Resource Allocation for Femtocell Networks by Using Chance-Constrained Optimization

Deploying femtocells underlaying macrocells is a promising way to improve the capacity and enhance the coverage of a cellular system. However, such a heterogeneous network also gives rise to cross-tier and intra-tier interference issue that should be addressed properly in order to acquire the expected performance gain. In this paper, we study the resource allocation (RA) problem in a two-tier Orthogonal Frequency Division Multiplexing Access (OFDM)-based cellular networks, where the femtocells that employ closed access strategy to share subchannels with the macrocells are equipped with cognitive radio (CR) function to identify radio environment so as to choose the subchannels that can yield less interference to the macrocell users in the coverage of the femtocells. Our optimization task is to maximize the sum throughput of the femtocell users under the consideration of imperfect spectrum sensing, while controlling the interference to the MUs under their bearable thresholds in the sense of probability resulting from imperfect channel state information. We introduce a conservative convex approximation to the formulated problem and develop a fast algorithm to solve it by exploiting its structure. Simulation results show our proposed RA scheme can improve the system throughput with almost no changes of the infrastructure of the cellular network.