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.

I. Introduction

Due to the rapid development of mobile Internet and Internet of Things, many applications with variant demands are expected to be satisfied for the fifth-generation (5G) wireless communication systems. Recently, non-orthogonal multiple access (NOMA) has attracted considerable attention to enhance the system capacity and spectral efficiency. In this paper, we focus on the power domain NOMA (PDNOMA), which is commonly used to serve multiple users at the same time and frequency domain with different power levels. Typically, for a PD-NOMA system, superposition coding (SC) is adopted at the transmitters to transmit information of multiple users simultaneously, while successive interference cancellation (SIC) is enabled at the receivers to suppress the inter-user interference.