Energy-Efficient Resource Allocation in NOMA Heterogeneous Networks with Energy Harvesting

Abstract

Non-orthogonal multiple access (NOMA) and heterogeneous networks are promising candidate technologies to meet the exponential growth of mobile data. However, because the wireless network is becoming more and more dense, the energy consumption problem has become increasingly prominent and severe. This paper studies the resource allocation problem of NOMA heterogeneous small cell networks with energy harvesting. By decoupling subchannel allocation and power control, a low complexity subchannel matching algorithm is designed, and a power optimization algorithm is proposed based on Lagrange dual method. The simulation results demonstrated the convergence and effectiveness of the proposed algorithms in terms of the system energy efficiency.