In this paper, we address the problem of energy efficient resource optimization for downlink transmission in user-centric ultra-dense networks enabled by wireless access via nonorthogonal multiple access and wireless backhaul via beamforming. Our objective is to maximize the system energy efficiency by optimizing user/access point scheduling, subchannel assignment, and power allocation jointly. The problem is formulated as a nonconvex mixed-integer nonlinear programming problem which is NP-hard. We then transform it into a convex subproblem using the sum-of-ratios decoupling and the iterative successive convex approximation method. An overall algorithm is further developed to solve the subproblem iteratively. Simulation results show that the proposed algorithm has improved the system-wide energy efficiency significantly when compared to the benchmark scheme.
Profitable and Energy-Efficient Resource Optimization for Heterogeneous Cloud-Based Radio Access Networks
