Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from a common digital information sequence. Each received signal vector is decoded using, for example, a maximum-likelihood decoder to produce log-likelihood ratios. The results of the decoders are combined by addition to produce a final decoding estimate. In some embodiments, each of the received signals may be processed prior to decoding. The disclosed decoding scheme may utilize all received information without increasing hardware complexity.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The receiver linearizes each received signal vector using one or more zero-forcing, MMSE, or other suitable linear equalizers. The components of the equalized signal vectors may be combined using maximum-ratio combining to form the components of a combined equalized signal vector. The components of the combined equalized signal vector may then be decoded individually using a linear decoder.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from a common digital information sequence. Each received signal vector is decoded using, for example, a maximum-likelihood decoder to produce log-likelihood ratios. The results of the decoders are combined by addition to produce a final decoding estimate. In some embodiments, each of the received signals may be processed prior to decoding. The disclosed decoding scheme may utilize all received information without increasing hardware complexity.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The receiver linearizes each received signal vector using one or more zero-forcing, MMSE, or other suitable linear equalizers. The components of the equalized signal vectors may be combined using maximum-ratio combining to form the components of a combined equalized signal vector. The components of the combined equalized signal vector may then be decoded individually using a linear decoder.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. For each received signal vector, the receiver evaluates a decoding metric using each possible value of the transmitted signal vector to produce a set of distances. The receiver then combines distances from across the received signal vectors to produce a combined distance associated with each possible value of the transmitted signal vector. Using the combined distances, the receiver may choose among the possible values of the transmit signal vector to determine the actual transmit signal vector.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. For each received signal vector, the receiver evaluates a decoding metric using each possible value of the transmitted signal vector to produce a set of distances. The receiver then combines distances from across the received signal vectors to produce a combined distance associated with each possible value of the transmitted signal vector. Using the combined distances, the receiver may choose among the possible values of the transmit signal vector to determine the actual transmit signal vector.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined received signal vector may be equalized by, for example, a zero-forcing or minimum-mean-squared error equalizer or another suitable linear equalizer. Following equalization, the equalized signal vector may be decoded using a simple, linear decoder.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The receiver linearizes each received signal vector using one or more zero-forcing, MMSE, or other suitable linear equalizers. The components of the equalized signal vectors may be combined using maximum-ratio combining to form the components of a combined equalized signal vector. The components of the combined equalized signal vector may then be decoded individually using a linear decoder.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. For each received signal vector, the receiver evaluates a decoding metric using each possible value of the transmitted signal vector to produce a set of distances. The receiver then combines distances from across the received signal vectors to produce a combined distance associated with each possible value of the transmitted signal vector. Using the combined distances, the receiver may choose among the possible values of the transmit signal vector to determine the actual transmit signal vector.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The receiver combines the received vectors by vector concatenation The concatenated vector may then be decoded using, for example, maximum-likelihood decoding. In some embodiments, the combined signal vector is equalized before decoding.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined received signal vector may be equalized by, for example, a zero-forcing or minimum-mean-squared error equalizer or another suitable linear equalizer. Following equalization, the equalized signal vector may be decoded using a simple, linear decoder.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The receiver combines the received vectors by vector concatenation The concatenated vector may then be decoded using, for example, maximum-likelihood decoding. In some embodiments, the combined signal vector is equalized before decoding.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined signal vector is then decoded using a maximum-likelihood decoder. In some embodiments, the combined received signal vector may be processed prior to decoding. Systems and methods are also provided for computing soft information from a combined signal vector based on a decoding metric. Computationally intensive calculations can be extracted from the critical path and implemented in preprocessors and/or postprocessors.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The receiver combines the received vectors by vector concatenation The concatenated vector may then be decoded using, for example, maximum-likelihood decoding. In some embodiments, the combined signal vector is equalized before decoding.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined signal vector is then decoded using a maximum-likelihood decoder. In some embodiments, the combined received signal vector may be processed prior to decoding. Systems and methods are also provided for computing soft information from a combined signal vector based on a decoding metric. Computationally intensive calculations can be extracted from the critical path and implemented in preprocessors and/or postprocessors.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The receiver combines the received vectors by vector concatenation The concatenated vector may then be decoded using, for example, maximum-likelihood decoding. In some embodiments, the combined signal vector is equalized before decoding.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined signal vector is then decoded using a maximum-likelihood decoder. In some embodiments, the combined received signal vector may be processed prior to decoding. Systems and methods are also provided for computing soft information from a combined signal vector based on a decoding metric. Computationally intensive calculations can be extracted from the critical path and implemented in preprocessors and/or postprocessors.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors from the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined signal vector is then decoded using a maximum-likelihood decoder. In some embodiments, the combined received signal vector may be processed prior to decoding. Systems and methods are also provided for computing soft information from a combined signal vector based on a decoding metric. Computationally intensive calculations can be extracted from the critical path and implemented in preprocessors and/or postprocessors.

Abstract: Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where a receiver has received one or more signal vectors from the same transmitted vector. The receiver processes these received signal vectors one by one, and uses information from signal vectors that have already been processed to process the next signal vector. To process a current signal vector, the receiver concatenates the current signal vector with a previously processed signal vector. This concatenated signal vector is decoded using, for example, a maximum-likelihood (ML). To decode the concatenated signal vector, the ML decoder can use a concatenated channel matrix that includes a channel response matrix associated with the current signal vector and a processed version of previous channel response matrices.

Abstract: Systems and methods are provided for decoding a signal vector in a transmission scheme that uses transmit diversity as well as HARQ, repetition coding, or any other protocol that allows a receiver to obtain multiple reception of common transmit information. Information obtained in more than one symbol period are treated as a single received vector, and each of the received signal vectors may be processed to reduce or remove phase rotations caused by the channel. The received signal vectors may be combined by addition and decoded using a maximum-likelihood decoder. In some embodiments, the transmitter and receiver are configured to communicate using the transmit diversity scheme and a spatial multiplexing scheme. The scheme may be chosen based on the quality of the channel through which communication takes place.