Tensor-Based Efficient Multi-Interferer RFI Excision Algorithms for SIMO Systems

被引:17
|
作者
Getu, Tilahun Melkamu [1 ,2 ]
Ajib, Wessam [2 ]
Yeste-Ojeda, Omar A. [1 ,3 ]
机构
[1] Ecole Technol Super, Montreal, PQ H3C 1K3, Canada
[2] Univ Quebec Montreal, Montreal, PQ H2L 2C4, Canada
[3] Natl Radio Astron Observ, Charlottesville, VA 22902 USA
关键词
RFI excision; multi-linear subspace estimation; multi-linear projection; joint enumeration; perturbation analysis; CHANNEL ORDER ESTIMATION; PERFORMANCE ANALYSIS; MITIGATION; TIME;
D O I
10.1109/TCOMM.2017.2694006
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Radio frequency interference (RFI) is causing performance loss in microwave radiometry, radio astronomy, and satellite communications. As the number of interferers increases, the performance loss gets more severe and RFI excision becomes more difficult. In this regard, this paper introduces the multi-linear algebra framework to the multi-interferer RFI (MI-RFI) excision research by proposing a multi-linear subspace estimation and projection (MLSEP) algorithm for single-input multiple-output (SIMO) systems suffering from MI-RFI. Having employed smoothed observation windows, a smoothed MLSEP (s-MLSEP) algorithm, which enhances MLSEP, is also proposed. MLSEP and s-MLSEP require the knowledge of the number of interferers and their respective channel order. Accordingly, a novel smoothed matrix-based joint number of interferers and channel order enumerator is proposed. Performance analyses corroborate that both MLSEP and s-MLSEP can excise all interferers when the perturbations get infinitesimally small. For such perturbations, the analyses also attest that s-MLSEP exhibit a faster convergence to a zero excision error than MLSEP which, in turn converges faster than a subspace projection algorithm. Despite its slight complexity, simulations and performance assessment on real-world data demonstrate that MLSEP outperforms projection-based RFI excision algorithms. Simulations also corroborate that s-MLSEP outperforms MLSEP as the smoothing factor gets smaller.
引用
收藏
页码:3037 / 3052
页数:16
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