Resource Allocation In Femtocell Networks

Femtocell has been pointed out as a key technology in the next generation mobilecommunication. The wireless industry begins to concern the femtocell in recent years,as femtocell can improve the indoor coverage, offload traffic from macrocell layer,increase the system capacity rapidly and reduce the radiation to the users with cost.However, introducing femtocells in a cellular network presents a major challenge.Actually, despite their low transmit power, these femtocells are often seen as hostileinterferers by macrocells and can lead to significant interference which affectsharmfully the macrocells users’ quality of service. The traditional resource allocationmethods will not be applied of the hierarchical network. So, it has important researchvalue and significance to design an efficient resource allocation algorithm in thehierarchical network and improve the resource utilization and power efficiency.This paper proposes an efficient centralized resource allocation algorithm infemtocell network. The algorithm proposes the optimal subcarrier allocation and powerallocation scheme to satisfy the FUE’s QoS in guaranteeing macro users’ normalcommunication. Simulation results show that the proposed algorithm reduces theinterference of macro users and increases the spectrum efficiency. Then, we propose andanalyze an efficient interference management scheme using adaptive action learningframework where a macrocell network is under laid with femtocells. We proposefractional frequency reuse (FFR) in order to minimize the interference between thefemtocell and the macrocell. Mealwhile, we propose a distributed adaptive actionlearning algorithm to minimize the interference between femtocells. Simulation resultsshow that through adaptive action learning, femtocells not only mitigate theirinterference towards the other femtocells, but also are able to self-organize with onlypublic information feedback. Meanwhile, the overall performance of the network interms of average utility and throughput are improved.