Alignment of Heterogeneous Packet Lengths for Random Access in 5G Massive Machine Type Communication.

Random access plays a critical role in massive machine type communication networks that consist of a myriad number of heterogeneous Internet of Things devices to meet the demand of applications in a large geographical area. In this paper, we propose using packet length alignment for framed slotted Aloha, where packets are assigned chunks of time slots according to the packet lengths generated by the devices. The packet length-dependent alignment ensures that the collision windows are relatively small, whereas the devices with varying packet lengths view the frame partitioned into chunks of time slots differently. In this paper, packet length alignment is used in combination with packet squeezing to enhance the throughput in framed slotted Aloha. Furthermore, the age of information (AoI) can be easily included in the proposed approach to emphasize the importance of data freshness. In the performance evaluation, the analytical model of the proposed packet length alignment along with packet squeezing demonstrate that the throughput of framed slotted Aloha in the context of massive machine type communications in 5G can reach up to 0.9. A simplified AoI model can be easily implemented with the proposed approach. [ABSTRACT FROM AUTHOR]