Joint Traffic Splitting and Spectrum Resource Allocation in Heterogeneous Cognitive Wireless Networks

This paper investigates the resource allocation problem in heterogeneous cognitive wireless networks (HCWNs), with the objective of improving the end-to-end quality of service (QoS) performance for the communication session which is based on multiple radio access technologies (Multi-RATs). The cognitive wireless networks (CWNs) share spectrum resource with primary users. The users with Multi-RATs applied transmit data through multiple paths by splitting the arrival packets to different access points in HCWNs. A mathematical model for minimizing the end-to-end delay with joint consideration of traffic splitting and spectrum resource allocation is formulated, and an algorithm is proposed by iteratively optimizing the traffic splitting and spectrum resource allocation parameters. During each iteration in the proposed algorithm, a tradeoff between the performance and complexity can be achieved. Simulation results show that the proposed algorithm iteratively decreases the end-to-end delay and outperforms conventional algorithms in QoS performance and spectrum utilization.