Resource Allocation in NOMA Virtualized Wireless Networks Under Statistical Delay Constraints

For 5G wireless communication networks, low latency and high spectral efficiency are required to provide ubiquitous communication for emerging applications. In this letter, we propose a novel framework which considers these requirements simultaneously by integrating the notion of effective capacity (EC) and non-orthogonal multiple access (NOMA) into virtualized wireless networks (VWNs). At first, we consider a virtual base station architecture to achieve isolation between different service providers (slices). Then, a resource allocation design for maximization of the EC is formulated as a non-convex optimization problem which takes into account the average maximum power constraints and delay quality-of-service requirements. To strike a balance between computational complexity and system performance, we apply the successive convex approximation to the non-convex optimization problem. Subsequently, an iterative low-complexity suboptimal algorithm is proposed. Numerical results illustrate that there is a non-trivial fundamental tradeoff between delay and spectral efficiency in VWNs while NOMA provides a significant improvement in terms of EC compared to conventional orthogonal multiple access.