Grant-Free Power Allocation for Ultra-Dense IoT: A Mean Field Perspective

Grant-free access, in which each Internet-of-Things (IoT) device delivers its packets through a randomly selected resource without spending time on handshaking procedures, is a promising solution for supporting the massive connectivity required for IoT systems. In this paper, we explore grant-free access with multi-packet reception capabilities, with an emphasis on ultra-low-end IoT applications with small data sizes and energy usage constraints. We propose a power allocation scheme that integrates the IoT device's traffic and energy budget by using stochastic geometry framework and mean-field approximation to model and analyze mutual interference among active IoT devices. We also derive a Markovian model to capture and track the IoT device's queue length, and derive the successful transmission probability at steady state. Simulation results illustrate the optimal power allocation strategy and show the effectiveness of the proposed approach.

Automated summary

This paper explores grant-free access with multi-packet reception capabilities, focusing on ultra-low-end IoT applications with small data sizes and energy usage constraints. It proposes a power allocation scheme that integrates the IoT device's traffic and energy budget using stochastic geometry framework and mean-field approximation. It also derives a Markov model to capture the IoT device's queue length and the successful transmission probability at steady state.