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Radio frequency interference (RFI) can corrupt passive remote sensing measurements taken with microwave radiometers. With the increasingly utilized spectrum and the push for larger bandwidth radiometers, the likelihood of RFI contamination has grown significantly. In this work, an eigenvalue-based algorithm is developed to detect the presence of RFI and provide estimates of RFI-free radiation levels...
Cognitive radios (CRs) are capable of sensing the RF spectrum to identify idle bands dynamically, and transmit opportunistically so as not to interfere with cohabiting primary users (PUs) over the same bands. In this work, spectrum sensing algorithms for CRs that support quality-of-service (QoS) traffic are investigated. Multiple bands are sensed in parallel to reduce the sensing delay, while ensuring...
Spectrum sensing algorithms are developed for cognitive radios to support real-time traffic. Multiple bands are sensed in parallel to reduce sensing delay, while meeting a minimum rate requirement with a prescribed outage probability. Interference constraints are also imposed to protect primary user (PU) transmissions. Both fixed sample size (FSS) and sequential sensing algorithms are developed. In...
A sequential cooperative spectrum sensing algorithm is developed for multi-channel cognitive radio (CR) systems. Each CR quantizes the local observations to a single-bit datum per sample per channel, and relays the data sequentially to the fusion center for joint decision. The optimal trade-off between the sensing time and the sensing reliability is sought with the objective of maximizing the overall...
Sequential sensing algorithms are developed for OFDM-based hierarchical cognitive radio (CR) systems. Secondary users sense multiple sub-bands simultaneously for possible spectrum availabilities under hard miss-detection constraints to prevent interference to the primary users. Accounting for the fact that the sensing time overhead can often be significant, a performance metric is developed based...
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