Abstract: A semi-single frequency network (SFN) concept is presented. According to the SFN concept, the same data signal is transmitted from multiple base stations to a mobile terminal simultaneously on the same frequency band. Accordingly, the transmitted signals are combined in the radio channel and the mobile terminal experiences the transmitted signals as one signal propagated through a multipath channel. Additionally, each base station transmits a base station specific pilot signal. The mobile terminal carries out a channel estimation procedure for each received pilot signal and combines the channel estimates to obtain information how to equalize the received data signal. Then, the mobile terminal calculates equalization weights from the combined channel estimates and equalizes the received data signal.

Abstract: An apparatus, including a detection unit configured to perform a non-linear detection on a receive signal, a first estimator configured to estimate a first quality measure based on the receive signal, and a second estimator configured to estimate a second quality measure dependent on the first quality measure and a performance measure of the detection unit is provided.

Abstract: The invention concerns methods and apparatus for performing channel equalization in a direct-sequence spread spectrum communications system. The methods and apparatus of the present invention are particularly applicable in situations where communication occurs over a channel experiencing multipath interference associated with paths having significantly different lengths. The impulse response-delay profile of such a channel is typically sparse, that is, dominated by a relatively few and widely spaced taps or clusters of closely spaced taps. In one aspect, equalization filter coefficients are calculated based on a channel estimate derived from a single cluster of closely-spaced channel taps collectively having the greatest percentage of energy as indicated by the impulse response-delay profile.

Abstract: A receiver includes a channel estimator for estimating a channel impulse response of a radio channel; an equalizer for generating linear minimum mean-square error equalizer coefficients and providing an equalized signal to a correlator; an estimating unit for forming an initial estimate of received data elements on the basis of an equalized signal; and a processing unit. The processing unit is configured to calculate a scaling factor by taking an inverse value, subtracted from a value of one, of a conjugate transpose of a linear minimum mean-square error equalizer coefficient vector multiplied by a channel impulse response vector, and to use the scaling factor for determining reliability of the initial estimate of the received data elements.

Abstract: A method is disclosed to obtain M final symbol decisions for signals received through N receive antennas that were transmitted in M parallel data layers, using a same spreading code from M transmit antennas. The method includes space-time equalizing the N received signals to generate M output signals from which at least inter-symbol interference is substantially removed and inter-layer interference is suppressed; despreading each of the M output signals for generating M soft symbol estimates; and processing the M soft symbol estimates to derive M final symbol decisions that are made in consideration of modeled residual inter-layer interference present in the space-time equalized M output signals. Processing includes operating a signal-plus-residual-interference (SPRI) detector that operates in accordance with a maximum likelihood (ML) technique, while space-time equalizing employs a linear minimum mean-square error (LMMSE) criterion.

Abstract: A method is disclosed to obtain M final symbol decisions for signals received through N receive antennas that were transmitted in M parallel data layers, using a same spreading code from M transmit antennas. The method includes space-time equalizing the N received signals to generate M output signals from which at least inter-symbol interference is substantially removed and inter-layer interference is suppressed; despreading each of the M output signals for generating M soft symbol estimates; and processing the M soft symbol estimates to derive M final symbol decisions that are made in consideration of modeled residual inter-layer interference present in the space-time equalized M output signals. Processing includes operating a signal-plus-residual-interference (SPRI) detector that operates in accordance with a maximum likelihood (ML) technique, while space-time equalizing employs a linear minimum mean-square error (LMMSE) criterion.