Tsn-IoT Achieves Prioritized Access and Connectivity for Dense IoT Networks

Researchers are tackling the critical issue of reliable connectivity and prioritised data transmission within increasingly dense Internet of Things (IoT) networks. Shama Siddiqui from DHA Suffa University, Anwar Ahmed Khan from Millennium Institute of Technology and Entrepreneurship, and Nicola Marchetti from Trinity College Dublin, alongside their colleagues, present a novel framework , TSN-IoT , that leverages Non-Orthogonal Multiple Access (NOMA) to overcome synchronisation challenges caused by node movement or unreliable GNSS signals. This research is significant because it moves beyond conventional synchronisation methods, integrating Precision Time Protocol with distributed NOMA-based techniques to facilitate prioritised data delivery in complex, heterogeneous IoT environments, demonstrated effectively through a healthcare application and simulations showing substantial performance gains over existing OFDMA approaches.

NOMA. Researchers engineered this system to overcome synchronization disruptions caused by node movement or unreliable Global Navigation System (GNSS) signals, a common issue in obstructed or electromagnetically noisy environments. This innovative algorithm aimed to improve synchronization speed and scalability while maintaining low computational complexity, making the framework suitable for large-scale beyond-5G and 6G networks. Researchers harnessed semi-grant free uplink NOMA, scheduling some users with grant-based access while allowing others to transmit without explicit grants, combining reliability with low latency. Unlike previous work focusing on single tiers, the TSN-IoT framework utilizes NOMA for both synchronization and data transmission, enabling data transfer from Sensor Nodes (SNs) to the Base Station (BS) via Cluster Heads (CHs) and Access Points (APs).
The team detailed sub-band allocation for each communication tier, integrating PTP and distributed synchronization alongside the data transmission mechanism. Experiments revealed that TSN-IoT significantly improves synchronization opportunities and enables parallel transmissions over the same sub-carrier, offering a substantial advancement over traditional methods. Data shows the framework’s ability to handle dense IoT scenarios where synchronization may be disrupted by node movement or unreliable Global Navigation System (GNSS) signals, a common issue caused by obstructions, fading, or electromagnetic interference. The TSN-IoT framework’s design explicitly addresses the need for efficient multiplexing techniques to meet the demands of delay and reliability in increasingly dense IoT deployments. Researchers recorded that the framework’s distributed synchronization component is particularly effective in scenarios where GPS access is limited or unavailable, relying on iterative timing updates from neighbouring nodes to achieve network-wide synchronization even with hundreds of devices.

Measurements confirm that this approach minimizes signalling overhead, as nodes only need to negotiate power levels occasionally, unlike orthogonal access systems requiring frequent coordination. The breakthrough delivers a hybrid approach combining distributed synchronization and NOMA, reducing the delay associated with exchanging synchronization information among nodes. Tests prove that the framework’s integration of NOMA facilitates efficient spectrum utilization by using varying power levels to transmit data streams with different Quality of Service (QoS) requirements or priority levels. The study highlights the framework’s scalability and low computational complexity, making it suitable for large-scale beyond-5G and 6G networks where centralized coordination is impractical. Specifically, the TSN-IoT framework addresses a gap in existing architectures by providing a unified, multi-tier model for dense IoT networks, incorporating sensor nodes, cluster heads, and small base stations, elements often missing in previous designs.