Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capa...Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.展开更多
众所周知,排列的施工质量对于野外地震资料采集极为关键,而对于排列的质控主要通过日检分析来完成。日检分析在空间上不能覆盖所有接收道,在时间上不能覆盖所有时段。本文介绍一种通过ADSTA(Ancillary Data Standard for Trace Attribu...众所周知,排列的施工质量对于野外地震资料采集极为关键,而对于排列的质控主要通过日检分析来完成。日检分析在空间上不能覆盖所有接收道,在时间上不能覆盖所有时段。本文介绍一种通过ADSTA(Ancillary Data Standard for Trace Attribute)文件来分析地震采集全时段、所有活动排列的方法。这种方法是对排列质控的升级,同时可监控资料品质的变化趋势。此方法在数字化地震队的远程质控、拓展实时监控内容方面具有一定的发展空间。展开更多
基金supported in part by the Beijing Natural Science Foundation under Grant No.L202003the National Natural Science Foundation of China under Grant U22B2001 and 62271065the Project of China Railway Corporation under Grant N2022G048.
文摘Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.
文摘众所周知,排列的施工质量对于野外地震资料采集极为关键,而对于排列的质控主要通过日检分析来完成。日检分析在空间上不能覆盖所有接收道,在时间上不能覆盖所有时段。本文介绍一种通过ADSTA(Ancillary Data Standard for Trace Attribute)文件来分析地震采集全时段、所有活动排列的方法。这种方法是对排列质控的升级,同时可监控资料品质的变化趋势。此方法在数字化地震队的远程质控、拓展实时监控内容方面具有一定的发展空间。
