Data Aggregation Based Massive Machine-Type Communications Coexisting With Human-to-Human Communications: Mechanism Design and Performance Analysis

To integrate efficiently the emerging massive machine-type communications (mMTC) into the fifth generation (5G) and beyond 5G (B5G) cellular networks, we design a two-hop data aggregation and forwarding mechanism for the machine-type communications (MTC) to coexist with the traditional human-to-human (H2H) communications. Specifically, by sharing the channel resources originally allocated to H2H user equipments (HUEs), the activated MTC devices (MTCDs) first send small-sized data packets to the associated MTC gateways (MTCGs). Then, the MTCGs aggregate the received data packets and forward them to the base station (BS). The data transmission of MTCGs and HUEs are scheduled by the BS such that there is a competition relationship between the forwarding MTCGs and HUEs. To limit the influence of mMTC on the H2H service, we set different scheduling weights for the forwarding MTCGs and HUEs to control the transmission opportunities of the two types of services. Based on the stochastic geometry (SG) theory, we develop an analytical framework to characterize signal-to-interference ratio (SIR) during the intra-group aggregation and MTCG forwarding phase. Using this SIR analytical framework, we derive the data aggregation success probability of each MTCD and the average throughput of each forwarding MTCG. We also conduct simulations to evaluate the performance of the mMTC and H2H service under varying parameter settings, which indicates the trade-off between the system settings of the data aggregation phase and MTCG forwarding phase.