Adaptive Switching Scheme for RS Overhead Reduction in Massive MIMO With Industrial Internet of Things

Due to the high spectral efficiency (SE) and energy efficiency (EE), it has been proven that massive multiple-input-multiple-output (MIMO) can be successfully applied to Industrial-Internet-of-Things (IIoT) networks. The channel hardening effect of massive MIMO which makes the instantaneous channel gain converges to its average value with little fluctuation, allows simple scheduling and little downlink reference signals (RSs) transmission. We analyze the performance of the channel hardening effect according to the parameter variations, and based on the analysis, we propose an adaptive switching scheme that switches between a mode of using downlink RS and a mode of without using downlink RS depending on the situation. If the downlink RS is not used, the available time and frequency resources can be increased, whereas the signal-to-interference plus noise ratio (SINR) can be decreased. On the other hand, using downlink RS can increase SINR, but it can decrease available time and frequency resources. The proposed scheme finds the mode providing better performance, and conducting mode switching based on various circumstances. The proposed scheme can achieve high SE improvement with little system burden and can thus be used as a useful tool to increase the performance of massive MIMO-based IIoT networks.