Abstract Accurate feedback of downlink channel state information (CSI) plays a vital role in enabling beamforming in frequency‐division duplex, massive multiple‐input multiple‐output (MIMO) systems. However, the feedback overhead scales with the number of antennas, severely impacting uplink efficiency. While transformer‐based methods, such as TransNet, have exhibited high‐reconstruction accuracy, their computational complexity limits the practical deployment on user equipment. STNet reduces this complexity via spatially separable attention but still underperforms TransNet in terms of accuracy. In this letter, we propose SPINNet, a lightweight CSI feedback network that combines spectral and inception modules to extract efficiently frequency‐domain features. Experimental results on the COST2100 dataset show that the proposed SPINNet outperforms STNet by only half its computational cost and surpasses TransNet in certain scenarios.
Kim et al. (Wed,) studied this question.