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Multi-Stage Antenna Selection for Adaptive Beamforming in MIMO Radar

机译:MIMO雷达自适应波束形成的多级天线选择

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Increasing the number of transmit and receive elements in multiple-input-multiple-output (MIMO) antenna arrays imposes a substantial increase in hardware and computational costs. We mitigate this problem by employing a reconfigurable MIMO array where large transmit and receive arrays are multiplexed in a smaller set of $k$ baseband signals. We consider four stages for the MIMO array configuration and propose four different selection strategies to offer dimensionality reduction in post-processing and achieve hardware cost reduction in digital signal processing (DSP) and radio-frequency (RF) stages. We define the problem as a determinant maximization and develop a unified formulation to decouple the joint problem and select antennas/elements in various stages in one integrated problem. We then analyze the performance of the proposed selection approaches and prove that, in terms of the output SINR, a joint transmit-receive selection method performs best followed by matched-filter, hybrid and factored selection methods. The theoretical results are validated numerically, demonstrating that all methods allow an excellent trade-off between performance and cost.
机译:多输入多输出(MIMO)天线阵列中发送和接收元素的数量增加,导致硬件和计算成本的大幅增加。我们通过采用可重新配置的MIMO阵列来缓解此问题,在该阵列中,较大的发射和接收阵列在较小的一组$ k $基带信号中进行复用。我们考虑了MIMO阵列配置的四个阶段,并提出了四种不同的选择策略,以在后处理中降低尺寸,并在数字信号处理(DSP)和射频(RF)阶段实现硬件成本的降低。我们将问题定义为行列式最大化,并开发统一的公式来解耦联合问题,并在一个集成问题中的各个阶段选择天线/元素。然后,我们分析所提出的选择方法的性能,并证明在输出SINR方面,联合发送-接收选择方法表现最佳,其次是匹配滤波器,混合和因式选择方法。理论结果在数值上得到了验证,表明所有方法都可以在性能和成本之间取得良好的折衷。

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