beyond the Nyquist frequency. By using the lifting transform or continuous-time blocking the design problem is equivalently reduced to a discrete-time H

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Offset windowing for FIR fractional-sample delay

Cited by 18 publications

References 4 publications

A Versatile Iterative Framework for the Reconstruction of Bandlimited Signals from Their Nonuniform Samples

A Versatile Iterative Framework for the Reconstruction of Bandlimited Signals from Their Nonuniform Samples

Deterministic Models of the Physical Layer through Signal Simulation

$H^{\infty}$-Optimal Fractional Delay Filters

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