Abstract: Systems and methods for providing for increased data rate modes using multiple encoders and decoders, comprising a transmitter comprising multiple encoders, wherein at least one of the encoders has a different error protection strength than at least one other of the encoders. Some embodiments comprise multiple encoders, wherein a symbol receives bits produced by at least two of the multiple encoders. Other embodiments comprise multiple encoders connected to at least one interleaver. Still other embodiments comprise a plurality of decoders, the decoders decoding received bits mapped on symbols on received tones, the bits received from at least one transmitter comprising a plurality of encoders and at least one interleaver.

Abstract: Embodiments provide novel systems and methods for low-complexity maximum-likelihood detection, for use in various communication systems, e.g., multiple-input multiple-output (MIMO) systems, etc. These systems and methods enable computation of a detector that is more accurate than the max-log approximation. Embodiments comprise systems and methods for computing, using a maximum-likelihood detector, a set of log-likelihood ratio (LLR) values for a cost function of a channel input by implementing at least one accumulate LLR functional definition.

Abstract: Systems and methods for dual-carrier modulation (DCM) encoding and decoding for communication systems. Some embodiments comprise a DCM encoder for applying a pre-transmission function to at least one 16-QAM input symbol and mapping resulting transformed symbols onto at least one larger constellation prior to transmission. Some embodiments joint decode, by a DCM decoder, a predetermined number of received data elements and compute a set of log-likelihood ratio (LLR) values for at least eight bits from a resulting at least one transformed symbol.

Abstract: Embodiments provide novel systems and methods for multiple-input multiple-output (MIMO) Max-Log detection. These systems and methods enable near-optimal performance with low complexity for a two-input two-output channel. Some embodiments comprise using a Max-Log detector to compute a set of log-likelihood ratio (LLR) values for a channel input by minimizing cost function while computing only one instance of the cost function for each value of each bit in a symbol. Other embodiments comprise using a Max-Log detector to compute a set of log-likelihood ratio (LLR) values for a channel input by computing all instances of a cost function for each value of each bit in a symbol and selecting the minimum cost from all computed instances of the cost function for each value of each bit.

Abstract: Embodiments provide systems and methods for improved multiple-input, multiple-output (MIMO) detection comprising generating at least one list of candidate vectors by employing lattice enumeration which approximates hyperellipsoid detection search space and calculating a reliability of the candidate vectors. At least one advantage to embodiments is that improved detection occurs because detection can be performed in a search space defined by the eigenvectors (which define the general shape of an ellipsoid/hyperellipsoid, depending upon number of dimensions) and eigenvalues (which provide the appropriate scaling in each direction of the eigenvectors) of the effective channel.

Abstract: Embodiments provide a system and method for reconstructing steering matrices in a MIMO-OFDM (multiple-input multiple-output orthogonal frequency division multiplexing) system by interpolating steering matrices in transmit beamforming. The reconstructed steering matrices provide a faithful representation to the actual steering matrices. Embodiments receive channel information for a subset of sub-carriers of a channel, interpolate the channel information for the subset of sub-carriers to obtain at least one Givens rotation angle for remaining sub-carriers of the channel which are not members of the subset, and reconstruct missing steering matrices from the interpolated angles.

Abstract: Embodiments provide a system and method for efficiently classifying different channel types in an orthogonal frequency division multiplexing (OFDM) system. Embodiments quantify the frequency selectivity in a channel by measuring the variation in a particular channel statistic across sub-carriers in an OFDM system, involve minimal complexity in implementation, and can be used in a variety of scenarios. One embodiment is a method for classifying channels in an OFDM system, comprising measuring variation of at least one channel statistic across sub-carriers, quantifying the variation to determine a measurement value, and applying the measurement value to at least one threshold to classify the channel.

Abstract: A method and system for estimating noise variance. A method for noise variance estimation comprises receiving a first multi-sample symbol and receiving a second multi-sample symbol. The first multi-sample symbol is subtracted from the second multi-sample symbol to produce a set of noise samples. The set of noise samples is used to produce a noise variance estimate. The noise variance estimate is applied in various tasks (e.g. channel estimation, log-likelihood ratio computation, and/or minimum mean squared error equalization) to process data provided to a user.

Abstract: Systems and methods for providing multiple-input multiple-output (MIMO) detection, comprising a leaf node predictor for receiving a processed communications stream, computing at least one channel metric corresponding to the communications stream for a given channel realization, and generating at least one parameter corresponding to at least one predicted best leaf node candidate for the given channel realization. A MIMO engine receives the at least one parameter and enumerates at least one list of candidate vectors corresponding to the leaf nodes specified by the generated at least one parameter. Some embodiments simulate a MIMO detector over many channel realizations, track channel metric and parameter values used for each channel realization resulting from such simulating, and store, in a look-up table, best values of the tracked values used for a particular channel metric.

