Novel Calibration of MIESM and Reduction of CQI Feedback for Improved Fast Link Adaptation

In mobile communications systems, fast link adaptation (FLA) aims to achieve high system throughput of each user by accurately determining a channel quality indicator (CQI) for feedback, which predicts the next channel based on the current channel state information. In this paper, we propose an improved calibration method of mutual information effective signal-to noise-ratio mapping (MIESM) to determine an accurate CQI feedback value in FLA. Our proposed calibration method derives the optimal calibration factors by considering various channel environments and setting the effective interval of effective signal-to-noise ratio, which is a single value compressing the information of channel characteristics at a time. The simulation is performed in various signal-to-noise ratio (SNR) ranges to account for the actual environments, and the calibration factors are derived from the proposed calibration method. The results show that the CQI feedback value from the derived calibration factors are more accurate than the existing calibration factors. In addition, we discuss a study regarding the time-coherence-based CQI feedback bit reduction scheme. Assuming that each channel is correlated to the previous and subsequent channels, we propose a method to reduce the number of CQI feedback bits adapted to the corresponding SNR regime. Through the simulation, we compare the system throughputs of the proposed adaptive CQI feedback and the conventional CQI feedback scheme. As a result, the proposed CQI feedback has almost the same system throughput as the conventional CQI feedback scheme, but the average number of feedback bits is reduced, thereby improving the efficiency of the communication.