To improve energy efficiency and reduce the interference to macro users (MUs)

this paper studies robust resource allocation for interference efficiency (IE) maximization in heterogeneous wireless networks. Firstly

considering the maximum interference power constraint of MU

the minimum rate requirements of femto users (FUs) and the maximum transmit power constraint of femto base station

the resource allocation problem is modeled as a multivariate nonlinear programming problem. Secondly

under bounded channel uncertainties

the original fractional programming problem is converted into a convex optimization problem by using Dinkelbach's method

logarithmic transformation and the successive convex approximation

where the analytical solution is resolved by using Lagrangian dual approach. And computational complexity and the cost of robustness are also analyzed. Finally

simulation results show that the proposed algorithm has better IE and robustness.