An Energy-Efficient DL-Aided Massive Multiple Access Scheme for IoT Scenarios in Beyond 5G Networks

In view of the challenges foreseen in futuristic massive IoT (mIoT) scenarios, characterized by a huge deployment of energy-constrained IoT devices, we propose an efficient next-generation multiple access (NGMA) scheme where several innovative solutions combine and integrate. First, we aim to maximize the spectral efficiency of the physical uplink-shared channel (PUSCH) by adopting the most appropriate nonorthogonal multiple access (NOMA) technique and by introducing an efficient contention-based approach for data transmission in the unused PUSCH resources. Second, on the basis of the traffic load, the proposed scheme dynamically sets the UpLink (UL) radio resources dimensioning by searching the optimal tradeoff between lowering the collision probability in the physical random access channel (PRACH) and providing enough radio resources in the PUSCH to permit the data transmission to all the succeeded access requests. Third, it is enriched by a series of strategic procedures to make feasible the traffic load estimation, even when the PRACH is in overload condition. Fourth, we exploit artificial intelligence technologies to further optimize the performances obtained. The proposed scheme is compared with other benchmark schemes available in the literature. It outperforms them in the most important metrics for the mIoT scenario (i.e., spectral efficiency and energy consumption), especially in high load conditions, which is the expected requirement for Beyond 5G and 6G networks.