Channel State Information Accuracy and its Impact on mMIMO Performance in 6G Industrial Networks

Abstract

The implementation of 5G technology paves way for major changes in terms of wireless communications, these applications are; robots, self-driving cars and even medical equipment. This technology that is based on higher frequency bandwidths and efficient modulation techniques hold the possibilities of enhanced capacities, less latency and better connected network. Nevertheless, there are some contentious issues that should be discussed while talking about 5G networks, one of them is the electromagnetic radiation and its possible influence on health. There are still controversies on whether it is safe to expose people to more RF, though regulatory bodies dismissed this as a concern arguing that the amounts found to be carcinogenic are much higher than RF-EMFs.  This paper describes the complex interactions of mMIMO systems for large scale indoor industrial settings, and explores the outcomes of CmMIMO and DmMIMO arrangements. For such an environment, we substantiate a wireless channel model using the collected measurement data and theoretical modeling and analyze the large scale fading behavior and the interplay between different device types and APs. The analysis focuses on evaluating the signal quality identification, which may include aspects such as avg channel gain and also signal to interference plus noise ratio (SINR). Furthermore, we also evaluate the outage probability to determine the effect of this parameter on the execution success ratio and the latency of MTC communication in the concerned network environment. It also evaluates the economic and needs for adopting the mMIMO technologies in certain industries and their operations, which are essentials in today’s industrial world. By simulating the channel coefficients using Monte Carlo simulations, we determine and compare the mMIMO deployment scenario outcomes during regular and emergency traffic. Thus, it has been noticed that DmMIMO configurations provide better signal strength and reliability in most of the cases that are beneficial for application in controlling and processing real-time data. From the general comparison table, it is evident that DmMIMO setups, in general, yield better results regarding the network and different settings of the grid and linear deployments yield different results in terms of spectral efficiency and outage probability. This study not only provides insights into the technical and operational aspects of mMIMO systems but also contributes to the ongoing standardization efforts for future wireless communication technologies. It highlights the transformative potential of 5G in supporting the demands of the Industrial Internet of Things (IIoT) and sets a precedent for future advancements in 6G technologies.