Abstract: A non-coherent receiver for digitally modulated signals, linearly or not, possibly combined with channel coding, is described. In the case of M-PSK, or M-QAM modulations, the received signal is demodulated and filtered by a filter matched to the transmitted pulse. In the case of linear modulations in presence of intersymbol interference, and non-linear M-CPM modulations, the reception filter is of the whitened matched type. The signal is filtered and sampled and the samples are accumulated in a relevant memory containing N-1 samples preceding the current one. These samples are processed by a Viterbi processor estimating the sequence of transmitted symbols according to a maximum likelihood criteria. A first embodiment calculates suitable trellis branch metrics using an implicit estimation of the carrier phase in PSP mode (Per- Survivor-Processing).

Abstract: It is described a non-coherent receiver for digital modulated radio signals, linear or not, possibly affected by channel coding. In the case of M-PSK, or M-QAM modulations, possibly combined with a channel coding, the signal received is demodulated and filtered by a filter matched to the pulse transmitted. In the case of linear modulations in presence of ISI, and of non-linear M-CPM modulations, the reception filter is a matched and whitened one. The signal is filtered and sampled and the samples are accumulated in a relevant phase reconstruction memory containing N−1 samples preceding the actual one. Samples are processed making use of a Viterbi processor estimating the sequence of symbols transmitted according to maximum likelihood. The first embodiment calculates the branch metrics using an estimation of the carrier phase in PSP mode (Per-Survivor-Processing). This improves the performance of the receiver.

Abstract: A method for selecting the best survivor from a plurality of surviving possible distal data symbols creates a channel estimate for each of the survivors independent of the others. The likelihood of each survivor is then evaluated, whereupon the most likely survivor is selected. The likelihood of each survivor is computed based only on its own channel estimate. A data sequence estimation system includes a memory for storing a plurality of "surviving" sequences. For each stored survivor, the system includes a channel estimator and a metrics computer, which calculates a measure of the likelihood of the survivor as a function of the survivor itself, the observed input, and the parameters of the associated channel estimator. The system also includes a processor that accumulates the metric and selects a best survivor as a function of a computed maximum likelihood.