Green Grant-Free Power Allocation for Ultra-Dense Internet of Things: A Mean-Field Perspective [r-libre/3288]

Nadif, Sami; Sabir, Essaid; Elbiaze, Halima, & Haqiq, Abdelkrim (In Press). Green Grant-Free Power Allocation for Ultra-Dense Internet of Things: A Mean-Field Perspective. Journal of Network and Computer Applications, In Pre. doi.org/10.1016/j.jnca.2024.103908

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Item Type:	Journal Articles
Refereed:	Yes
Status:	In Press
Abstract:	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, sporadic activity, and energy usage constraints. We propose a power allocation scheme aimed at maximizing throughput while minimizing power consumption by considering the tra!c and energy constraints of IoT devices. Our approach employs a stochastic geometry framework and mean-field game theory to model and analyze the mutual interference among active IoT devices. Additionally, we utilize a Markov chain model to capture and track the queue length of IoT devices, enabling the derivation of the transmission success probability at steady-state. The simulation results illustrate the optimal power allocation strategy and evaluate the proposed approach’s performance in terms of packet transmission success probability and average delay.
Official URL:	https://www.sciencedirect.com/science/article/abs/...
Depositor:	Essaid, Sabir
Owner / Manager:	Sabir Essaid
Deposited:	03 Jun 2024 12:59
Last Modified:	03 Jun 2024 12:59

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