Fast Adaptive S-ALOHA Scheme for Event-driven M2M Communications (Journal version)

TL;DR

The paper introduces a Fast Adaptive S-ALOHA (FASA) scheme that improves random access control in event-driven M2M communications by using consecutive slot statistics for faster network status estimation, reducing delay and enhancing stability.

Contribution

The paper proposes a novel FASA scheme that accelerates network status tracking in bursty M2M traffic, demonstrating stability and superior performance over traditional schemes.

Findings

FASA outperforms PB-ALOHA in reducing access delay.

FASA maintains robustness under heavy traffic loads.

FASA achieves near-optimal delay performance.

Abstract

Supporting massive device transmission is challenging in Machine-to-Machine (M2M) communications. Particularly, in event-driven M2M communications, a large number of devices activate within a short period of time, which in turn causes high radio congestions and severe access delay. To address this issue, we propose a Fast Adaptive S-ALOHA (FASA) scheme for random access control of M2M communication systems with bursty traffic. Instead of the observation in a single slot, the statistics of consecutive idle and collision slots are used in FASA to accelerate the tracking process of network status which is critical for optimizing S-ALOHA systems. Using drift analysis, we design the FASA scheme such that the estimate of the backlogged devices converges fast to the true value. Furthermore, by examining the $T$-slot drifts, we prove that the proposed FASA scheme is stable as long as the average arrival rate is smaller than $e^{-1}$, in the sense that the Markov Chain derived from the scheme is geometrically ergodic. Simulation results demonstrate that the proposed FASA scheme outperforms traditional additive schemes such as PB-ALOHA and achieves near-optimal performance in reducing access delay. Moreover, compared to multiplicative schemes, FASA shows its robustness under heavy traffic load in addition to better delay performance.