Abstract: A receiver including an input module, a computation module, and an equalizer module. The input module is configured to receive a message from a wireless communication channel. The message includes multiple training fields. The computation module is configured to recursively compute equalizer parameters, as the training fields are being received, based on the training fields and a channel estimation matrix. The equalizer module is configured to apply the equalizer parameters to the message to recover user data.

Abstract: Methods and apparatus are provided for computing reliability values in a pipeline. A reliability value portion is computed, with control circuitry in a first pipeline stage, based on a difference between a received input signal value and an expected value. The reliability value portion is combined, in a second pipeline stage that follows the first pipeline stage, with a first value derived from the received input signal to generate a first reliability value. A determination is made as to whether to update the first reliability value in a third pipeline stage based on a combination of the first reliability value with a second reliability value that corresponds to a second value derived from the received input signal.

Abstract: Systems and techniques relating to processing information received from a spatially diverse transmission. In some implementations, an apparatus includes an input configured to receive data that has been transmitted over a wireless channel using multiple transmit antennas, nt, and multiple receive antennas, nr; and an equalizer responsive to multiple data streams corresponding to the multiple receive antennas and configured to generate an equalization matrix, Gntxnr, using a kernel matrix order updated from n(t?i)xn(r?j) to ntxnr, the kernel matrix updates being distributed across preamble processing operations. The input can be responsive to a selectable number of at least four antennas in an orthogonal frequency division multiplexed (OFDM) multiple-in-multiple-out (MIMO) system, and the equalizer can be configured to distribute the kernel matrix updates across multiple training fields of data preambles.

Abstract: An equalizer to be applied to signals received via at least one multiple input, multiple output (MIMO) channel is computed using a matrix equalizer computational device. The computed equalizer is applied to a received signal to recover an equalized representation of encoded data sent in a transmission. Errors are removed from the equalized representation of the encoded data to generate an error-corrected estimation of the encoded data sent in the transmission, and the equalized representation of the encoded data is compared to the error-corrected estimation of the encoded data. An updated equalizer is then computed to be applied to a subsequent signal based on the comparison.

Abstract: Systems and methods are provided for channel estimation using linear phase estimation. These systems and methods enable improved channel estimation by estimating a linear channel phase between received pilot subcarrier signals. The estimated linear phase can then be removed from the received pilot subcarrier signals. After the estimated linear phase is removed from the received pilot subcarrier signals, a channel response can be estimated. A final estimated channel response can be generated by multiplying the results of the linear channel estimation by the estimated linear phase.

Abstract: Methods and apparatus are provided for performing LLR value computations in a pipeline. Portions of a metric used to compute LLR values are computed in one pipeline part. The portions correspond to all permutations of some received signal streams. The portions are combined with one permutation x2 of the received signal stream that was not included in the previous pipeline computation in a subsequent pipeline part to produce M values associated with a particular bit position. At each subsequent clock cycle, a different permutation of x2 is combined with the previously computed portions producing different M values. State values corresponding to different values of bit positions of the received stream are computed by finding the minimum among the M values, in each clock cycle, that affect a particular bit position. The state values are combined to compute the LLR values for the bit position in a final pipeline part.

Abstract: A training signal is received, and a channel estimate matrix is determined based on the received training signal. The channel estimate matrix is partitioned into a plurality of block matrices, wherein at least one of the block matrices has at least one dimension greater than one. Additionally, a multiple input, multiple output (MIMO) equalizer is calculated based on a block matrix inverse or pseudo-inverse of the partitioned channel estimate matrix, and the MIMO equalizer is applied to data signals.

Abstract: Systems and techniques relating to processing information received from a spatially diverse transmission. In some implementations, a method comprises: obtaining a received signal that was transmitted over a wireless channel using spatially diverse transmission, the received signal comprising multiple subcarriers; and recursively computing a signal-to-noise-ratio (SNR) of the received signal while receiving channel response information of the wireless channel derived from the received signal; wherein the recursively computing comprises recursively updating a diagonal kernel matrix, the method further comprising generating an equalization matrix from the recursively updated diagonal kernel matrix, the equalization matrix being useable in equalizing the received signal across the multiple subcarriers.

Abstract: Methods and systems for communication include determining multiple angles based on a channel response matrix, calculating a triangular matrix based on the determined angles and the channel response matrix, receiving signals from a transmitter, and estimating transmitted signals using an inverse of the triangular matrix, the determined angles, and the received signals. The determined angles can include one or more angles to perform phase cancellation on the channel response matrix and one or more angles to zero one or more below diagonal elements of the channel response matrix.

Abstract: A receiver module includes an input that receives a data message from a wireless communication channel. The data message has a plurality of training fields and data. A channel estimator module recursively estimates a matrix H that represents the channel based on the plurality of training fields. The recursive estimation is performed as the plurality of training fields are being received. An equalizer module applies coefficients to the data based on the matrix H.

Abstract: A receiver in a MIMO-OFDM system may estimate the transmitted signal by performing a QR decomposition on the channel response matrix. The receiver may utilize Givens rotations to perform the decomposition, which may be performed using coordinate rotation digital computer (CORDIC) modules.

Abstract: A receiver module includes an input that receives a data message from a wireless communication channel. The data message has a plurality of training fields and data. A channel estimator module recursively estimates a matrix H that represents the channel based on the plurality of training fields. The recursive estimation is performed as the plurality of training fields are being received. An equalizer module applies coefficients to the data based on the matrix H.