Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: Systems, methods, and computer programs for analyzing genetic sequence data is disclosed. In one aspect, the system can include one or more of a first integrated circuit, with each first integrated circuit forming a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of a sequence analysis pipeline. Additionally, the system can include one or more second integrated circuits, with each second integrated circuit forming a field programmable gate array (FPGA). The FPGA can be configured by firmware to arrange a set of hardwired digital logic circuits to perform a second set of genomic processing stages of the sequence analysis pipeline, the set of hardwired digital logic circuits of each FPGA being arranged as a set of processing engines to perform the second set of genomic processing stages.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline.

Abstract: A dedicated calibration device may be utilized by a wireless transceiver device, such as a base station, to compute compensation matrices. The wireless transceiver device and the dedicated calibration device can exchange training sequence signals. Based on the exchanged training sequence signals, the wireless transceiver device and the dedicated calibration device can estimate overall baseband to baseband channel responses taking into account the amplitude and phase responses of the respective transmit and receive radio chains, and the wireless transceiver device can determine the compensation matrices. Furthermore, the wireless transceiver device can estimate a baseband-to-baseband uplink channel response relative to actual user equipment, approximate a downlink channel response using only one of the determined compensation matrices, and perform beamforming to the actual user equipment using the approximated downlink channel response.

Abstract: A method and system for an iterative multiple user multiple input multiple output (MU-MIMO) communication system are presented. In one aspect, a current iteration beamforming matrix may be generated based on a current iteration matched filter matrix for each of a plurality of user devices. A subsequent iteration matched filter matrix may be generated based on the current iteration beamforming matrix for each of the plurality of user devices. A subsequent iteration beamforming matrix may be generated based on the subsequent iteration matched filter matrix for each of the plurality of user devices. A succeeding iteration beamforming matrix may be generated based on an iteration count value and/or based on one or more difference values. The one or more difference values may be computed based on the plurality of subsequent iteration beamforming matrices and the plurality of current iteration beamforming matrices generated for the plurality of user devices.

Abstract: Aspects of a method and system for utilizing Givens rotation expressions for quantization for a general beamforming matrix in feedback information. In one aspect of the invention, feedback information is computed at the receiving MIMO wireless device based on a geometric mean decomposition (GMD) method. The feedback information may include a matrix that describes a wireless medium. The matrix may represent a multiplicative product of at least one rotation matrix and at least one diagonal phase rotation matrix. Each of the rotation matrices may include at least one matrix element whose value is based on Givens rotation angle. The transmitting MIMO wireless device may subsequently transmit a plurality of signals via the wireless medium based on the received matrix information. The signal strength and/or signal to noise ratio (SNR) measurement (as measured in decibels, for example) associated with each of the transmitted plurality of signals may be about equal.

Abstract: Aspects of a method and system for predicting CQI values for ML detection in a 2×2 MIMO system are presented. In one aspect of the system, a CQI value for a MIMO communication system may be computed based on a computed channel realization by reverse mapping the computed channel realization to a corresponding CQI value. Based on the computed CQI value, a coding rate may be selected. The coding rate may be selected from a lookup table, wherein the computed CQI value is utilized as an index to the lookup table. The reverse mapping may utilize a function, which is computed using radial basis function networks. In another aspect of the system, a joint mutual information value may be computed for the MIMO communication system. The joint mutual information value may be computed based on a Shannon mutual information value and a matched filter mutual information value.

Abstract: A method and system for beamforming signal transmission under a per-antenna power constraint is presented. In one aspect, a multiple input multiple output (MIMO) transmitting station may compute a per-antenna power gain factor for each of a plurality of transmit chain signals. The transmit chain signals may be concurrently transmitted by a plurality of transmitting antennas at the MIMO transmitting station. The plurality of transmit chain signals may correspond to beamforming signals, which are generated by performing spatial mapping on a plurality of space-time signals. The plurality of power gain factors may be computed based on a per-antenna power constraint. Alternatively, the plurality of power gain factors may be computed based on joint per-antenna power and total-power constraints. Each of the transmit chain signals may be amplified or attenuated based on the corresponding antenna gain factor. The amplified or attenuated signal is then transmitted by the corresponding transmitting antenna.

Abstract: Aspects of a system for subspace beamforming for near capacity MIMO performance may include a MIMO transmitter that computes one or more rotation angle values (?f) based on a channel estimate matrix (H). In instances when each rotation angle is computed based on a Euclidean distance criterion, each value ?f may also be computed based on a computed Euclidean distance. Alternatively, in instances when each rotation angle is computed based on a bit error rate (BER) criterion, each value ?f may also be computed based on a signal noise power level (N0). A plurality of spatial stream signals (xi) may be generated utilizing one or more constellation types. The constellation map for each constellation type may be rotated based on a corresponding value ?f. A plurality of transmit chain signals (txi) may be generated based on the signals xi and transmitted via a communication medium characterized by matrix H.

Abstract: An efficient optimal maximum-likelihood output detector reducing the complexity of demodulation/decoding computations in multiple-input multiple-output communication systems. A plurality of received signals may be combined into a plurality of combined received signals by multiplication of a matrix representing the plurality of received signals with another matrix that meets certain conditions. The plurality of combined received signals may then allow for slicing operations as well as calculation of distance metrics with significantly reduced complexity.

Abstract: A method and system for beamforming signal transmission under a per-antenna power constraint is presented. In one aspect, a multiple input multiple output (MIMO) transmitting station may compute a per-antenna power gain factor for each of a plurality of transmit chain signals. The transmit chain signals may be concurrently transmitted by a plurality of transmitting antennas at the MIMO transmitting station. The plurality of transmit chain signals may correspond to beamforming signals, which are generated by performing spatial mapping on a plurality of space-time signals. The plurality of power gain factors may be computed based on a per-antenna power constraint. Alternatively, the plurality of power gain factors may be computed based on joint per-antenna power and total-power constraints. Each of the transmit chain signals may be amplified or attenuated based on the corresponding antenna gain factor. The amplified or attenuated signal is then transmitted by the corresponding transmitting antenna.

Abstract: Aspects of a method and system for reordered QRV-LST (layered space time) detection for efficient processing for multiple input multiple output (MIMO) communication systems are presented. The method may include receiving an ordered plurality of signals wherein each of the ordered plurality of received signals comprises information contained in an ordered plurality of spatial streams. Each spatial stream may comprise one or more frequency carriers, or tones. Information, or data, contained in a corresponding one of the ordered plurality of spatial streams may be detected. The order in which the information is detected may be determined for each individual frequency carrier.