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To improve energy efficiency and reduce the interference to macro users (MUs), this paper investigates the robust resource allocation (RA) problem for maximizing the interference efficiency of users (i.e., total rate/sum interference) in heterogeneous networks. Under perfect channel state information (CSI), the considered RA problem is formulated as a multivariate nonlinear programming problem with constraints on the maximum interference power of MUs, the minimum rate requirement of each femto user, and the maximum transmit power of the femto base station. The original fractional programming problem is converted into a convex optimization problem by using Dinkelbach’s method, the logarithmic transformation method, and the successive convex approximation method, where the closed-form solution is obtained with the Lagrangian dual approach. Moreover, with imperfect CSI consideration, the original problem is reformulated as a robust RA problem that is transformed into a deterministic and convex optimization problem by using an inequality transformation approach. In addition, the computational complexity and the cost of robustness are also analyzed. The simulation results verify that the proposed algorithm has better interference efficiency and robustness by comparing with the existing algorithms.

Optimal and Robust Interference Efficiency Maximization for Multicell Heterogeneous Networks