Robust Max-Min Fairness Energy Efficiency in NOMA-based Heterogeneous Networks

Fairness among different users and system robustness are key issues in the future communication network design. A robust max-min fairness energy efficiency (EE) maximization problem in a downlink non-orthogonal multiple access (NOMA) heterogeneous network is studied when channel state information and interference power are uncertain. A worst-case EE of the small cell is maximized by jointly optimizing the transmit power and cell association under the bounded channel uncertainty model, subject to constraints on the cross-tier interference power, maximum transmit power, and the minimum rate requirement of each small-cell user. The formulated robust max-min fairness EE problem is a mixed-integer and non-convex programming problem with infinite inequality constraints. An iterative resource allocation algorithm is designed based on the proposed power allocation and cell association scheme. Simulation results demonstrate the effectiveness of the proposed robust resource allocation scheme and its improvement over existing schemes.