Trellis Based Equalization

For low complexity equalization of sc fdma signals mmse linear filtering can be applied cf.

Trellis based equalization.

In this section we revisit mmse linear equalization for mimo sc fdma transmission. Such channels have a large channel memory length but only a small number of significant channel coefficients. 3 5 which will serve also as a preprocessing stage for the trellis based equalization scheme presented in section iv. Various approaches have been proposed in the.

In this paper trellis based equalization of sparse isi channels is revisited. For a reduction of the number of states of the trellis dia gram of mlse the principles of trellis based equalization and decision feedback equalization dfe might be com bined 2. 1995 the data are protected by a convolutional code and the receiver consists of two trellis based detectors one for the. Equalization based on linear filtering with decoding.

The viterbi algorithm is an effective solution to the problem of estimating the inputs to an fsm based on a noisy observation of the fsm output and it is used in a wide variety of applications beyond equalization of isi channels including error control decoding for convolutional and trellis codes and demodulation of continuous phase modulation. In the original system invented by douillard et al. Timum trellis based equalization with a reduced number of states might be adopted because it offers a very good trade off between performance and complexity. We study the turbo equalization approach to coded data transmission over channels with intersymbol interference.

Due to the large channel memory length the complexity of maximum likelihood detection e g by means of the viterbi. Trellis based soft output adaptive equalization techniques for tdma cellular systems abstract. The concatenation of an equalizer and a viterbi 1967 decoder is a powerful means for improving receiver performance in wireless communication systems. Sparse intersymbol interference isi channels are encountered in a variety of high data rate communication systems.

In this paper trellis based equalization of sparse isi channels is revisited. Due to the large channel memory length the complexity of maximum likelihood detection e. Through simulation and analytical results we show that the performance of the new approaches is similar to the trellis based receiver while providing large savings in computational complexity. In order to limit the required number of states of the viterbi algorithm va the cir might be shortened by linear prefiltering.

Principles and new results abstract. Phase ambiguity and shift ambiguity associated with trellis based blind equalization are discussed for coded systems.