Cross-Layer Resource Allocation in NOMA Systems with Dynamic Traffic Arrivals

Non-orthogonal multiple access (NOMA) has become a potential candidate to satisfy the heterogeneous demands in the fifth generation of wireless communication systems. With the optimization on the resource allocation, NOMA can further enhance the system performance. This paper proposes a cross-layer resource allocation framework for downlink NOMA systems. The problem is formulated as a stochastic problem to minimize the long-term total power consumption with dynamic traffic arrivals and time-varying channel under limited feedback. Then, this problem can be transformed to a rate control problem and a mixed-integer programming resource allocation problem solved at each time slot based on the Lyapunov optimization. To reduce the computational complexity, we devise an efficient suboptimal resource allocation algorithm with the dynamic penalty factor. The simulation results show that our proposed algorithms can reduce the power consumption compared with the two baseline algorithms while satisfying the QoS requirements.