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

机译:基于SEMIDEFINITE放松和线性规划的准基本似然检测的实现

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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SEMIDEFINITE放松(SDR)方法。通过添加新形式的切割平面和列生成方法,进一步减少了SDR问题。误码率(BER)性能结果总结了纸张。将BER性能与其他MIMO检测算法进行比较。性能实际上与最大似然检测的性能实际上相同,而复杂性则较少并且不依赖于通道矩阵的调节数。

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