In this paper, we investigate a spectrum sensing algorithm for detectingspatial dimension holes in Multiple Inputs Multiple Outputs (MIMO)transmissions for OFDM systems using Compressive Sensing (CS) tools. Thisextends the energy detector to allow for detecting transmission opportunitieseven if the band is already energy filled. We show that the task describedabove is not performed efficiently by regular MIMO decoders (such as MMSEdecoder) due to possible sparsity in the transmit signal. Since CSreconstruction tools take into account the sparsity order of the signal, theyare more efficient in detecting the activity of the users. Building onsuccessful activity detection by the CS detector, we show that the use of aCS-aided MMSE decoders yields better performance rather than using eitherCS-based or MMSE decoders separately. Simulations are conducted to verify thegains from using CS detector for Primary user activity detection and theperformance gain in using CS-aided MMSE decoders for decoding the PUinformation for future relaying.
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