الفهرس 
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Abstract
Routing in cognitive networks is a challenging problem due to primary users’ (PU) ac¬tivities and mobility. Multipath routing is a general solution to improve reliability of con¬nections. Existing multi path routing metrics for traditional wireless networks do not take into account PUs’ activities. This work is in two folds, introducing a new routes selection metric for multi path routing in cognitive networks and proposing a channel assignment tech¬nique that suits the new routes selection metric and takes PU’s activities into account. Routes closeness, the proposed metric, favors routes that are not close to each other. Selecting non¬close routes makes them less vulnerable to PUs’ activities as it would be less possible for an active mobile PU to intenupt all the routes at the same time. The new routes closeness metric is described with a routing protocol that make use of it to enhance cognitive networks per¬formance. The channel assignment technique proposed relies on early detection of PUs. It suites the routes selection metric and can cope with speedy primary users. Simulation results show the effectiveness of the proposed routing framework in increasing connection reliabil¬ity and end-to-end throughput and decreasing end-to-end delay, especially with increasing number of PUs, PU’s mobility and secondary user’s (SUs) density.