Joint resource allocation and routing optimization for spectrum aggregation based CRAHNs

Abstract

As an integration of spectrum aggregation (SA) and cognitive radio Ad Hoc networks (CRAHNs), SA-enabled CRAHNs are capable of utilizing non-continuous spectrum components and is promising in improving the network performance. However, existing research on CRAHNs mainly assuming of an ideal spectrum sensing while ignoring the false alarm probability, resulting in an inaccurate capacity characterization. Hence, in this paper, we propose a more accurate capacity characterization while the detection and false alarm probability are considered. Moreover, we propose the joint optimization model for SA-enabled CRAHNs constrained by QoS requirements of primary users and network resource allocation. We propose the prim-dual method to decompose this problem into two sub-problems: a physical (PHY) layer sub-problem on CC assignment and power allocation, and a network layer sub-problem on route selection. Besides, these two sub-problems are coupled on the link capacity constraint. For sub-problem at PHY layer, we propose the genetic algorithm to obtain the optimal CC assignment and successive convex approximation method to the find the optimal power allocation. For sub-problem at network layer, we propose to apply the standard convex method to find the optimal solution. The numerical simulations demonstrate that network throughput can be improved by increasing the number of CCs. The obtained network throughput outperforms algorithms that without power control, spectrum aggregation or route optimization.