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Compressive sensing based multiuser detector for massive MBM MIMO uplink 被引量:3
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作者 SONG Wei WANG Wenzheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第1期19-27,共9页
Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple inpu... Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods. 展开更多
关键词 media based modulation(MBM) radio frequency(RF)mirror compressive sensing(CS) multiple input multiple output(MIMO) multiuser detector compressive sampling matching pursuit(CoSaMP).
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Improved RIP-based bounds for guaranteed performance of two compressed sensing algorithms 被引量:1
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作者 Yunbin Zhao Zhiquan Luo 《Science China Mathematics》 SCIE CSCD 2023年第5期1123-1140,共18页
Iterative hard thresholding(IHT)and compressive sampling matching pursuit(CoSaMP)are two mainstream compressed sensing algorithms using the hard thresholding operator.The guaranteed performance of the two algorithms f... Iterative hard thresholding(IHT)and compressive sampling matching pursuit(CoSaMP)are two mainstream compressed sensing algorithms using the hard thresholding operator.The guaranteed performance of the two algorithms for signal recovery was mainly analyzed in terms of the restricted isometry property(RIP)of sensing matrices.At present,the best known bound using the RIP of order 3k for guaranteed performance of IHT(with the unit stepsize)isδ3k<1/√3≈0.5774,and the bound for CoSaMP using the RIP of order 4k isδ4k<0.4782.A fundamental question in this area is whether such theoretical results can be further improved.The purpose of this paper is to affirmatively answer this question and to rigorously show that the abovementioned RIP bound for guaranteed performance of IHT can be significantly improved toδ3k<(√5−1)/2≈0.618,and the bound for CoSaMP can be improved toδ4k<0.5102. 展开更多
关键词 iterative hard thresholding compressive sampling matching pursuit compressed sensing guaranteed performance restricted isometry property
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