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Turbo multi-user detection for OFDM/SDMA systems relying on differential evolution aided iterative channel estimation

机译:用于OFDm / sDma系统的Turbo多用户检测依赖于差分进化辅助迭代信道估计

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摘要

A differential evolution (DE) algorithm aided iterative channel estimation and turbo multi-user detection (MUD) scheme is proposed for multi-user multi-input multiple-output aided orthogonal frequency-division multiplexing/spacedivision multiple-access (OFDM/SDMA) systems. The proposed scheme iteratively exchanges the estimated channel information and the detected data between the channel estimator and MUD employing a turbo technique, which gradually improves the accuracy of the channel estimation and the MUD, especially for the first iteration. Quadrature amplitude modulation (QAM) is employed in most wireless standards by virtue of providing a high throughput. However, the optimal maximum likelihood (ML)-MUD becomes extremely complex for employment in QAM-aided multi-user systems. Hence, two different DE aided MUD schemes, the DE aided minimum symbol error rate (MSER)-MUD as well as the discrete DE aided ML-MUD, were developed, and their achievable performance versus complexity was characterized. The simulation results demonstrate that the proposed DE aided channel estimator is capable of approaching the Cramer-Rao lower bound with just two or three iterations. The ultimate bit error rate lower-bound of the single-user additive white Gaussian noise scenario has been approached in the range of E_{b}/N_{0}ge 10 dB and E_{b}/N_{0}ge 6 dB for the DE aided MSER-MUD and the discrete DE aided ML-MUD, respectively.
机译:针对多用户多输入多输出辅助正交频分复用/空分多址(OFDM / SDMA)系统,提出了一种差分演化(DE)算法辅助迭代信道估计和turbo多用户检测(MUD)方案。 。所提出的方案采用turbo技术在信道估计器和MUD之间迭代地交换估计的信道信息和检测到的数据,这尤其是对于第一次迭代而言逐渐提高了信道估计和MUD的准确性。正交幅度调制(QAM)通过提供高吞吐量而在大多数无线标准中使用。但是,在QAM辅助的多用户系统中使用最佳最大似然(ML)-MUD变得极为复杂。因此,开发了两种不同的DE辅助MUD方案,即DE辅助最小符号错误率(MSER)-MUD和离散DE辅助ML-MUD,并描述了它们可实现的性能与复杂性之间的关系。仿真结果表明,提出的DE辅助信道估计器仅需进行两次或三个迭代就可以逼近Cramer-Rao下限。单用户加性高斯白噪声场景的最终误码率下限已达到E_ {b} / N_ {0} ge 10 dB和E_ {b} / N_ {0} ge的范围DE辅助MSER-MUD和离散DE辅助ML-MUD分别为6 dB。

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