The Internet of Things (IoT) market is currently undergoing a period of unprecedented, rapid evolution, leading to the enabling of novel and diverse applications spanning both the civilian and industrial sectors. A significant proportion of these emerging use cases, particularly those in domains such as maritime communications and forestry management, require service continuity and connectivity within geographically remote regions, where conventional terrestrial infrastructure is often absent or economically unfeasible. To bridge this coverage gap and achieve truly ubiquitous connectivity, the recent 3GPP initiative to extend 5G services into Non-Terrestrial Segments (NTNs) holds substantial promise. This expansion is crucial for ensuring that massive Machine-Type Communication (mMTC) services can be reliably provisioned globally. This paper aims to detail the progress in standardization and academic activities towards the design and deployment of NTN-based Narrowband IoT (NB-IoT) systems, which are the leading NTN mMTC enabler in the 3GPP portfolio. We will specify the challenges faced by these systems and outline the solutions proposed thus far. We conclude the paper with a discussion on already operational systems and lessons learned from their deployment and operation.

The standardized 3GPP integrated access and backhaul (IAB) technology is expected to provide a cost-efficient densification of 5G New Radio access networks. Relying on multi-hop communications, one of the critical metrics in such a system is latency. In this paper, our objective is to characterize the latency performance of the roadside deployment of an IAB system operating in the millimeter wave band (mmWave). To this end, we first utilize queuing theory tools to capture the dynamics of the buffering process at intermediate nodes with bursty arrival and service processes in the uplink and downlink directions. We then apply stochastic geometry to parameterize the model with radio part parameters. We address both user-and operator-related metrics, including packet latency and resource utilization coefficient. Our numerical results show that in roadside IAB deployment, backhaul is the main bottleneck, as the number of IAB nodes that can be supported by a donor is mainly affected by the number of users and traffic they generate, even for large bandwidths supported by 5G mmWave NR systems. The mean latency in the system scales exponentially as a function of the number of hops supported by the donor, implying that congestion in such a system is partial, affecting only the last few nodes in the chain. We demonstrate that an efficient way to adapt deployment to road traffic conditions is to fix the minimal modulation and coding scheme at the backhaul links by appropriately choosing the inter-IAB node distance. The proposed model provides a ready-to-use tool for estimating the optimal distance between IAB nodes for a given road, system traffic conditions, and number of IAB nodes associated with a single IAB donor.

The utilization of high millimeter wave (mmWave, 30–100 GHz) in 5G New Radio (NR) systems and sub-terahertz (sub-THz, 100–300 GHz) in future 6G requires dense deployments of base stations (BSs) to provide uninterrupted connectivity to the users. 3GPP Integrated Access and Backhaul (IAB) deployments that utilize wireless relay nodes offer cost-efficient densification options for these systems. However, the infrastructure that is often scaled and deployed for busy-hour traffic conditions is not used efficiently during periods when traffic demands are lower, resulting in excessive power consumption. In this work, we consider the IAB roadside deployment option and demonstrate that the deployment designed to meet traffic demands during busy-hour traffic conditions can be efficiently controlled to provide large power savings during other times of the day. To demonstrate the feasibility of the solution, we will utilize the tools of stochastic geometry and queuing theory. Our numerical results show that the dynamic switching of IAB nodes may lead to power savings of up to 40% depending on the traffic and deployment specifics. The proposed methodology also allows us to maintain the specified upper bound on the transit delay and improve the utilization of active IAB nodes.