Interference alignment in overlay cognitive radio femtocell networks

Abstract

An overly multiple-input–multiple-output cognitive radio femtocell network consisting of P macrocell users equipments (MUEs), known as primary users (PUs), and K femtocell access points (FAPs), known as secondary users is considered in which femtocell user equipments (FUEs) operate in the closed access mode. Each FAP is equipped with a CR device to perform the local channel state information. The main objective is to maximise the average sum-rate of the macrocell base station (MBS), as well as significantly increase in the FUE’s rate with negligible reduction in the PU’s rate for moderate-to-high signal-to-noise ratio regimes. This goal is achieved by proposing an opportunistic interference alignment (OIA) technique using the threshold-based beamforming (TBF) algorithm. Assuming that the receiver and the transmitter of the PU have perfect knowledge of their own channel matrices, the authors use the maximum eigenmode beamforming algorithm for the transmission between the MBS and its MUEs, where the PU releases some of its eigenmodes for the FAPs, in order to transmit signals for their corresponding FUEs over them. To decide on the presence or absence of MUEs, they use the generalised likelihood ratio test detector which is more robust to the noise uncertainty than the energy detector. The proposed OIA-TBF protocol allows the opportunistic FAPs to send data for FUEs and use the same frequency band of a preexisting MUE to guarantee that no interference is imposed on the MUE’s performance for such a network.