The field of wireless communication is moving towards more efficient and accurate channel estimation methods. Recent developments have focused on exploiting sparsity in channels, improving the performance of multiple-input multiple-output (MIMO) systems, and enhancing spectrum utilization in Wi-Fi networks. Notably, innovative approaches have been proposed to address the challenges of doubly sparse time-varying channels, reducing computational overhead in joint channel estimation and signal detection, and improving the performance of non-primary channel access mechanisms. These advancements have the potential to significantly impact the development of future wireless communication systems. Noteworthy papers include: Models, Methods and Waveforms for Estimation and Prediction of Doubly Sparse Time-Varying Channels, which introduces a novel off-grid model for channel estimation and prediction. Joint Channel Estimation and Signal Detection for MIMO-OFDM proposes a novel data-aided approach with reduced computational overhead. Performance Analysis of IEEE 802.11bn Non-Primary Channel Access presents a comprehensive analysis of the Non-Primary Channel Access mechanism. Sparsity-Exploiting Channel Estimation For Unsourced Random Access With Fluid Antenna explores the channel estimation problem in uplink transmission for unsourced random access with a fluid antenna receiver.