Channel Estimation Algorithm Based on Spatial Direction Acquisition and Dynamic‐Window Expansion in Massive MIMO System

Li, Shufeng; Su, Baoxin; Liu, Yiming; Zhang, Junwei; You, Minglei

Abstract

Millimeter-wave (mmWave) and massive multiple-input multiple-output (MIMO) technologies are critical in current and future communication research. They play an essential role in meeting the demands for high-capacity, high-speed, and low-latency communication brought about by technological advancements. However, existing mmWave channel estimation schemes rely on idealized common sparse channel support assumptions, and their performance significantly degrades when encountering beam squint scenarios. To address this issue, this paper introduces a dynamic support detection window (DSDW) algorithm. This algorithm dynamically adjusts the position and size of the window based on the received signal strength, thereby better capturing signal strength variations and obtaining a more complete set of signal supports. The DSDW algorithm can better capture and utilize the sparsity of the channel, improving the efficiency and accuracy of the channel state information acquisition. By combining the beam-split pattern (BSP) algorithm with the DSDW algorithm, this paper designs an effective method to address the inherent beam-spreading problem in mmWave scenarios. Simulation results are proposed to demonstrate the effectiveness of the BSP-DSDW algorithm.

Citation

Li, S., Su, B., Liu, Y., Zhang, J., & You, M. (2024). Channel Estimation Algorithm Based on Spatial Direction Acquisition and Dynamic‐Window Expansion in Massive MIMO System. International Journal of Intelligent Systems, 2024(1), https://doi.org/10.1155/2024/7727469

• Journal Article Type: Article
• Acceptance Date: Jul 5, 2024
• Online Publication Date: Jul 19, 2024
• Publication Date: Jul 19, 2024
• Deposit Date: Sep 16, 2024
• Publicly Available Date: Sep 19, 2024
• Journal: International Journal of Intelligent Systems
• Print ISSN: 0884-8173
• Electronic ISSN: 1098-111X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 2024
• Issue: 1
• DOI: https://doi.org/10.1155/2024/7727469
• Public URL: https://nottingham-repository.worktribe.com/output/37320220
• Publisher URL: https://onlinelibrary.wiley.com/doi/10.1155/2024/7727469