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基于FPGA的改进的排序QR分解实现
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上海大学

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上海市科委重点资助项目(20511102400)


Implementation of Improved Sorted QR Decomposition on FPGA
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shanghai university

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Science and Technology Commission of Shanghai Municipality (20511102400)

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    摘要:

    MIMO技术虽然可以提高频谱的利用率,但是多维度的信号处理为MIMO信号的检测带来了极大的挑战。在对各类MIMO检测算法分析的基础上,选择非线性QR分解算法作为研究对象。为了获取更高的检测性能,进一步研究了排序的QR分解并提出了基于L1范数的排序方案。Matlab性能仿真显示,基于L1范数的排序策略和基于L2范数的排序策略对MIMO系统检测性能的影响基本一致但采用L1范数降低了计算复杂度。在此基础上,设计了基于FPGA的利用Givens旋转改进的排序QR分解的硬件电路结构。在4×4信道矩阵的分解实现中,相较于L2范数求解,L1范数在单个列范数计算中组合逻辑资源至少节省了29.2%,触发器资源至少节省了32.4%。整体结构设计与同等规模的类似结构相比,主频时钟得到明显改善。

    Abstract:

    Although MIMO technology can improve the utilization rate of spectrum, multi-dimensional signal processing brings great challenges to the detection of MIMO signals. Based on the analysis of various MIMO detection algorithms, QR decomposition is selected as the research object, which is a kind of nonlinear algorithm. In order to obtain higher performance of detection, the sorted QR decomposition is further studied and propose the sorting scheme based on L1-norm. Using Matlab for performance simulation, the L1-norm sorting strategy and the L2-nrom sorting strategy have basically the same impact on MIMO system, but the L1-norm sorting strategy reduces the computational complexity. On this basis, the hardware structure of improved sorted QR decomposition by Givens rotation on FPGA is proposed. Comparing with the solution of L2-norm, the L1-norm strategy reduces at least 29.2% combinational logic resources and 32.4% register resources when calculating a single column norm in the realization of 4×4 channel matrix decomposition. Comparing with similar designs, the frequency of operating clock has been significantly improved.

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  • 收稿日期: 2021-10-25
  • 最后修改日期: 2021-12-10
  • 录用日期: 2021-12-16
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