On the Throughput of NOMA-ALOHA in Massive IoT With Sparse Active Users

The use of non-orthogonal multiple access (NOMA)-assisted ALOHA can effectively improve the throughput of random access. In this letter, we study the throughput of NOMA-ALOHA for massive Internet of Things (IoT) with sparse active users, i.e., only a small number of active users require simultaneous transmissions in an access slot. Since all active users independently choose the power level at the identical distribution, the number of active users in each power level follows binomial distribution. Firstly, the upper and lower bounds on the throughput of NOMA-ALOHA are derived by relaxing and limiting the higher-power dominance characteristic. Then, with the obtained bounds, the optimal load (optimal number of active users) is analyzed to maximize the throughput. Finally, the simulation results are presented to demonstrate the accuracy of the derived throughput expressions and optimal load.