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We target M-ary data sequence estimation over time-variant frequency selective fading channels. Recently, we proposed a low complexity breadth first tree detector, termed improved M-algorithm (IMA). Unlike the M-algorithm (MA), it takes the whole energy of the received symbol of the current step into account when choosing survivors. Unknown future symbols overlap with postcursors of the current symbol and are modelled as additive Gaussian noise in the metric. Thus, unlike the standard MA, IMA works well without an energy compacting Front End Prefilter (FEP) even in frequency-selective channels, whereas a FEP is crucial for ordinary reduced state sequence estimators such as the Delayed Decision Feedback Sequence Estimator (DDFSE) and Reduced State Sequence Estimator (RSSE). However, although not explicitly needed, we show that the complexity of IMA can be reduced even more applying a FEP, because the first channel tap has increased energy, and the effective channel would be even shorter, so that the influence of future symbols on the postcursors is smaller, enabling the tree detector to chose the paths through the tree more precisely. We propose to make use of the cepstrum to compute the FEP via a minimum phase target impulse response. We use the GSM/EDGE modulation format here, in order to enable other researchers to compare their results. Simulation results indicate that for the given application, IMA is superior to RSSE with similar complexity.

The technique presented here improves a previously proposed [1] Iterative Channel Data Estimation (ICDE) technique in M-ary data transmission over time-variant frequency selective channels by using a proportionate sample adaptive filter for channel tracking on a Per-Survivor Processing (PSP) basis. Henceforth, we call the approach using proportionate algorithm P-ICDE. The data detector is a simple M-algorithm with extended metric calculation that minimizes the expectation of the Euclidian distance between received signal and convolution of channel and data hypotheses. For low velocities, the technique can work with an initial channel estimate as data detector only, simply as Malgorithm with extended metric. Known techniques, such as Delayed Decision Feedback Sequence Estimation (DDFSE), optionally with Reduced State Sequence Estimation (RSSE) or Adaptive State Allocation (ASA), for comparison, reduce the complexity of the Viterbi detector by shortening of the channel impulse response or applying decision feedback on the trellis. In order to keep the performance loss low, a minimum-phase overall impulse response, achieved by an allpass approximating Front-End Prefilter (FEP), is crucial for these techniques. Our detector, however, works without FEP, which, if block adapted, would lead to severe degradation in fast fading. The detector can work with 3-5 states only, depending on the quality of the channel estimates, the multipath profile of the channel and the symbol constellation. We propose a receiver with fixed parameterization.

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In this paper, a prefiltering approach is taken in order to suppress co-channel interference signals in a frequency selective fading environment. A complex time-variant prefilter results. It rotates the signal space to place the interferer on the axis orthogonal to the detection axis. After the equalizer, a projection on the detection axis is done and a maximum likelihood sequence estimation (MLSE) is performed. Up to 3 totally asynchronous users are considered. The simulation results indicate that the suggested technique outperforms a conventional maximum likelihood sequence estimation (MLSE) for the bit error rate (BER) region of interest in practical systems. The technique works with signal spaces of the desired signals that have their signal points on an straight line in the signal space. With Laurent's decomposition, also GMSK signals can he treated. This approach of practical interest is taken here. As an application, the interference canceller is applied to a receiver following the Global System for Mobile Communications (GSM) standard.