In this paper, we focus on cognitive wireless networking, where a primary wireless network (PWN) is co-located with a cognitive (or secondary) wireless network (CWN). The shared frequency spectrum is divided into disjoint "subchannels" and each subchannel is "freely" assigned (in a unique way) to a node of the PWN, denoted as primary user equipment (PUE). We assume that the nodes of the CWN, denoted as cognitive user equipments (CUEs), cooperate to sense the frequency spectrum and estimate the idle subchannels which can be used by the CWN (i.e., assigned to CUEs) without interfering the PWN. The sensing correlation among the CUEs is exploited to improve the reliability of the decision, taken by a secondary fusion center (FC), on the occupation status (by a node of the PWN) of each subchannel. In this context, we compute the mutual information between the occupation status and the observations at the FC, with and without knowledge of the positions of the nodes in the network, showing a potential significant benefit brought by this side information. Then, we derive the fusion rules at the FC: our numerical results, in terms of the network-wise probabilities of missed detection (MD) and false alarm (FA) at the secondary FC, indicate a significant performance improvement when knowledge of the CUEs' positions is available at the secondary FC, confirming the mutual information-based theoretical prediction.
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