Robust Energy Efficiency Optimization for SWIPT-enabled Heterogeneous NOMA Networks

With the increasing requirements of high data rates and large connectivity, the application of the non-orthogonal multiple access (NOMA) technique in heterogeneous networks (HetNets) has become an inevitable trend for 5G communication systems in order to achieve good spectrum efficiency and system throughput. Moreover, the energy-constrained low-power nodes (e.g., small cell users) are the bottlenecks for restricting the overall network performance. To improve the system throughput and prolong the operation life of the energy-limited networks, a robust energy efficiency (EE) maximization problem is addressed for simultaneous wireless information and power transfer (SWIPT)-enabled heterogeneous NOMA networks. Considering the co-channel interference and the cross-tier interference, the resource allocation problem is formulated as a non-convex multivariable fractional programming problem under the time-switching energy harvesting mode. It is challenging to obtain the optimal solution. By using the min-max probability machine approach, the probabilistic interference constraint and the outage rate constraint are transformed into the convex ones. Based on the ellipsoidal uncertainty sets, the worst-case harvested energy is converted into a deterministic one. The obtained convex optimization problem is solved by CVX tools. Simulation results show the superiority of the proposed algorithm by comparing with the non-robust algorithm.