Performance of Proportional Fair Scheduling for Downlink PD-NOMA Networks

In this paper, we present an analytical model for performance analysis of dynamic proportional fair scheduling (PFS) in downlink power-domain non-orthogonal multiple access (PD-NOMA) networks. In order to develop a tractable model of analytical performance, we relax the condition in the PFS optimization problem and assume an ideal NOMA system with an arbitrary number of multiplexed users per frame. We derive a closed-form solution of the optimal power allocation for the relaxed problem and design a low-complexity algorithm for joint power allocation and user set selection. With this optimal solution, the transmission performance in the ideal NOMA system is proved to be an upper bound. Based on our derivation, we develop an analytical model of the upper bound throughput performance. The analytical performance is used to estimate user data rates and overall throughput in practical NOMA systems. We conduct system-level simulations to evaluate the accuracy of our data rate estimation. The simulation results verify our analysis of the upper bound performance of PFS in NOMA systems and confirm that using its analytical results for data rate estimation guarantees high accuracy. The impact of partial and imperfect channel state information on the estimation performance is investigated as well.