Real-time Implementation of Cyclostationary Analysis using FPGAs

Jingyi Li
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Abstract

Cyclostationary analysis is an important tool for understanding periodic phenomenon and the spectral correlation density (SCD) function is commonly used in its characterisation. Due to its high computational requirements it is not commonly applied to real-time signals, despite the fact that efficient FFT-based techniques for estimation of the SCD exist. In this research, we aim to address this issue by developing high-performance cyclostationary analysis techniques through FPGA acceleration, and apply them to enable new applications. We will first explore the tradeoff between arithmetic precision and implementation area, applying statistics-based analysis techniques to understand how signal to quantisation noise is affected by wordlength in fixed and floating-point implementations. Next, high-speed FPGA-based systolic architectures for estimating the SCD will be studied. Finally, we apply our optimised arithmetic and architectures to real-time, radio frequency applications.
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利用fpga实时实现循环平稳分析
周期平稳分析是理解周期现象的重要工具,谱相关密度函数(SCD)常用于周期现象的表征。尽管基于fft的高效SCD估计技术已经存在,但由于其高计算要求,它通常不应用于实时信号。在本研究中,我们的目标是通过FPGA加速开发高性能循环平稳分析技术来解决这个问题,并将其应用于新的应用。我们将首先探讨算术精度和实现面积之间的权衡,应用基于统计的分析技术来理解在固定和浮点实现中,字长如何影响信号到量化噪声。接下来,将研究用于估计SCD的基于fpga的高速收缩架构。最后,我们将优化的算法和架构应用于实时射频应用。
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