Robust Energy-Efficient Optimization for Heterogeneous Networks with Residual Hardware Impairments

Abstract

Resource allocation is very important for achieving interference suppression and protecting the quality of service of users in heterogeneous networks (HetNets). However, the existing works with perfect channel state information (CSI) and ideal hardware ignored the impact of channel uncertainties and hardware impairments on system performance. In this paper, we design a robust secure resource allocation algorithm with imperfect CSI to achieve the energy efficiency (EE) maximization of femtocell users for a two-tier downlink HetNet with multiple passive eavesdroppers, where the residual hardware impairments are considered at the transceivers. The formulated EE problem is non-convex with the consideration of the maximum transmit power constraint of each base station, the cross-tier interference power constraint, as well as the secure rate constraint. By using the worst-case approach and successive convex approximation, the resource allocation problem with the infinite-dimensional constraints is converted into a convex one which is efficiently solved by using convex optimization theory. Simulation results verify that the proposed algorithm has a higher EE and causes less interference power to macrocell users by comparing it with the baseline algorithms.