Hybrid Interference Alignment (IA) Scheme for Improving the Sum-Rate of HetNet Users

In this paper, we propose a hybrid Interference Alignment (IA) scheme for early detection of signal leakage to improve the sum rate of user cells in Heterogeneous Networks (HetNets). In the hybrid sceheme, Gaussian-Newton (GN) model is employed for estimating the signal at the receiver end. This model classifies the signal in Jacobian and Hessain Matrix representations to detect the interference and hence to improve the degree of freedom (DOF). The update variations are precisely classified using the vector representations using the above matrix representations to detect the leakage through classification at an early stage. This helps to improve the sum rate in HetNet environment with earlier convergence. The proposed hybrid IA in HetNets is found to detect leakage at a less convergence so as to improve sum rate.