Macrocell-femtocells resource allocation with hybrid access motivational model

摘要

Femtocell technology has emerged as an efficient cost-effective solution not only to solve the indoor coverage problem but also to cope with the growing demand requirements. This paper investigates two major design concerns in two tier networks: resource allocation and femtocell access. Base station selection together with dual bandwidth and power allocation among the two tiers is investigated under shared spectrum usage. To achieve fair and efficient resource optimization, our model assumes that the hybrid access mode is applied in the femtocells. The hybrid access mode is beneficial for system performance as (1) it lessens interference caused by nearby public users, (2) it allows public users to connect to near femtocells and get better Quality of Service (QoS) and (3) it increases system capacity as it allows the macrocell to serve more users. However, femtocells' owners can behave selfishly by denying public access to avoid any performance reduction in subscribers' transmissions. Such a problem needs a motivation scheme to assure the cooperation of femtocells' owners. In this paper, we propose a game-theoretical hybrid access motivational model. The proposed model encourages femtocells' owners to share resources with public users, thus, more efficient resource allocation can be obtained. We optimize the resource allocation by means of the Genetic Algorithm (CA). The objective of the formulated optimization problem is the maximization of network throughput that is calculated by means of Shannon's Capacity Law. Simulations are conducted where a modified version of the Weighted Water Filling (WWF) algorithm is used as a benchmark. Our proposed model, compared to WWF, achieves more efficient resource allocation in terms of system throughput and resources utilization.