RSMA-Aided Coded Random Access With Adaptive Traffic Load and Traffic Load Estimation for Overload Future IoT

This paper considers a contention-based modern random access for overload future massive Internet of Things (IoT), where a rate-splitting multiple access (RSMA)-aided coded random access (CRA) is proposed. To facilitate RSMA in random access, uncoordinated uplink RSMA is proposed as signal transmission in the physical layer, and the CRA protocol is exploited as packet behavior in the medium access control (MAC) layer. Furthermore, adaptive traffic load (ATL) and traffic load estimation (TLE) schemes are proposed considering overload IoT. The ATL controls the number of contentions in a MAC frame by setting the access probability of IoT devices. By accurately analyzing the collision model in power allocation and rate control, a uniform distribution is used to model the active users who selected power transmission in RSMA, and the asymptotic throughput using density evolution is derived. The proposed RSMA-aided CRA with ATL (ATL-RSMA-CRA) is validated using computer simulations and compared with two baseline RA schemes based on slotted ALOHA and nonorthogonal multiple access (NOMA)-aided CRA. Finally, our numerical results highlight that the proposed ATL-RSMA-CRA yields significantly higher throughput and stable throughput at high traffic load.