Ghost imaging(GI)offers great potential with respect to conventional imaging techniques.However,there are still some obstacles for reconstructing images with high quality,especially in the case that the orthogonal mea...Ghost imaging(GI)offers great potential with respect to conventional imaging techniques.However,there are still some obstacles for reconstructing images with high quality,especially in the case that the orthogonal measurement matrix is impossible to construct.In this paper,we propose a new scheme based on the orthogonal-triangular(QR)decomposition,named QR decomposition ghost imaging(QRGI)to reconstruct a better image with good quality.In the scheme,we can change the randomly non-orthogonal measurement matrix into orthonormal matrix by performing QR decomposition in two cases.(1)When the random measurement matrix is square,it can be firstly decomposed into an orthogonal matrix Q and an upper triangular matrix R.Then let the off-diagonal values of R equal to 0.0,the diagonal elements of R equal to a constant k,where k is the average of all values of the main diagonal,so the resulting measurement matrix can be obtained.(2)When the random measurement matrix is with full rank,we firstly compute its transpose,and followed with above QR operation.Finally,the image of the object can be reconstructed by correlating the new measurement matrix and corresponding bucket values.Both experimental and simulation results verify the feasibility of the proposed QRGI scheme.Moreover,the results also show that the proposed QRGI scheme could improve the imaging quality comparing to traditional GI(TGI)and differential GI(DGI).Besides,in comparison with the singular value decomposition ghost imaging(SVDGI),the imaging quality and the reconstruction time by using QRGI are similar to those by using SVDGI,while the computing time(the time consuming on the light patterns computation)is substantially shortened.展开更多
Aiming at the problem of high computational complexity of Vertical-BLAST(V-BLAST) algorithm in Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing(MIMO-OFDM) system signal detection, this paper f...Aiming at the problem of high computational complexity of Vertical-BLAST(V-BLAST) algorithm in Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing(MIMO-OFDM) system signal detection, this paper first uses Sorted QR Decomposition(SQRD) iterative operation instead of matrix inversion to reduce the computational complexity of the algorithm, and then considering that the algorithm is greatly affected by noise, Minimum Mean Square Error(MMSE) criterion is used to weaken the noise effect. At the same time, in order to reduce the noise and computational complexity, MMSE and SQRD are combined, which can not only reduce the noise and computational complexity, but also obtain the sub-optimal detection order, thus improving the detection performance of the MIMO-OFDM system. Finally, the numerical simulation of the MMSE-SQRD detection algorithm is carried out. The results show that the Eb/No of MMSE-SQRD algorithm is 2 dB greater than that of the MMSE algorithm and the computational complexity is O(NT3) under the conditions that NT =NR=2 and the BER is 10–2. The detection algorithm satisfies the demand of short wave and wideband wireless communication.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61871234 and 62001249)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(Grant No.KYCX200729)+1 种基金Natural Science Research Project of Higher Education of Jiangsu Province,China(Grant No.20KJB510030)Research project of NanJing Tech University Pujiang Institute(Grant No.njpj2020-1-02)。
文摘Ghost imaging(GI)offers great potential with respect to conventional imaging techniques.However,there are still some obstacles for reconstructing images with high quality,especially in the case that the orthogonal measurement matrix is impossible to construct.In this paper,we propose a new scheme based on the orthogonal-triangular(QR)decomposition,named QR decomposition ghost imaging(QRGI)to reconstruct a better image with good quality.In the scheme,we can change the randomly non-orthogonal measurement matrix into orthonormal matrix by performing QR decomposition in two cases.(1)When the random measurement matrix is square,it can be firstly decomposed into an orthogonal matrix Q and an upper triangular matrix R.Then let the off-diagonal values of R equal to 0.0,the diagonal elements of R equal to a constant k,where k is the average of all values of the main diagonal,so the resulting measurement matrix can be obtained.(2)When the random measurement matrix is with full rank,we firstly compute its transpose,and followed with above QR operation.Finally,the image of the object can be reconstructed by correlating the new measurement matrix and corresponding bucket values.Both experimental and simulation results verify the feasibility of the proposed QRGI scheme.Moreover,the results also show that the proposed QRGI scheme could improve the imaging quality comparing to traditional GI(TGI)and differential GI(DGI).Besides,in comparison with the singular value decomposition ghost imaging(SVDGI),the imaging quality and the reconstruction time by using QRGI are similar to those by using SVDGI,while the computing time(the time consuming on the light patterns computation)is substantially shortened.
基金Supported by the National Natural Science Foundation of China(61671333)
文摘Aiming at the problem of high computational complexity of Vertical-BLAST(V-BLAST) algorithm in Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing(MIMO-OFDM) system signal detection, this paper first uses Sorted QR Decomposition(SQRD) iterative operation instead of matrix inversion to reduce the computational complexity of the algorithm, and then considering that the algorithm is greatly affected by noise, Minimum Mean Square Error(MMSE) criterion is used to weaken the noise effect. At the same time, in order to reduce the noise and computational complexity, MMSE and SQRD are combined, which can not only reduce the noise and computational complexity, but also obtain the sub-optimal detection order, thus improving the detection performance of the MIMO-OFDM system. Finally, the numerical simulation of the MMSE-SQRD detection algorithm is carried out. The results show that the Eb/No of MMSE-SQRD algorithm is 2 dB greater than that of the MMSE algorithm and the computational complexity is O(NT3) under the conditions that NT =NR=2 and the BER is 10–2. The detection algorithm satisfies the demand of short wave and wideband wireless communication.