Abstract: In order to enable multiple input-multiple output (MIMO) equalization, including as an example minimum mean-squared error (MMSE) MIMO equalization, to be implemented using a conventional QR decomposition, it is beneficial to force the noise variance of each of the channel outputs to be equalized. Embodiments scale the channel outputs in order to create an effective channel whose outputs have approximately the same noise variance. Embodiments comprise systems and methods for a channel outputs scaler to apply at least one scaling factor to each channel output of a channel outputs vector to thereby equalize the noise variance among the channel outputs.

Abstract: Embodiments provide systems and methods for a novel multiple-input multiple-output (MIMO) equalization technique that produces a channel matrix that contains partly real coefficients and partly complex coefficients, referred to herein as a hybrid-MIMO equalization. MIMO detectors can exploit the hybrid-MIMO equalization to reduce complexity. Some embodiments provide systems and methods for equalizing a communication channel comprising receiving as an input a channel output vector, dividing the input into two vectors, a first vector that remains a complex number and a second vector that contains only real numbers, separating the second vector into its real and imaginary components, and regrouping the first and second vectors into a hybrid channel output vector that contains both real and complex coefficients.

Abstract: A Multiple-input Multiple-Output (MIMO) receiver is provided. The MIMO receiver comprises a parameterized sphere detector having two search modes. During a first search mode, the parameterized sphere detector enumerates a number of best candidate vectors up to a fixed parameter value. During a second search mode, the parameterized sphere detector enumerates additional candidate vectors using a greedy search until a predetermined number of candidate vectors have been enumerated.

Abstract: In at least some embodiments, a receiver for a wireless communication system is provided. The receiver includes an equalizer that provides an equalized channel matrix. The receiver also includes scaling logic coupled to the equalizer, the scaling logic selectively scales coefficients of the equalized channel matrix. The receiver also includes a decoder coupled to the scaling logic. The decoder decodes a signal based on the equalized channel matrix with scaled coefficients.

Abstract: A method and system for performing Multiple-input Multiple-Output (“MIMO”) detection that reduces complexity by decomposing MIMO detection problem into two less complex problems, Candidate List generation and Interference Cancellation (“CLIC”). Embodiments of the CLIC framework parse an N element channel output into a first set containing S elements and a second set containing N-S elements. A first list of candidate vectors is generated from the first set of elements. A set of interference cancelled elements is generated by using the first list of candidate vectors to cancel interference from the second set of elements. A second list of candidate vectors is generated from the set of interference cancelled elements. A minimum cost is computed for each bit of the candidate vectors and from the costs a log-likelihood ratio is computed.

Abstract: A method and system for generating a set of candidate symbols. A system includes a Multiple Input Multiple Output (“MIMO”) receiver. The receiver includes a candidate generation look-up table (“LUT”) that provides a list of candidate values for a transmitted symbol selected from a constellation of symbols. The candidate generation LUT stores candidate lists for a portion of the constellation of symbols. The portion of the constellation for which candidate lists are stored is selected according to a symmetry of the constellation. The LUT preferably provides a secondary constellation superimposed on a decision region of a primary constellation. The LUT also preferably includes an inner point of the primary constellation and outer points of the primary constellation. The primary and secondary constellations are preferably compressed by application of quadrant, mirror, and inner-point symmetries.

Abstract: A method and apparatus for detecting symbols in a Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (“MIMO-OFDM”) system. A MIMO-OFDM receiver includes a first detector that estimates a symbol of a first MIMO-OFDM sub-carrier and a second detector that estimates a symbol of a second MIMO-OFDM sub-carrier. The second detector differs in complexity from the first detector. A detector control block is coupled to the detectors. The detector control block assigns the first detector to process the first MIMO-OFDM sub-carrier and assigns the second detector to process the second MIMO-OFDM sub-carrier. The detector control block computes a list metric for a sub-carrier. Based on the list metric the detector control block assigns a candidate symbol list length to the detector processing the sub-carrier. Alternately, the detector control block assigns one of a variety of detector types to a sub-carrier based on the sub-carrier list metric.

Abstract: A method and system for reduced feedback transmit beamforming are provided. Some embodiments comprise computing a matrix of channel transfer function coefficients. The matrix of channel transfer function coefficients is compressed by applying a rotation matrix having orthogonal columns to the matrix of channel transfer function coefficients to produce a compressed transfer function matrix having a reduced number of non-zero coefficients. The compressed matrix is fed back to a transmitting unit. Decompression of the transfer function coefficient matrix is not required. This compression does not cause any performance degradation for transmit beamforming. The transmitting unit computes a set of beamsteering coefficients from the compressed matrix and applies the coefficients to signals prior to transmission. The beamformed signals are transmitted to the receiving unit and post-coded to allow the receiving unit to see an effective diagonalized channel.