面向低空通信MIMO-OTFS系统的QR-BKS高效检测算法OA

To address the issues of high mobility and limited computation power of terminals in low-altitude communication MIMO-OTFS systems,this paper proposes an efficient QR decomposition-assisted block Klein sampling detection algorithm(QR-BKS).The algorithm deeply integrates block-wise Klein sampling with regularized MMSE-QR decomposition technology and utilizes a soft-mean-based soft interference cancellation mechanism to enhance the detector's error correction capability,thereby effectively overcoming the error propagation defects inherent in traditional successive interference cancellation.To meet real-time requirements of the system,a QR decomposition caching mechanism based on channel circulant properties and a dynamic randomized blocking strategy are designed.These strategies significantly reduce computational redundancy while effectively smoothing inter-block interference,eliminating the error floor phenomenon in the high signal-to-noise ratioregime.Furthermore,by introducing a fast hot-start mechanism based on least squares minimal residual and global Euclidean distance calibration,the algorithm further improves convergence speed and detection reliability.Simulation results demonstrate that in MIMO-OTFS systems,the proposed algorithm achieves superior detection performance with lower computational overhead,making it suitable for low-altitude intelligent network communication scenarios.