Joint Scheduling and Power Adaptation in NOMA-Based Fog-Radio Access Networks

Abstract

Non-Orthogonal Multiple Access (NOMA) is a promising technology for 5G that enables each resource unit to simultaneously serve multiple users. This work evaluates the potential benefit of joint scheduling and power adaptation in NOMA- based downlink in Fog-Radio Access Networks (FRAN). We consider the downlink of a FRAN, where the Fog Access Points (FAPs) are connected to central cloud baseband units (BBUs) through capacity-constrained fronthaul links. The FAPs adopt a two-user NOMA scheme, within each resource block (RB), to serve a common set of users. The paper formulates an optimization problem which maximizes a network-wide {rate-based utility} function subject to fronthaul- capacity constraints, so as to determine both the user- to-FAP assignment and the power levels of the users served by each FAP. The main contribution of the paper is solving this mixed-integer non-convex optimization problem using a two- step centralized-distributed approach, which is aligned with FRAN operation that {aims to} %relies on partially shifting the network control to the FAPs so as to overcome delays due to fronthaul rate constraints. The assignment step is first solved at the centralized BBU pool by reformulating the problem such that the Hungarian algorithm is applicable. The power {adaptation} is then solved at every FAP using a barrier method. Simulation results show that the proposed NOMA-based algorithm outperforms conventional Orthogonal Multiple Access (OMA) algorithms, even with stringent fronthaul limitations. The proposed algorithm further shows an appreciable {performance trade-off} between the rate and fairness metrics.