Satisfaction degree and channel state difference based fair resource allocation in femto networks

In this paper, a distributed fair algorithm is proposed to address the resource allocation problem in the cognitive femtocell network. The cognitive functionalities equipped in femtocells enable us to effectively identify the qualified resource blocks (RBs), thus we can mitigate inter-cell interference. By exploiting the satisfaction degree and the channel state difference, the proposed distributed fair resource allocation (DFRA) algorithm is able to fairly assign the limited spectrum resource to the femtocells. In addition, the DFRA algorithm works in a fully distributed way which can reduce the signal overhead comparing with the centralized schemes. Simulation results demonstrate that the proposed DFRA algorithm improves the resource allocation fairness and at the same time maintain a considerable throughput performance comparing with other existing algorithms.