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It is known that in addition to spectrum sparsity, spatial sparsity can also be used to further enhance spectral utilization in cognitive radio systems. To achieve that, secondary users (SUs) must know the locations and signal strength distributions (SSDs) of primary users' base stations (PUBSs). Recently, a group sparse total least squares method was developed to cooperatively sense the PUBSs' signal...
Based on the concept of sparse Bayesian learning, an expectation and maximization algorithm is proposed for cooperative spectrum sensing and locationing of the primary transmitters in cognitive radio systems. Different from typical approaches, not only the signal strength, but also the number and the radio power profiles of the primary transmitters are estimated, which greatly facilitates resource...
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