Cross-Layer Optimization for Spectrum Aggregation-Based Cognitive Radio Ad-Hoc Networks

Abstract

Spectrum aggregation provides a promising approach to improve the network capacity for Cognitive Radio Ad-Hoc Networks (CRAHNs). Resource allocation for spectrum aggregation-based CRAHNs has become one of the main issues. In this paper, we propose a cross-layer optimization for CRAHNs with the spectrum aggregation. The main objective of our paper is to maximize the network throughput under the network resource constraints. In this regard, we investigate the joint optimization for channel allocation, power control and routing under signal-to-interference-and- noise ratio (SINR) model. This cross-layer optimization problem is decomposed into two sub-problems: a resource allocation at the physical (PHY) layer, and a throughput optimization at the network layer. At the PHY layer, the particle swarm optimization algorithm is proposed to find the suboptimal solution, then at the network layer, linear programming is applied to evaluate the particle's fitness value for throughput maximization. The simulation results demonstrate that the joint optimization of channel allocation and power control is an effective way to improve network throughput, especially when the network has sufficient power supply.