Autonomous Interference Mapping for Industrial Internet of Things Networks Over Unlicensed Bands: Identifying Cross-Technology Interference
Simone Grimaldi, Aamir Mahmood, Syed Ali Hassan, Mikael Gidlund, Gerhard P. Hancke
Abstract
The limited coexistence capabilities of current Internet of Things (IoT) wireless standards produce inefficient spectrum utilization and mutual performance impairment. The problem becomes critical in industrial IoT (IIoT) applications, which have stringent quality-of-service (QoS) requirements and very low error tolerance. The constant growth of wireless applications over unlicensed bands mandates then the adoption of dynamic spectrum-access techniques, which can significantly benefit from interference mapping over multiple dimensions of the radio space. In this article, we analyze the critical role of real-time interference detection and classification mechanisms that rely on only IIoT devices, without the added complexity of specialized hardware. The tradeoffs between classification performance and feasibility are analyzed in connection with the implementation on low-complexity IIoT devices. Moreover, we explain how to use such mechanisms for enabling IIoT networks to construct and maintain multidimensional interference maps at runtime in an autonomous fashion. Finally, we give an overview of the opportunities and challenges of using interference maps to enhance the performance of IIoT networks under interference.