Performance comparison of TEQ design techniques for FDM ADSL

Warke, N.; Redfern, A.J.; Sestok, Charles K.; Ali, Muhammad Asım

doi:10.1109/acssc.2002.1197208

Cited by 1 publication

(2 citation statements)

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“…The first method that sought to maximize bit rate was the Maximum Geometric Signal-to-Noise Ratio (MGSNR) method proposed by Al-Dhahir and Cioffi, and was based on maximizing the geometric mean of the subchannel SNRs [7]. Equation (10) can be expressed as…”

Section: B Geometric Snrmentioning

confidence: 99%

“…Various methods which include TEQ spectral flatness in the design criteria have been proposed [8][9][10], and these have been shown to result in improved bit rate performance. In the MSSNR context, these methods can be said to trade SSNR for TEQ spectral flatness and are able to achieve a local bit rate maximum over the range of design parameters.…”

Section: Introductionmentioning

confidence: 99%

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Channel Spectral Flattening in Time Domain Equalizer Design for OFDM Systems

Chen

Chin

2009

2009 IEEE International Conference on Communications

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Time domain equalization (TEQ) methods based on the maximum shortening signal-to-noise ratio (MSSNR) criterion is one of the most commonly used criterion for shortening impulse responses as it is computationally efficient and simple. However, the MSSNR method tends to design a TEQ with a bandpass-like frequency response, resulting in a spectrally uneven effective channel response. As as result, bitloading have to be performed to improve the bit rate of the system. Additionally, when residual intersymbol interference (ISI) is low compared to noise power, the spectral shape of the effective channel does not have much impact on the bit rate. However, the negative effect of the channel spectral unevenness on achievable bit rate increases as the noise power decreases. In this paper, a design method is proposed to maximize effective channel spectral flatness to increase the bit rate of the system.

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Section: B Geometric Snrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%