Meeting MTC requirements in safety-critical applications presents some challenges for communication systems. Such systems must ensure high availability, data integrity and small latency times with deterministic behaviour. For Power Line Communication (PLC) and wireless systems, the challenge is particularly high due to the statistical characteristics of the transmission channel resulting from signal attenuation, reflection, coupled noise, etc. between transmitter and receiver. CC ISN specialises in communication algorithms, protocols and methods that meet the MTC requirements.
- Measurement and modelling of signal propagation in the different application environments.
- Research into the most suitable transmission methods (PHY, MAC layer), based on the Orthogonal Frequency Division Multiplexing (OFDM) multicarrier modulation method
- Network protocol design
- Realisation in embedded hardware (FPGA) and software (DSP, MCU)
- Development in functional samples and prototypes
- Prototype production for larger field tests with quantities of up to 100 units
- Field tests in real applications
This makes it much easier for customers to integrate the CC's technologies into their product innovations and minimises their R&D risk. CC ISN uses state-of-the-art development platforms, such as XILINX ZYNQ, as well as modern measuring and testing equipment in a modern laboratory environment.
In the realisation in hardware and software for the achievement of mission-and-time-critical requirements, special emphasis is placed on a solid design methodology. For this purpose, a mixture of proven process models and design practices (V-Model) and modern approaches, such as Model Based Design, is used. Safety-critical components are developed according to international design standards such as DO-160, DO-178, DO-254 or SIL.
One example is the PLC technology PLUS - Power Line data bUS, which was researched and developed at CC ISN, as well as its integration into various application systems in aircraft, trains, etc. with MTC requirements.
Another example is edge computing systems, such as smart sensors, in which signal processing for communication functions is fused with that for processing sensor measurement data to reduce the typically large amounts of sensor data to metadata at the source, with significantly lower bandwidth requirements for the networks over which this data is transmitted.