Optimal Detection In The Presence Of Non-Gaussian Jamming
Khalid Almahorg, Ramy Gohary
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SPS
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We consider a scenario in which a transmitter sends complex multidimensional symbols to a receiver in the presence of a proactive continuous jammer emitting a zero-mean complex Gaussian signal over an unknown complex Gaussian channel. We develop the optimal maximum likelihood (ML) detector for cases in which the receiver has full channel state information (CSI), full channel distribution information (CDI), or partial CDI about the transmitter channel. The jammer CDI is either partially or fully available at the receiver. We identify cases in which the non-Gaussian signals resulting from the jammer’s transmission can be approximated by Gaussian signals to reduce the computational cost without compromising optimality of detection. Furthermore, we identify cases in which the Gaussian approximation ML detector is not equivalent to the exact ML detector. In these cases, we show that the advantage of the exact ML detector over the Gaussian approximation one can be significant.
Chairs:
Wei Yu