# Robust Downlink Mechanism for Industrial Internet of Things Using LoRaWAN Networks
###### Abstract  
The adoption of LoRaWAN as a technology for wireless deployments in many applications, such as smart cities or industry 4.0, still presents challenges such as energy consumption, robustness, or reduced throughput in harsh, noisy scenarios. Class B is a MAC mode that allows better performance in downlink traffic but has difficulties regarding scalability and its response to channel interference. This article introduces, via simulation software, the possibility of testing deployments, adding interference sources that model industrial scenarios, and proposes an adaptive data rate (ADR) mechanism to enhance the operation for downlink and class B devices, called DROB (downlink rate optimization for class B) to study the impact of these conditions in a network with detailed event characterization. L on  
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Draft <.15, 2021</> <.15, 2021</> <. LoRa devices and managing their connection parameters, e.g., channels, bandwidth, and data encryption. Besides LoRaWAN, there are other LPWAN technologies on the market [4] like SigFox, which has a fee per device and year connected and whose technology is private, with strong restrictions for devices which can only transmit up to 140 packets of 12 bytes per day; or NB-IoT, which also relies on public cellular network operators. All the elements in LoRaWAN can be deployed as a private end-to-end network, avoiding the use of public infrastructure, and it is an open specification, which allows for some modifications and special configurations that could be of interest for industrial applications. LoRaWAN presents a fit solution for selected use cases in IIoT. It supports deploying hundreds of nodes with extended range and optimal energy consumption, with a reduced cost in network infrastructure, and works in the sub-GHz band, a different band to Wi-Fi, Bluetooth, or other popular wireless technologies, avoiding interference from these networks and presenting better noise resistance. This standard includes the implementation of an Adaptive Data Rate (ADR), a mechanism that helps adapt to channel conditions by changing devices' data rate (DR) transmission parameters, which reduces congestion in dense areas and can help save battery. Nevertheless, the current trend focuses mainly on the optimization and enhancement of the uplink traffic, that is, from nodes (end devices or ED) to the gateway (GW). This is derived from the fact that this type of network is mostly used for simple telemetry, although it has potential for much more. Many applications and use cases are appearing that present a chance to profit from the downlink part of the communication, that is, from GW (or better, application server) to the end devices. These use cases include relaying information or data analysis on zero defect manufacturing to alert personnel on the floor plant where 2.4 GHz communications are banned for security and safety reasons. In that scenario, users with end devices may have some mobility, or be spread over a large area that would otherwise require several access points and GWs. This is presented in the Zero-Defect Manufacturing Platform (ZDMP) [5] project, where devices need to receive maintenance alerts coming from a data analysis system, and the proposed LoRaWAN network is used to support data acquisition and alarm events because that company's policies restrict wireless communications to sub gigahertz bands. Once the technology and potential use cases have been selected, two challenges remain, and these are covered by this article. On one hand, deploying a high number of nodes often requires some clarification to ensure the network will operate as required. For this task, simulators are handy tools that reproduce a given scenario virtually. In this work, the popular ns3 simulator has been chosen, as it includes many models and libraries for LoRaWAN, some of them tested and used during this work [6]. On the other hand, the foremtioned ADR mechanism is only implemented for the uplink stage of communication, while the use cases under study aim to use optimized downlink traffic.