QoE-aware NOMA user grouping in 5G mobile communications using a multi-stage interval type-2 fuzzy set model

The user grouping has a significant impact on the performance of non-orthogonal multiple access (NOMA) systems. The present work is focused on downlink NOMA user grouping leveraging the type-2 fuzzy set (T2FS). The main drawback of conventional user grouping methods is low efficiency for middle users which degrades the overall system performance. To overcome this problem, a 2-step user grouping process is proposed that includes identifying group candidates and selecting the most qualified one. The first step is handled by introducing a group membership competency criterion based on T2FS modeling due to its capability to handle extra uncertainty in real-world phenomena. The second step involves adding the most qualified candidate to the desired group, given the additional power imposed on the group. The key contribution of the paper is twofold: (i) it affords a multi-stage structure to evaluate the competency of users to join a particular group relying on T2FS modeling. It allows groups of different sizes to be formed, depending on the network channel status and quality of experience (QoE) requirements, and (ii) the additional power imposed on the group is exploited as a measure to select the final group. In this regard, the analysis of interference that each user brings to others in the same group is taken into account. The performance of the proposed scheme is evaluated by simulations and compared with other methods. The obtained results indicate the efficiency of the proposed approach in terms of total power consumption and symbol error rate.