Abstract: In general, this disclosure describes techniques for beamforming using limited feedback that exploit the spatio-temporal channel correlation and avoid the limitations of codebook-based feedback and Markov chain modeling. In one example, a receiving device includes a plurality of receive antennas for receiving communication information, a memory for storing the communication information, and one or more processors for processing the communication information. The one or more processors are configured to receive, through a wireless communication channel, a pilot signal transmitted by a transmitting device, determine, based on the received pilot signal, channel state feedback comprising a quantized representation of the pilot signal as received at the receiving device, and send, through the wireless communication.

Abstract: In general, this disclosure describes techniques for beamforming using limited feedback that exploit the spatio-temporal channel correlation and avoid the limitations of codebook-based feedback and Markov chain modeling. In one example, a receiving device includes a plurality of receive antennas for receiving communication information, a memory for storing the communication information, and one or more processors for processing the communication information.

Abstract: In general, this disclosure describes techniques for beamforming using limited feedback that exploit the spatio-temporal channel correlation and avoid the limitations of codebook-based feedback and Markov chain modeling. In one example, a receiving device includes a plurality of receive antennas for receiving communication information, a memory for storing the communication information, and one or more processors for processing the communication information. The one or more processors are configured to receive, through a wireless communication channel, a pilot signal transmitted by a transmitting device, determine, based on the received pilot signal, channel state feedback comprising a quantized representation of the pilot signal as received at the receiving device, and send, through the wireless communication.

Abstract: In general, this disclosure describes techniques for beamforming using limited feedback that exploit the spatio-temporal channel correlation and avoid the limitations of codebook-based feedback and Markov chain modeling. In one example, a receiving device includes a plurality of receive antennas for receiving communication information, a memory for storing the communication information, and one or more processors for processing the communication information.

Abstract: A frequency hopping signal receiving system comprising: a receiver for extracting discrete-time samples from the signal; a memory connected to the receiver for storing the extracted discrete-time samples from the signal; at least one processor operatively connected to the memory for: determining a state-space vector that captures relevant information to describe the dynamics of the signal; selecting a parameter to represent the probability of hopping associated with the signal; generating particle filters to estimate unknown parameters in the state-space vector based upon the extracted discrete-time samples by generating random particles that approximate the filtering distribution having importance weights; specifying the importance function in closed-form in a convenient mixture representation, which enables drawing particles and updating the importance weights; constructing an estimator to generate hop particles based upon observing at least one sample hop and then evaluating the estimator using a condition

Abstract: A frequency hopping signal receiving system comprising: a receiver for extracting discrete-time samples from the signal; a memory connected to the receiver for storing the extracted discrete-time samples from the signal; at least one processor operatively connected to the memory for: determining a state-space vector that captures relevant information to describe the dynamics of the signal; selecting a parameter to represent the probability of hopping associated with the signal; generating particle filters to estimate unknown parameters in the state-space vector based upon the extracted discrete-time samples by generating random particles that approximate the filtering distribution having importance weights; specifying the importance function in closed-form in a convenient mixture representation, which enables drawing particles and updating the importance weights; constructing an estimator to generate hop particles based upon observing at least one sample hop and then evaluating the estimator using a condition

Abstract: A window and level control tool that operates in real time and can quickly determine initial values for window and level settings such that a displayed image is always presented in a readable format is disclosed. The invention transforms input image data into an image histogram. This histogram is then segmented into a small number of parts corresponding to structures of interest. Segmentation of the histogram is done by a novel Viterbi optimal runlength-constrained approximation nonlinear filter. Window and level settings are calculated to correspond to this optimal segmentation. A readable image of one of the structures of interest is then displayed. In another embodiment, the tool provides a menu of optimal window and level settings corresponding to the different types of information a radiologist may be interested in.