Matching-based distributed resource allocation in cognitive femtocell networks

Abstract

In this paper, a novel framework is proposed for joint subchannel assignment and power allocation in the uplink of cognitive femtocell network (CFN). In the studied model, femtocell base stations (FBSs) are deployed to serve a set of femtocell user equipments (FUEs) by reusing subchannels in a macrocell network. The problem of optimal allocation of subchannels and transmit power is formulated as an optimization problem in which the goal is to maximize the overall uplink throughput while guaranteeing minimum rate requirement of the served FUEs and macrocell base station (MBS) protection. To solve this problem, a novel framework based on matching theory is proposed to model and analyze the competitive behaviors among the FUEs and FBSs. Using this framework, distributed algorithms are implemented to enable the CFN to make decisions on subchannel allocation and power control. The developed algorithms are then shown to converge to stable matchings. Simulation results show that the proposed approach yields a notable performance improvement, in terms of the overall network throughput and outage probability while requiring only a small number of iterations for convergence.