Adaptive User Pairing With Non-Orthogonal Medium Access Choices for Balanced Coexistence of Mission-Critical and eMBB Services in Cellular IoT

This paper investigates adaptive user pairing (UP) under different non-orthogonal medium access choices in 5G-and-beyond cellular IoT networks to balance the uplink performance of mission-critical (MC) and enhanced mobile broadband (eMBB) services. Our objective is to enhance eMBB rates while ensuring quality of service (QoS) for MC users, assessed through average age of information (AoI) and peak AoI (PAoI) violation probabilities. By deriving a signal-to-noise ratio (SNR) gap threshold between a pair of eMBB and MC users, we identify optimal access scheme—puncturing, non-orthogonal multiple access (NOMA), or rate-splitting multiple access (RSMA)—with respect to activation probability $(p_{m})$ and cellular network radius. By using this derived threshold, we design an adaptive pairing algorithm that achieves near-optimal QoS for MC users and maximizes eMBB data rates. To realize different spatial associations among users in the cell, the proposed pairing strategy for eMBB and MC services is evaluated for three user distributions around the base station: concave (eMBB users concentrated near the BS), uniform (evenly spread eMBB and MC users), and convex (MC users concentrated near the BS). The extensive numerical analysis of the proposed solution demonstrates significant performance gains over random and traditional NOMA-based pairings, especially under concave scenarios. In concave distributions, our strategy reduces MC users’ QoS outage by 85% at $p_{m} = 0.1$ , achieving zero outage for $p_{m} \geq 0.3$ . Uniform and convex distributions confirm method robustness, maintaining low or zero outage probabilities across all $p_{m}$ values. We also analyzed the impact of network radius and MC user activation probabilities on access scheme selection. Results show that RSMA generally outperforms other multiple access schemes in terms of eMBB rate, but NOMA exhibits superior performance compared to RSMA and puncturing in larger networks.