Interference-limited Resource Allocation Algorithm in Cognitive Heterogeneous Networks

Abstract

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput.Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity.Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint.We decompose the resource allocation problem into subcarrier allocation and power allocation.In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method.Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.