Abstract: A method for managing beam squint in a phased antenna array system operating at millimeter wavelengths using carrier aggregation includes determining a minimum array gain threshold, determining an upper bound for a fractional bandwidth for a fixed number of antennas, and constructing a codebook with a predetermined coverage range based on at least one of an angle of arrival or an angle of departure and further based on the upper bound. The method further includes performing carrier aggregation for the fixed number of antennas and selecting at least two antennas based on the codebook.

Abstract: Examples of wideband spectrum sensing techniques for cognitive radio are provided. The techniques permit undersampling (e.g., sub-Nyquist sampling) the spectrum band, which permits use of more cost effective electronic components (e.g., lower frequency analog-to-digital converters (ADC)). The techniques permit determination of whether there are any (or sufficient) sub-channels that exist in the band to use for transmission, so that only a portion of less than the entire spectrum band is sampled. Detection decisions can be based at least partly on a pair of performance metrics more appropriate for wideband spectrum sensing. These performance metrics are the probability of insufficient spectrum opportunities (PISO) and the probability of excessive interference opportunities (PEIO).

Abstract: In one embodiment, a cognitive radio dynamic spectrum access sensing system is configured to incorporate a hidden Markov model and a risk function to determine the primary user state sequence with the minimum amount of associated risk. The system comprises one or more weighted cost factors that can be used to handle a missed detection sensing error differently from a false alarm sensing error. The system further comprises a complete forward partial backward computation designed to increase sensing accuracy with limited effect on sensing delay and complexity.

Abstract: In one embodiment, a cognitive radio dynamic spectrum access sensing system is configured to incorporate a hidden Markov model and a risk function to determine the primary user state sequence with the minimum amount of associated risk. The system comprises one or more weighted cost factors that can be used to handle a missed detection sensing error differently from a false alarm sensing error. The system further comprises a complete forward partial backward computation designed to increase sensing accuracy with limited effect on sensing delay and complexity.