Abstract: A Building Management System (BMS) may be controlled in accordance with predicted occupancy using a trained model. A model is trained by providing the model with time stamped environmental data and corresponding time stamped occupancy data pertaining to a training building, wherein the time stamped environmental data is derived from one or more environmental sensors of the training building and the corresponding time stamped occupancy data is derived from one or more occupancy sensors of the training building. Once trained, the trained model is provided with time stamped environmental data for a use building that is derived from one or more environmental sensors of the use building. Occupancy data for the use building is not required. The trained model outputs a predicted occupancy value that represents a predicted occupancy count in the use building, and the BMS of the use building is controlled based at least in part on the predicted occupancy value.

Abstract: A method for determining coarse carrier phase and frequency offsets of an initial block of received M-QAM symbols includes creating a grid of discrete candidate phase offset values and for each candidate value: applying the candidate value to each symbol, applying a respective hard decision to each applied symbol, and computing a figure of merit based thereon. The candidate value having the best figure of merit is selected as an initial phase offset estimate. An initial frequency offset estimate is computed using the symbols updated with the initial phase offset estimate, their respective hard decisions, and an approximation of the complex exponential function. To track carrier phase and frequency offsets associated with a series of symbol blocks, for each symbol of a current block, set a binary trust weight based on comparison of a computed parameter with a threshold and use the binary trust weights to compute a phase offset error and a frequency offset error for the current block.

Abstract: A method for determining coarse carrier phase and frequency offsets of an initial block of received M-QAM symbols includes creating a grid of discrete candidate phase offset values and for each candidate value: applying the candidate value to each symbol, applying a respective hard decision to each applied symbol, and computing a figure of merit based thereon. The candidate value having the best figure of merit is selected as an initial phase offset estimate. An initial frequency offset estimate is computed using the symbols updated with the initial phase offset estimate, their respective hard decisions, and an approximation of the complex exponential function. To track carrier phase and frequency offsets associated with a series of symbol blocks, for each symbol of a current block, set a binary trust weight based on comparison of a computed parameter with a threshold and use the binary trust weights to compute a phase offset error and a frequency offset error for the current block.

Abstract: The noise figure for a radio frequency device may be obtained through power measurements. A signal flow graph based upon the S-parameter information of the entire RF system may be constructed. The S-parameter information may be representative of the microwave termination, the device, the measurement instrument and any losses due to additional components such as connecting cables/attenuators/switches, etc. The signal flow graph includes proper placement and values of the source nodes corresponding to each RF sub-system enumerated above. Noise figure measurements may include a calibration step and a measurement step. During the calibration step the noise figure and the noise temperature of the measurement instrument used for the measurement may be obtained. During the measurement step, the noise figure and the noise temperature of the device may be obtained based at least on the noise figure and noise temperature of the measurement instrument obtained during the calibration step.

Abstract: The noise figure for a radio frequency device may be obtained through power measurements. A signal flow graph based upon the S-parameter information of the entire RF system may be constructed. The S-parameter information may be representative of the microwave termination, the device, the measurement instrument and any losses due to additional components such as connecting cables/attenuators/switches, etc. The signal flow graph includes proper placement and values of the source nodes corresponding to each RF sub-system enumerated above. Noise figure measurements may include a calibration step and a measurement step. During the calibration step the noise figure and the noise temperature of the measurement instrument used for the measurement may be obtained. During the measurement step, the noise figure and the noise temperature of the device may be obtained based at least on the noise figure and noise temperature of the measurement instrument obtained during the calibration step.