Cross-layer resource allocation approach for multi-hop distributed cognitive radio network

In multi-hop distributed cognitive radio network, link layer resource allocation must consider the information about number of hops packets have already traveled in the network in order to optimize the overall resource utilization. The loss of a packet after traveling some hops results in waste of all the resources allocated to it in previous hops. The existing resource allocation schemes may not provide optimal resource utilization in such network as this issue has been greatly ignored. Therefore, in this paper, we propose a scheme to allocate transmit power to different packets favoring those which have traveled more hops before reaching a particular node. We present a cross-layer approach in which link layer gets the hop-count information from network layer module. Distributed implementation is possible with the proposed scheme because each node can access this information. We formulate the power allocation problem as a convex optimization problem and obtain its analytical solution by using Lagrangian duality. Simulation results show that the proposed scheme is capable of minimizing wastage of network resources used by packets in their previous hops without any degradation in throughput and outage performance.