Low-complexity signal detection algorithm based on preconditioned conjugate gradient method
For large-scale multiple-input multiple-output system，minimum mean square error signal detection algorithm is near-optimal but involves matrix inversion，and complexity is growing exponentially. So less-complexity signal detection algorithm using preconditioned conjugate gradient method was proposed，...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2016-04-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016092/ |
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| Summary: | For large-scale multiple-input multiple-output system，minimum mean square error signal detection algorithm is near-optimal but involves matrix inversion，and complexity is growing exponentially. So less-complexity signal detection algorithm using preconditioned conjugate gradient method was proposed，the algorithm reduced the condition number of matrix by pretreatment technology，thus speeding up the convergence rate of conjugate gradient signal detection algorithm. The simulation results show that the proposed algorithm can achieve the near-optimal bit error rate performance of minimum mean square error detection algorithm with a small number of iterations，and computation complexity reduces a order of magnitude. Compared with the conjugate gradient method，the proposed algorithm can quickly converge to the optimum value. |
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| ISSN: | 1000-0801 |