On the Optimal Communication Spanning Tree Problem

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MMSE–Based Iterative Equalization with Soft Feedback for QAM Transmission over . . .

In this paper, an equalization algorithm based on soft–decision feedback, designed for transmission with square QAM constellations is introduced. The algorithm employs a minimum mean–squared error (MMSE) filter in each iteration in order to refine the data estimates. The rule for generating soft decisions is adapted continuously to the current state of the algorithm. It is shown that the algorithm is especially well suited for transmission over certain sparse frequency–selective fading channels where optimum schemes are by far too complex. A minimum mean–squared error decision–feedback equalizer (MMSE–DFE) is clearly outperformed for this application

Iterative Equalization with Soft Feedback with a Subsequent Stage Utilizing Hopfield Networks for Error Search and Correction

In this paper, a second stage for algorithms applying iterative soft decision interference cancellation (ISDIC) [1], [2], [3], [4] for channel equalization is proposed performing error search and correction. Analysis by simulations shows that a matched filter (MF) ISDIC with subsequent second stage can outperform a more complex minimum mean--squared error (MMSE) ISDIC. Furthermore, the latter can be improved by the proposed second stage by up to 2 dB. It is shown that the ISDIC scheme with following second stage can reach the matched filter bound up to a fraction of a dB for all analyzed channels and 4QAM transmission and up to 1 dB for 16QAM transmission. In [1] it has been reported that the MF ISDIC performs very well for highly dispersive channels, e.g. with 60 symbol--spaced paths, but for channels of moderate dispersion an error floor occurs. Utilizing performance bounds for delayed decision--feedback sequence estimation (DDFSE) we show that now already for channels of moderate length, e.g. 20 symbol--spaced taps, even the low--complexity MF ISDIC with the proposed subsequent second stage outperforms a DDFSE approach with about 10 states.

Matched-Filter- and MMSE-Based Iterative Equalization with Soft Feedback for QPSK Transmission

In this paper, two novel equalization algorithms applying soft-decision feedback, designed for quaternary phase-shift keying (QPSK) transmission are introduced. The first one uses a matched filter (MF) as a front end and is derived from [1] where it was originally developed for binary transmission. The second one is an improved version of the first, employing a minimum mean-squared error (MMSE) filter in each iteration in order to refine the data estimates. The rule for generating soft decisions is adapted continuously to the current state of the algorithm. In most cases, standard DFE methods are clearly outperformed. In contrast to the algorithm of [1], a performance close to that of maximum-likelihood sequence estimation can be obtained for the MMSE-based scheme for a broad class of channels

Decision-feedback equalization for CDMA downlink

A well-known receiver strategy for a linearly modulated signal transmitted over a frequency-selective channel is channel equalization. Recently it was proposed to employ a minimum mean-squared error (MMSE) channel equalizer for the downlink of CDMA. In this paper, we introduce a new receiver concept using MMSE channel equalization as a first stage and MMSE decision-feedback equalization (DFE) utilizing soft feedback from the decoding unit as a second stage. Both schemes are compared for the downlink of CDMA. It turns out, that after channel decoding we gain about 1 dB compared to conventional MMSE channel equalization