Imagine a world where everything from traffic sensors to wearable health monitors communicates seamlessly. This vision lies at the heart of massive Machine-Type Communication (mMTC), a cornerstone of 5G and future 6G mobile networks.

In short, mMTC aims to connect an unprecedented number of Internet of Things (IoT) devices—up to one million per square kilometer—allowing them to sporadically transmit small data bursts. This capability is crucial for applications such as smart cities, autonomous vehicles, and telemedicine.

A key enabler of such massive connectivity is the adoption of grant-free communication schemes. Unlike traditional cellular systems where devices must first request permission from the base station, grant-free approaches allow devices to transmit data without prior authorization.

This simplifies communication, significantly reducing processing and power consumption at the device end as well as scheduling overhead at the base station. However, grant-free schemes have a major drawback: when many devices transmit simultaneously, the risk of data collisions increases, potentially leading to network congestion and communication failures.

To address these critical challenges, a research team led by Professor Shigeo Shioda from the Graduate School of Informatics at Chiba University has developed a comprehensive analytical model to evaluate the performance of grant-free communication schemes. Their paper, published in Computer Communications, examines the behavior of the well-known grant-free method slotted ALOHA in high-density IoT environments.

Other team members include Mr. Yuki from Chiba University and Professor Takeshi Hirai from the Graduate School of Information Science and Technology at Osaka University.

This paper is an extended version of an award-winning study that received the Best Paper Award at ACM MSWiM 2023 (26th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems), a top-tier (CORE Rank A) conference in performance modeling and evaluation of wireless communication systems.

The team's approach involved creating a sophisticated analytical model based on stochastic geometry, a mathematical tool for analyzing systems with randomly distributed elements. They assumed both base stations and IoT devices are distributed across an area in a statistically random yet predictable manner.

They then analyzed three variants of slotted ALOHA: a basic version with no special enhancements; a version incorporating interference cancellation (known as NOMA); and a version employing power control, where devices adjust their signal strength. The team focused on two key performance metrics: transmission success probability and base station throughput (the amount of data a base station can successfully receive in a given time).

Their findings revealed complex dynamics among the different ALOHA variants. While interference cancellation can boost base station throughput by up to 20% in some cases, it does not resolve the so-called near-far problem, where devices closer to the base station have a much higher chance of successful transmission than those farther away.

Surprisingly, interference cancellation proved most effective for devices at medium distances, while offering little benefit to devices very close or very far from the base station. On the other hand, although power control successfully mitigates the near-far problem and ensures fairer transmission opportunities for all devices, it leads to a substantial drop in overall network performance.

"Our study shows that ALOHA-based communication faces an inherent trade-off between two conflicting goals: fairness—devices should have equal communication opportunities regardless of their distance from the base station—and throughput—the goal of enabling a single base station to receive data from as many devices as possible," explained Professor Shioda.

"In other words, it is fundamentally difficult to achieve both fairness and maximum throughput simultaneously." This highlights a critical design challenge for future IoT networks, suggesting that relying solely on grant-free schemes may not deliver both optimal performance and fair access.

Overall, the results of this study will help guide the evolution of IoT systems. Understanding the fundamental trade-offs in communication schemes is essential for designing efficient and equitable next-generation networks.

Professor Shioda concluded: "We have revealed inherent limitations of IoT networks that will underpin future IoT-driven societies. These limitations stem from the use of grant-free communication schemes, and adopting grant-based schemes may overcome them. In future work, we plan to further explore this possibility."

Exciting applications in such societies include vehicle-to-everything (V2X) communication—where vehicles and road infrastructure exchange data—and remote healthcare using wearable devices, where high communication reliability is vital for monitoring critical health information.