Disclosed is a signal source estimation method and apparatus performing the same, the signal source estimation method including acquiring first reception signals received by first receivers, among signals radiated from signal sources, selecting second receivers receiving reception signals to be used to estimate the signal sources, from among the first receivers based on the first reception signals, and detecting the number of signal sources based on second reception signals received by the second receivers.

Allocation of CSI-RS or CSI pilot sequences among cells in a cooperative manner to reduce pilot inter-cell interference. Sequences in each cell occupy the same time slot, multiple subcarrier frequencies, and are orthogonal in time via properly chosen cyclic shifts. Sequences in multiple cells are chosen from a pool of non-orthogonal yet distinguishable sequences through their root indices. Exchanging root indices among cells allows a given cell to reconstruct sequences used in neighboring cells and to estimate interfering channels as the number of channel taps is usually limited, thus mitigating pilot contamination. Furthermore, a greedy selection algorithm to find combinations of sequences that further reduce the channel estimation mean-square-error is proposed.

Various embodiments disclosed herein provide for a reciprocity based channel state information acquisition scheme for frequency division duplex wireless communications systems. By converting channel state information from a traditional frequency-time domain to a Delay-Doppler domain, the channel state information feedback overhead can be reduced since the multi-path of radio propagation is reciprocal in terms of each ray and each cluster of antenna elements. Since the surrounding objects create the same multipath fading for both uplink and downlink transmissions, modeling the channel state information in the Delay-Doppler domain, and adjusting the sign of the Doppler value (negative/positive) can account for the multipath characteristics in both uplink and downlink.

Methods and apparatus for sub-block based architecture of Cholesky decomposition and channel whitening. In an exemplary embodiment, an apparatus is provided that parallel processes sub-block matrices (R.sub.00, R.sub.10, and R.sub.11) of a covariance matrix (R) to determine a whitening coefficient matrix (W). The apparatus includes a first LDL coefficient calculator that calculates a first whitening matrix W.sub.00, lower triangle matrix L.sub.00, and diagonal matrix D.sub.00 from the sub-block matrix R.sub.00, a first matrix calculator that calculates a lower triangle matrix L.sub.10 from the sub-block matrix R.sub.10 and the matrices L.sub.00 and D.sub.00, and a second matrix calculator that calculates a matrix X from the matrices D.sub.00 and L.sub.10. The apparatus also includes a matrix subtractor that calculates a matrix Z from the matrix X and the sub-block matrix R.sub.11, a second LDL coefficient calculator that calculates a third whitening matrix W.sub.11, lower triangle matrix L.sub.11, and a diagonal matrix D.sub.11 from the matrix Z, and a third matrix calculator that calculates a second whitening matrix W.sub.10 from the matrices L.sub.00, L.sub.10, L.sub.11, and D.sub.11.

A receiver for receiving OFDM signals with a channel estimation means is disclosed. The channel estimation means estimates the channel at pilot locations by least squares estimation at pilot locations in subcarriers that include pilot symbols. Using the estimates of the channel at pilot locations, it estimates the channel for each subcarrier containing the pilot symbols, using linear interpolation. It estimates the channel for the sub-frame by interpolating the channel estimates estimated for the sub-carriers including the pilot locations, by using Minimum Mean Square Estimation that uses an auto-covariance matrix. An auto-covariance matrix generator generates the auto-covariance matrix. It generates an auto-covariance matrix based on, an extended cyclic prefix, an estimate of the channel in the time domain estimated by performing an Inverse Discrete Fourier Transform on the channel estimated as above and an average tap power calculated based on the estimate of the channel in the time domain.

A device includes a selection circuit that is configured to generate a bias level. The device also includes a combinational circuit coupled to the selection circuit. The combinational circuit is configured to generate a distortion correction factor used offset inter-symbol interference from a data stream on a distorted bit based on the bias level to generate a correction signal. The device additionally includes a latching element coupled to the combinational circuit and configured to receive the first correction signal.

Embodiments provide a transceiver, configured to select, responsive to a reported position of a mobile terminal, one channel covariance matrix out of a plurality of channel covariance matrices for communication with the mobile terminal or a further mobile terminal, wherein each of the channel covariance matrices is associated with a different one of a plurality of locations of a cell served by the transceiver.

A semi-blind channel estimation method and apparatus are provided. The semi-blind channel estimation method includes: step S1: obtaining data that includes a first training sequence and that is received by a receive end; step S2: performing minimum mean square error channel estimation based on the data and the prestored first training sequence, to obtain a channel parameter matrix; step S3: detecting the first training sequence by using a least square detection algorithm, to obtain estimated data; and step S4: using the estimated data as a second training sequence, replacing the first training sequence in step S2 with the second training sequence, and cyclically performing step S2 and step S3 on the second training sequence, until a channel parameter matrix obtained last time is the same as a channel parameter matrix obtained this time, and then stopping circulation, to estimate a final channel parameter matrix.

The present disclosure relates to methods and devices for Channel State Information, (CSI) prediction. More particularly the disclosure pertains to predicting CSI for a dynamic channel that is varying over time, e.g. because the receiver is moving. This object is obtained by a method performed in a first wireless node of predicting CSI of a dynamic wireless channel H between the first wireless node and a second wireless node. The method comprises deriving channel covariance estimates C.sub.k(n), . . . , C.sub.k(nM) of the dynamic wireless channel H, estimating one or more channel properties of the dynamic wireless channel H, wherein one of the estimated channel properties defines a spectrum spread of the dynamic wireless channel H, and determining a covariance prediction filter, based on the estimated one or more channel properties. The method further comprises predicting one or more channel covariance estimates .sub.k(n+N|n) by applying the determined covariance prediction filter to the derived channel covariance estimates C.sub.k(n), . . . , C.sub.k(nM) and calculating a predicted CSI using the predicted covariance estimates .sub.k(n+N|n). Hence, this disclosure proposes predicting CSI by predicting channel covariance using a methodology which implies deriving optimal covariance prediction filters.

A method and apparatus for data transmission in a cellular system are disclosed herein In one embodiment, the method comprises receiving transmissions of uplink pilot signals made in each slot, by a number of UEs, over the radio resource elements in slots that are allocated for uplink pilot transmission, wherein the number of UEs in the vicinity of at least one base station exceeds the number of radio resource elements that have been allocated for uplink pilot transmission in the slot; estimating large-scale radio-channel propagation strengths of a plurality of nearby UEs to a base station; estimating radio-propagation channel coefficients between each base-station antenna and each UE, in a subset of UEs in the plurality of nearby UEs that have large-scale radio-channel propagation strengths to the base station that are stronger than those UEs in the plurality of nearby UEs not part of the subset; and transmitting to in-cell UEs via multi-user beamforming, including suppressing interference to one or more nearby out-of-cell UEs that are part of the plurality of nearby UEs.