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Computer Platform Adaptive Interference Cancellation Using Higher-Order Statistics

机译：使用高阶统计量的计算机平台自适应干扰消除

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摘要

Broadband wireless interference in a computer platform is the result of multiple dynamic electromagnetic emission sources. This interference is non-Gaussian and a receiver design based on the Gaussian assumption will yield suboptimal performance. In fact, it has a double-sided K-dis-tribution and needs to be treated differently in the design process. When dealing with this type of interference in the presence of white Gaussian noise, traditional interferenceoise cancellation schemes do not produce satisfactory results. In this paper, we present an interference mitigation method which improves BER performance. We do this by using the cross-cumulant as the criterion of goodness. Specifically, our algorithm is based on higher order statistics (HOS) and is designed to reconstruct and to cancel the interference in a recursive fashion. The algorithm is tested on both BPSK and OFDM communication environments. We compare performance in terms of BER against other cancellation methods.
机译：计算机平台中的宽带无线干扰是多种动态电磁辐射源的结果。这种干扰是非高斯的，基于高斯假设的接收机设计将产生次优的性能。实际上，它具有双面K分布，在设计过程中需要区别对待。当在高斯白噪声的情况下处理此类干扰时，传统的干扰/噪声消除方案无法产生令人满意的结果。在本文中，我们提出了一种改善BER性能的干扰缓解方法。我们通过使用交叉累积量作为优劣标准来做到这一点。具体来说，我们的算法基于高阶统计量（HOS），旨在以递归方式重建和消除干扰。该算法在BPSK和OFDM通信环境中均经过测试。我们将误码率与其他消除方法的性能进行了比较。

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