Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
DSL: Simulation Techniques and Standards Development for Digital Subscriber Lines
DSL: Simulation Techniques and Standards Development for Digital Subscriber Lines
Multirate Digital Signal Processing: Multirate Systems, Filter Banks, Wavelets
Multirate Digital Signal Processing: Multirate Systems, Filter Banks, Wavelets
An efficient block adaptive decision feedback equalizer implemented in the frequency domain
IEEE Transactions on Signal Processing
A low-complexity adaptive echo canceller for xDSL applications
IEEE Transactions on Signal Processing
Fast computation of channel-estimate based equalizers in packetdata transmission
IEEE Transactions on Signal Processing
Efficient decision feedback equalization for sparse wireless channels
IEEE Transactions on Wireless Communications
Reduced-complexity equalization techniques for broadband wireless channels
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Reduced complexity decision feedback equalization for digital subscriber loops
IEEE Journal on Selected Areas in Communications
Pole-zero decision feedback equalization with a rapidly converging adaptive IIR algorithm
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.08 |
The decision feedback equalizer (DFE) is widely used in communication systems combating intersymbol interference effect. In wireline communications, the channel response is usually long and the computational complexity of the DFE is often high. This is particularly true when the precoding is applied in which the feedback signal value becomes continuous rather than discrete. In this paper, an interpolated DFE (IDFE) structure is proposed to solve the problem. The proposed IDFE consists of a finite-impulse-response (FIR) feedforward filter and an interpolated FIR feedback filter. Thanks to the interpolation operation, the computational complexity of the DFE can be greatly reduced. The least-mean-squared (LMS) algorithm is applied to train the tap weights yielding an adaptive IDFE. Closed-form expressions for optimal filter coefficients, mean squared errors, and signal-to-noise ratios are derived. The convergence behavior of the adaptive IDFE is also analyzed. Simulation results show that while the computational complexity is significantly reduced, the performance of the proposed IDFE is similar to the conventional DFE. The computational saving can be as high as 76% for a high-speed digital subscriber line application.