Stereo super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) stereo image pairs. However, existing methods ignore the connection between the interaction information at each stage in the image pair and acquire global information from the cross-view information with more computational complexity. In this work, we propose an iterative interaction guidance network (I²GSRnet) to obtain the rich cross-view information between image pairs. First, we propose an iterative interaction strategy to fully leverage the interaction guidance information between each iteration. Then, we design an adaptive bidirectional parallax attention module (ABPAM) to efficiently acquire parallax information horizontally and capture global information vertically with less complexity. Finally, we propose a distillation guidance module (DGM) to fully integrate cross-view information with intra-view information using multi-scale information guided by multiple receptive fields. Extensive experiments show that our approach achieves state-of-the-art performance on the KITTI2012, KITTI2015, Middlebury, and Flickr1024 datasets.