Design Methodology for Industrial Internet-of-Things Wireless Systems
Industrial Internet of Things (IIoT) applications have strict requirements regarding the power consumption, latency, and reliability (PLR) of wireless systems. Designing a reliable and efficient wireless system for IIoT applications requires a thorough understanding of system requirements.
Optimal power consumption and signal quality can be achieved by considering time-related factors like delay spread and coherence time and carefully selecting the data rate. Additionally, accounting for amplitude requirements like path loss and signal sensitivity and selecting appropriate modulation schemes ensure robust and efficient wireless communication in industrial IoT environments.
An innovative design methodology was presented to deliver resource-efficient and PLR-balanced performance for a given application. The methodology optimizes performance by considering the physical, data link, and network layers. It leverages diversity schemes and error detection, and correction mechanisms to enhance reliability and reduce latency in IIoT communications. Using cost-effective Commercial Off-The-Shelf modules enables efficient implementation and widespread application in various IIoT scenarios.
The methodology identifies the design settings, system goals, and objectives based on system requirements, network structure, and chosen hardware. These adjustable design settings include auto-retry count, auto-retry delay, data rate, output power, and standby time, which influence the system goals of achieving specific latency, improving reliability, and minimizing power consumption.
An Active Suspension System (ASAS) for a car is selected for the case study. The ASAS system has components installed in each wheel, enabling a smoother ride. A reusable node platform with microcontrollers and the nRF24L01+ transceiver facilitates wireless communication. To ensure reliable communication, minimum uncorrelated coherence bandwidth (5.25 MHz), coherence time (940 μs), and data rates (250, 1000, or 2000 kbps) were considered. The transceiver's receiver sensitivity and adjustable parameters optimize signal strength to guarantee reliable communication. Higher Bit Error Rate (BER) requirements prompt measures like increased output power and time diversity. The vehicle's movement provides additional time diversity. At the data link and network levels, a transceiver with a basic data link protocol handles data packet assembly, disassembly, CRC-based data validation, and independent state machine control.
Using Multiple-criterion Decision Analysis (MCDA) and objective functions considering the design settings, the authors evaluate different combinations to identify optimal solutions. They analyze trade-offs between objectives, create a Pareto front, and consider cost implications. Based on a cost-function evaluation, the best candidate solution is selected, achieving a balance between system requirements and resource efficiency.
The presented methodology is validated through laboratory experiments, demonstrating its effectiveness. The system achieved a Packet Error Rate close to the required value, while power consumption was measured at 41.6 mW. Latency exhibited a maximum and minimum delay of 515 ms and 1 ms, respectively.
Compared to contemporary technology references, the methodology outperforms its counterparts by up to four times, according to a Figure-of-Merit, exhibiting excellent power consumption and latency performance. These findings provide valuable insights for optimizing wireless systems in industrial applications.
The system could be further improved by implementing parallel links to send data concurrently, reducing latency while maintaining the Bit Error Rate and power consumption.