| Patent application number | Description | Published |
|---|
| 20080260065 | METHOD AND SYSTEM FOR MODULATING AND DEMODULATING SIGNALS IN ULTRA-WIDE BAND (UWB) COMMUNICATION SYSTEMS - A communication system is disclosed and it may include one or more first circuits in a first passband single carrier transmitter coupled to a first ultra-wide-band wireless transmission channel. The communication system may also include one or more second circuits in a first receiver coupled to the first ultra-wide-band wireless transmission channel. The one or more second circuits may enable receiving of signals transmitted by the one or more first circuits over the first ultra-wide-band wireless transmission channel at a baud rate less than or equal to half of a spectral bandwidth of the signal transmitted by the one or more first circuits. The one or more first circuits and the one or more second circuits coupled to the first ultra-wide-band wireless transmission channel may be a first piconet. | 10-23-2008 |
| 20090040940 | OFF-LINE BROADBAND NETWORK INTERFACE - A system for processing a data packet is disclosed and may include at least one processor that enables receiving of a data packet at a station on a network, the data packet having a preamble which includes a destination tag and a training sequence. The at least one processor may enable obtaining a channel model using the training sequence, and encoding each of one or more addresses that the station receives with the channel model to produce a result. The at least one processor may also enable comparing the result with the destination tag. The at least one processor may enable convolving of each of the one or more addresses that the station receives with the channel model to produce the result. | 02-12-2009 |
| 20090074114 | Method and System for Approximate Maximum Likelihood (ML) Detection in a Multiple Input Multiple Output (MIMO) Receiver - Aspects of a method and system for approximate maximum likelihood (ML) detection in a multiple input multiple output (MIMO) receiver may comprise computing soft decision values for bits that may be decoded from a received signal vector by utilizing approximate ML detection. The soft decision values may be computed for at least a portion bits carried within a received signal vector by decomposing a candidate constellation vector into segments, with each dimension representing a spatial stream signal. After decomposition, soft decision values for at least a portion of the bits may be computed by selecting values in a search dimension and computing values in a plurality of slice dimensions. Values within the search dimension may be determined by selecting constellation points within a constellation map for the search dimension. Values within each slice dimension may be computed for each selected constellation point. | 03-19-2009 |
| 20090190691 | Method and System for Subspace Beamforming for Near Capacity Multiple Input Multiple Output (MIMO) Performance - 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 (θ | 07-30-2009 |
| 20090268833 | METHOD AND SYSTEM FOR PREDICTING CHANNEL QUALITY INDEX (CQI) VALUES FOR MAXIMUM LIKELIHOOD (ML) DETECTION IN A 2X2 MULTIPLE INPUT MULTIPLE OUTPUT (MIMO) WIRELESS SYSTEM - 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. | 10-29-2009 |
| 20090268834 | METHOD AND SYSTEM FOR PREDICTING CHANNEL QUALITY INDEX (CQI) VALUES FOR MAXIMUM LIKELIHOOD (ML) DETECTION IN A KXK MULTIPLE INPUT MULTIPLE OUTPUT (MIMO) WIRELESS SYSTEM - Aspects of a method and system for predicting CQI values for ML detection in a K×K MIMO system are presented. In one aspect of the system, a CQI value for a K×K MIMO communication system may be computed by decomposing the K×K MIMO system into a series of 2×2 MIMO systems. For each 2×2 MIMO system a CQI value may be computed by reverse mapping a PER computed for the 2×2 MIMO system and an SNR value for a SISO communication system. By summing CQI values among the series of 2×2 MIMO systems a CQI value for the K×K MIMO system may be computed. Based on the computed CQI value for the K×K MIMO system, a coding rate may be selected. The selected coding rate may be selected to maximize a computed information throughput rate at a MIMO receiver that utilizes ML detection. | 10-29-2009 |
| 20090285343 | SYSTEM AND METHOD FOR CANCELING INTERFERENCE IN A COMMUNICATION SYSTEM - A filter settings generation operation includes sampling a communication channel to produce a sampled signal. The sampled signal is spectrally characterized across a frequency band of interest to produce a spectral characterization of the sampled signal. This spectral characterization may not include a signal of interest. The spectral characterization is then modified to produce a modified spectral characterization. Filter settings are then generated based upon the modified spectral characterization. Finally, the communication channel is filtered using the filter settings when the signal of interest is present on the communication channel. In modifying the spectral characterization, pluralities of spectral characteristics of the spectral characterization are independently modified to produce the modified spectral characterization. Modifications to the spectral characterization may be performed in the frequency domain and/or the time domain. One particular spectral modification that is performed is raising of the noise floor of the spectral characterization to meet a budgeted signal-to-noise ratio. Other spectral modifications include modifying spectral components corresponding to an expected interfering signal. In modifying these spectral characterizations, spectral components corresponding to a plurality of expected interfering signals may be modified. | 11-19-2009 |
| 20100150260 | METHOD AND SYSTEM FOR MINIMIZING EFFECTS OF TRANSMITTER IMPAIRMENTS IN MULTIPLE INPUT MULTIPLE OUTPUT (MIMO) BEAMFORMING COMMUNICATION SYSTEMS - Aspects of a method and system for minimizing effects of transmitter impairments in multiple input multiple output (MIMO) beamforming communication systems are presented. In one aspect of a system for minimizing effects of transmitter impairments, a MIMO transmitter may enable nulling of transmitter-induced noise by adjusting at least a portion of a plurality of signals transmitted based on a transmitter error vector magnitude (EVM). The transmitter may enable transmission of the plurality of signals subsequent to the nulling. In another aspect of a system for minimizing effects of transmitter impairments a MIMO receiver may enable nulling of transmitter-induced noise contained in a plurality of received signals based on a transmitter EVM. Each of the plurality of received signals may include information contained in a plurality of spatial streams. The receiver may enable detecting estimated values for the information contained in the plurality of spatial streams based on the nulling. | 06-17-2010 |
| 20100232551 | EFFICIENT OPTIMAL ML DETECTOR - 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. | 09-16-2010 |
| 20110135044 | System and Method for Canceling Interference in a Communication System - A filter settings generation operation includes sampling a communication channel to produce a sampled signal. The sampled signal is spectrally characterized across a frequency band of interest to produce a spectral characterization of the sampled signal. This spectral characterization may not include a signal of interest. The spectral characterization is then modified to produce a modified spectral characterization. Filter settings are then generated based upon the modified spectral characterization. Finally, the communication channel is filtered using the filter settings when the signal of interest is present on the communication channel. In modifying the spectral characterization, pluralities of spectral characteristics of the spectral characterization are independently modified to produce the modified spectral characterization. Modifications to the spectral characterization may be performed in the frequency domain and/or the time domain. One particular spectral modification that is performed is raising of the noise floor of the spectral characterization to meet a budgeted signal-to-noise ratio. Other spectral modifications include modifying spectral components corresponding to an expected interfering signal. In modifying these spectral characterizations, spectral components corresponding to a plurality of expected interfering signals may be modified. | 06-09-2011 |
| 20110164699 | METHOD AND SYSTEM FOR AN ITERATIVE MULTIPLE USER MULTIPLE INPUT MULTIPLE OUTPUT (MU-MIMO) COMMUNICATION SYSTEM - 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. | 07-07-2011 |
