Abstract

The number of hops between source node and destination node is a key parameter in studying multi-hop wireless networks. Although hop count in wireless ad-hoc networks (AHNs) has been studied in the literature, no works on investigating the hop count characteristics in cognitive environments have been carried out. In this paper, we model cognitive radio ad-hoc networks (CRAHNs) as geometric random graphs and then propose a framework for studying the hop count distribution and correlated connectivity of communication path between two arbitrary nodes in CRAHNs with shadow fading. The framework consists of an algorithm and a methodology. Specifically, from the perspective of geometric random graph, the algorithm finds all possible paths between two arbitrary nodes and returns the hop count of the shortest path between them by using the global location information of nodes, i.e. primary users – PUs and secondary users – SUs, and the active states of PUs as input data. Meanwhile, through huge number of random network topology trials, the methodology returns the hop count distribution and connection status of communication path between two arbitrary nodes in CRAHNs with shadow fading. From the evaluating scenarios in this paper, important features of hop count distribution and connectivity and their correlating relationship in CRAHNs with shadow fading are revealed and compared with those in AHNs and in CRAHNs without shadow fading.

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