This paper addresses the optimization of distributed compression in a sensor network with partial cooperation among sensors. The widely known Chief Executive Officer (CEO) problem, where each sensor has to compress its measurements locally in order to forward them over capacity limited links to a common receiver is extended by allowing sensors to mutually communicate. This extension comes along with modified statistical dependencies among involved random variables compared to the original CEO problem, such that well-known outer and inner bounds do not hold anymore.
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