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Implementation of quasi-maximum-likelihood detection based on semidefinite relaxation and linear programming

机译:基于半定松弛和线性规划的拟最大似然检测

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In this paper, a new numerical method is proposed for fast signal detection in large scale MIMO systems. Semidefinite relaxation (SDR) approach is utilized. The SDR problem is further reduced to the sequential linear programming by adding new form of cutting planes and column generation method. Bit error rate (BER) performance results conclude the paper. BER performance is compared with other MIMO detection algorithms. Performance of the new scheme practically identical to performance of the maximum-likelihood detection, while complexity is much less and does not depend on the conditioning number of the channel matrix.
机译:本文提出了一种新的数值方法,用于大规模MIMO系统中的快速信号检测。使用半定松弛(SDR)方法。通过添加新形式的切割平面和列生成方法,将SDR问题进一步简化为顺序线性编程。本文总结了误码率(BER)性能结果。 BER性能与其他MIMO检测算法进行了比较。新方案的性能实际上与最大似然检测的性能相同,而复杂性要小得多,并且不取决于信道矩阵的条件数。

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