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.

Apparatus and methods are provided for noise-whitening post-compensation in a receiver. A first apparatus includes a first whitening filter configured to filter a received signal comprising symbols to generate a first filtered signal. The first apparatus further includes a first decision feedback equalizer having an input coupled to an output of the first whitening filter to receive the first filtered signal. The first decision feedback equalizer is configured to apply decision feedback equalization to the first filtered signal to generate estimates for the symbols of the received signal. A second apparatus includes a decision device configured to generate a symbols decision based on a received signal comprising symbols, a noise predictor configured to predict noise in the received signal, and a subtractor configured to subtract the predicted noise from the received signal to generate a symbols estimate.

The present invention relates to a 5th-generation (5G) or pre-5G communication system, which is to be provided for supporting a higher data transmission rate after the 4th-generation (4G) communication system, such as long term evolution (LTE). The present invention provides a method for receiving a signal in a multi-carrier system, the method comprising the steps of: performing, with respect to an input signal, a waveform pre-processing operation on the basis of at least one of an equalizing operation and a filtering operation; checking whether the waveform pre-processed signal is a Gaussian proximity signal; and performing soft-de-mapping with respect to the waveform pre-processed signal on the basis of a result of the checking.

This disclosure relates to a data processing device, comprising: a digital front end (DFE) configured to convert an antenna signal to digital data, wherein the digital data comprises a plurality of data symbols; a baseband (BB) circuitry configured to process the digital data in baseband; and a digital interface between the DFE and the BB circuitry, wherein the DFE comprises a data compression circuitry configured to compress the plurality of data symbols for use in transmission via the digital interface to the BB circuitry.

What is disclosed is a method for wireless communication comprising receiving a wireless communication via a receiver of the mobile communication device, deriving a demodulation reference signal from a first plurality of symbols of the wireless communication; creating a channel estimation matrix using the demodulation reference signal; inverting the channel estimation matrix to obtain a channel pseudo-inverse matrix; deriving a tracking reference signal from a second plurality of symbols of the wireless communication; calculating a phase shift for one or more additional symbols based on the tracking reference signal; determining a corrected channel pseudo-inverse matrix for the one or more additional symbols by adjusting the channel pseudo-inverse matrix according to the calculated phase shift; and controlling the receiver to accomplish data detection using the corrected channel pseudo-inverse matrix on one or more orthogonal frequency division multiplexing subcarriers.

A method and system for providing sub-band whitening are herein provided. According to one embodiment, a method includes deriving an estimated noise plus interference variance (NIVar) based on at least one legacy-long training field (LLTF) symbol from an LLTF signal; and updating an interference whitening (IW) factor by using a sub-band NIVar.

A radio receiver is disclosed, comprising: a receiving stage configured to receive a multi-layered signal comprising a plurality of layers; a division stage configured to divide the plurality of layers into a first subset and a second subset; a first whitening filter configured to filter the multi-layered signal based on a noise and interference covariance measure derived from the second subset to provide a first filtered multi-layered signal; and a first detection stage configured to detect at least one layer of the first subset based on the first filtered multi-layered signal.

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.

According to one aspect of the present disclosure, a baseband chip may be configured to receive a data stream associated with a channel. The baseband chip may be configured to select a first anchor point from the first constellation points of the first transmission layer. The baseband chip may be configured to select a first subset of constellation points from the first constellation points and the second constellation points. The baseband chip may be configured to perform a first iteration of a recursive tree search. The baseband chip may be configured to determine a first path metric based at least in part on the first iteration of the recursive tree search operation. The baseband chip may be configured to select a second anchor point from the second constellation points of the second transmission layer. The second anchor point may be associated with a second iteration of the recursive tree search.

This disclosure describes a receiver having equalization with noise de-whitening mitigation for wireless communication. An input port receives, via an antenna, a signal communicated over a wireless communication link, the signal comprising a noise component. Control circuitry performs zero forcing equalization of the received signal to generate a zero forcing equalization result signal. The zero forcing equalization causes de-whitening of the noise component by increasing a correlation among elements of the noise component. The control circuitry mitigates the de-whitening of the noise component by: determining a noise variance value based on channel properties of the wireless communication link, and modifying the zero forcing equalization result signal based on the noise variance value. The modified zero forcing equalization result signal is communicated, via an output port, to log-likelihood ratio (LLR) generation circuitry for LLR computation.