Telecommunications Science ›› 2016, Vol. 32 ›› Issue (4): 30-35.doi: 10.11959/j.issn.1000-0801.2016092

• research and development • Previous Articles     Next Articles

Low-complexity signal detection algorithm based on preconditioned conjugate gradient method

Hua QU1,2,Jing LIANG1,Jihong ZHAO1,2,Weihua WANG1   

  1. 1 School of Software Engineering,Xi’an Jiaotong University,Xi’an 710049,China
    2 School of Electronic and Telecommunication Engineering,Xi’an Posts & Telcommunications University,Xi’an 710061,China
  • Online:2016-04-20 Published:2016-04-28
  • Supported by:
    The National Natural Science Foundation of China;The National High Technology Research and Development Program of China(863 Program)

Abstract:

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.

Key words: large-scale multiple-input multiple-output, conjugate gradient method, minimum mean square error

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