Reliability analysis of the random access channel of LTE with access class barring for smart grid monitoring traffic

Kalalas, Charalampos; Alonso-Zarate, Jesus · 2017 · Crossref

DOI: 10.1109/iccw.2017.7962744

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses the challenge of providing reliable connectivity for massive machine-type communication in smart grid monitoring systems using LTE networks. Specifically, it focuses on the Random Access Channel (RACH) procedure, which suffers from congestion when numerous Intelligent Electronic Devices (IEDs) attempt simultaneous access. The authors aim to analyze the reliability of the contention-based RACH mechanism enhanced with Access Class Barring (ACB), a 3GPP overload control scheme, under realistic traffic conditions typical of distribution grid monitoring. To achieve this, the authors develop a tractable analytical framework based on a two-dimensional Markov chain model. This model captures the behavior of an IED contending for channel access, incorporating states for barring, backoff, preamble transmission, and success or failure. Crucially, the study introduces a Markov Modulated Poisson Process (MMPP) traffic model to represent the varying behavior of monitoring IEDs. Unlike previous works that relied on simple Poisson processes, this model accounts for both periodic "regular" reporting and sporadic, high-rate "alarm" bursts triggered by grid events. The analytical derivation yields a closed-form expression for reliability, defined as the probability of successful access within a maximum number of allowed attempts, as a function of RACH parameters, ACB settings, and traffic characteristics. The accuracy of the analytical model is validated through extensive simulations using the ns-3 discrete-event simulator. The simulation setup involves 1,000 IEDs in a single cell, with parameters such as barring rates, backoff windows, and traffic arrival rates aligned with smart grid requirements. The results confirm that the analytical predictions closely match simulation outcomes. The performance evaluation demonstrates how reliability is impacted by monitoring traffic characteristics, such as the frequency and duration of burst traffic, as well as specific RACH and ACB configurations. The study provides insights into optimizing these parameters to support the reliable transmission of critical monitoring data. The significance of this work lies in its provision of a proactive analytical tool for estimating RACH performance in smart grid scenarios. By accurately modeling the bursty nature of IED traffic and the impact of ACB schemes, the paper enables network operators to predict congestion and adjust barring parameters to ensure reliable connectivity. This contributes to the broader goal of enhancing the observability and controllability of distribution grids through efficient cellular communication, addressing a key challenge in the integration of distributed energy resources.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• teleoperation remote driving