Recent Advances in FIR Approximation by IIR Digital Filters

Kwan, Hon Keung; Jiang, Aimin

doi:10.1109/icccas.2006.284615

Cited by 12 publications

(14 citation statements)

References 9 publications

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“…It is proved that for an arbitrary ( ) ( ) k X z which minimizes (17) in the least-squares sense, the model is always stable [6]. In summary, a SISO IIR structure can be obtained from ( ) / ( ) P z Q z through (11), (12), (16) and (17).…”

Section: B Determination Of Denominatormentioning

confidence: 97%

“…SISO (single-input-single-output) Least-Squares (LS) [4] is shown to be accurate and effective in approximation of FIR type responses with IIR structures, comparing to other algorithms [6]. It exploits the advantages of simple calculation, and avoids state-space realization, eigenvalue computation or initial pole assignment, and thus shuns from the problem of the numerical-sensitive calculation.…”

Section: Introductionmentioning

confidence: 98%

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Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ

Liu

2009

2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications

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Efficient implementation of FIR (finite-impulseresponse) equalizers for wireless channels has attracted much attention these days as equalizations can improve the link performance in hostile mobile radio environment by compensating for inter-symbol interference created by multipath within time dispersive channels. Meanwhile, the MIMO (multiple-input-multiple-output) technique becomes a trend in wireless channel design. On the other hand, we have observed a Least-Squares rational function system identification algorithm, which approximates FIR impulse response with IIR (infiniteimpulse-response) structures effectively. In this paper, we exploit the approximation algorithm and extend the algorithm for a MIMO response approximation which can generate a hardwareefficient MIMO IIR structure for FIR type time domain equalizers in the wireless system. We demonstrate the efficiency and accuracy of our method with MIMO modeling examples.

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Section: B Determination Of Denominatormentioning

confidence: 97%

Section: Introductionmentioning

confidence: 98%

Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ

Liu

2009

2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications

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“…It involves overdetermined equations and digital filtering operations without state-space realization, eigenvalue computation or initial pole assignment. Therefore, the algorithm avoids numericalsensitive calculation and is superior to other IIR approximation algorithms, in terms of both accuracy and speed [8].…”

Section: Introductionmentioning

confidence: 99%

Efficient linear macromodeling via least-squares response approximation

Lei¹,

Kwan²,

Wong³

2008

2008 IEEE International Symposium on Circuits and Systems (ISCAS)

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Abstract-We present a least-squares (LS) algorithm for rational function macromodeling of port-to-port responses with discrete-time sampled data. The core routine involves over-determined equations and filtering operation, and avoids numerical-sensitive calculation and initial pole assignment. We demonstrate the fast computation and excellent accuracy and robustness, even with noisy data, in stable response approximation.

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“…On the other hand, in digital filter design, recent research has been drawn to the infinite-impulse-response (IIR) approximation of finiteimpulse-response (FIR) filters, e.g., [6]- [11]. This is motivated by 1) IIR design methodology through matching to a prescribed FIR filter prototype and 2) possible hardware savings due to the fewer multipliers in IIR structures.…”

Section: Introductionmentioning

confidence: 99%

“…However, in the approximation exercise, stringent constraints like accurate magnitude and phase matching, stability, and low algorithmic complexity have to be satisfied. Owing to the highly nonlinear nature of the problem, so far there is no optimal algorithm in terms of accuracy and computational cost [11].…”

Section: Introductionmentioning

confidence: 99%

IIR Approximation of FIR Filters Via Discrete-Time Vector Fitting

Wong

Lei

2008

IEEE Trans. Signal Process.

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We present a novel technique for approximating finite-impulse-response (FIR) filters with infinite-impulse-response (IIR) structures through extending the vector fitting (VF) algorithm, used extensively for continuous-time frequency-domain rational approximation, to its discrete-time counterpart called VFz. VFz directly computes the candidate filter poles and iteratively relocates them for progressively better approximation. Each VFz iteration consists of the solutions of an overdetermined linear equation and an eigenvalue problem, with real-domain arithmetic to accommodate complex poles. Pole flipping and maximum pole radius constraint guarantee stability and robustness against finite-precision implementation. Comparison against existing algorithms confirms that VFz generally exhibits fast convergence and produces highly accurate IIR approximants.

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Recent Advances in FIR Approximation by IIR Digital Filters

Cited by 12 publications

References 9 publications

Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ

Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ

Efficient linear macromodeling via least-squares response approximation

IIR Approximation of FIR Filters Via Discrete-Time Vector Fitting

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