Compressive Sensing based Intercell Interference Channel Estimation for Heterogeneous Network

Heterogeneous network (HetNet) uses two- tier network architecture in which an unplanned femtocell layer is randomly deployed with no coordination between the coexisting macrocell layer. Both layers share the same spectrum so that spontaneous intercell interference is unavoidable and needs to be identified and canceled afterwards. In order to address the subsequent interference management, this paper proposes an intercell interference channel estimation scheme for HetNets using compressive sensing (CS). Applying CS to analog orthogonal frequency division multiple access (OFDMA) signals not only achieves lower cost sub- Nyquist sampling but also reduces interference by spreading out the energy of reference symbols of interference link that overlaps data symbols of desired link. Our scheme enhances both desired data symbols and interference channel by canceling the estimations of each other from the received signal in turn iteratively. Simulation results show that our scheme obtains accurate estimation of interference channel and is robust to variations in multipath number and signal- tointerference ratio (SIR).