处理CSI压缩以减少损耗和开销：一种人工智能方法
Dealing with CSI Compression to Reduce Losses and Overhead: An Artificial Intelligence Approach
摘要：
由于反馈/处理延迟和压缩问题导致基站（BS）处的信道状态信息（CSI）不准确，本文提出了一种采用人工智能（AI）辅助CSI获取的可扩展思想。所提出的方案增强了CSI压缩，这是在移动终端（MT），随着准确的恢复估计的CSI在BS。仿真结果证实了该方案的有效性。在数值上，观察到估计的CSI的接近100%的恢复，具有比基准方案相对较低的开销。所提出的思想可以在无线通信环境中带来潜在的益处，例如，超可靠和低延迟通信（URLLC），其中不完美的CSI和开销是不可容忍的。
英文摘要：
Motivated by the issue of inaccurate channel state information (CSI) at the base station (BS), which is commonly due to feedback/processing delays and compression problems, in this paper, we introduce a scalable idea of adopting artificial intelligence (AI) aided CSI acquisition. The proposed scheme enhances the CSI compression, which is done at the mobile terminal (MT), along with accurate recovery of estimated CSI at the BS. Simulation-based results corroborate the validity of the proposed scheme. Numerically, nearly 100\% recovery of the estimated CSI is observed with relatively lower overhead than the benchmark scheme. The proposed idea can bring potential benefits in the wireless communication environment, e.g., ultra-reliable and low latency communication (URLLC), where imperfect CSI and overhead is intolerable.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
