Optimization of transmitter and receiver filters for OQAM-OFDM systems using nonlinear programming

Hsiao-Hwa Chen, Xiao Dong Cai

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper proposes a family of optimized transmitter and receiver FIR filters for orthogonal frequency division multiplex (OFDM) systems with offset QAM modulation using nonlinear-programming. Two objective functions in the frequency domain (considering both OFDM orthogonal condition and Nyquist condition), least square error (LSE) and minimizing maximal spectral side lobe (Mini-max), are used. The nonlinear programming is implemented with a modified sequential quadratic programming (SQP) algorithm, which guarantees a super-linear convergence. Resultant optimized FIR filters are given with their coefficients and spectra.

Original languageEnglish
Pages (from-to)1680-1687
Number of pages8
JournalIEICE Transactions on Communications
VolumeE80-B
Issue number11
Publication statusPublished - 1997

Fingerprint

FIR filters
Nonlinear programming
Transmitters
Quadratic programming
Quadrature amplitude modulation
Modulation

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

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Optimization of transmitter and receiver filters for OQAM-OFDM systems using nonlinear programming. / Chen, Hsiao-Hwa; Cai, Xiao Dong.

In: IEICE Transactions on Communications, Vol. E80-B, No. 11, 1997, p. 1680-1687.

Research output: Contribution to journalArticle

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AU - Cai, Xiao Dong

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AB - This paper proposes a family of optimized transmitter and receiver FIR filters for orthogonal frequency division multiplex (OFDM) systems with offset QAM modulation using nonlinear-programming. Two objective functions in the frequency domain (considering both OFDM orthogonal condition and Nyquist condition), least square error (LSE) and minimizing maximal spectral side lobe (Mini-max), are used. The nonlinear programming is implemented with a modified sequential quadratic programming (SQP) algorithm, which guarantees a super-linear convergence. Resultant optimized FIR filters are given with their coefficients and spectra.

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