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Time-Interleaved Phased Arrays With Parallel Signal Processing in RF Modulations

机译:射频调制中具有并行信号处理的时间交错相控阵

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摘要

The proposed time-interleaved phased array is a functional integration of a space-time domain filter in antenna arrays and a time-frequency domain filter in mixer arrays. Spatially sampled signals by the antenna arrays will be interleaved in time by the mixer arrays to increase modulation speed while leveraging relatively low-frequency carriers. In M-element time-interleaved arrays, the carriers frequency can be reduced by the factor of M to realize an equivalent functionality as in conventional phased arrays based on fundamental carrier modulations. Depending on the array configuration, the time-interleaved phased array can be categorized as “correlated-noise time-interleaved (CNTI)” array or “uncorrelated-noise time-interleaved (UNTI)” array. In the CNTI-array, both signal and correlated noise will be interleaved resulting in the same filter response for the signal and noise, whereas in the UNTI-array only signal will be interleaved in time domain: uncorrelated noise will not participate in the time-interleaving process. An extensive noise analysis for both array types is provided in the paper. To achieve maximum SNR, noise filtering techniques are proposed and verified through CAD behavioral simulations. In essence, the time-interleaved array architecture is a mix of parallel signal processing at RF and LO domains, which can have an advantage in compensating system performance deficits due to an active device speed limitation at high frequencies at the expense of an endurable system complexity.
机译:所提出的时间交错相控阵是天线阵列中的时空域滤波器和混频器阵列中的时频域滤波器的功能集成。天线阵列在空间上采样的信号将被混频器阵列及时交织,以提高调制速度,同时利用相对低频的载波。在M个元素的时间交错阵列中,可以将载波频率降低M倍,以实现与基于基本载波调制的常规相控阵列相同的功能。根据阵列配置,时间交错的相控阵列可以归类为“相关噪声时间交错(CNTI)”阵列或“不相关噪声时间交错(UNTI)”阵列。在CNTI阵列中,信号和相关噪声都将被交织,从而对信号和噪声产生相同的滤波器响应,而在UNTI阵列中,仅信号将在时域中交织:不相关的噪声将不参与时域。交织过程。本文提供了两种阵列类型的广泛噪声分析。为了获得最大的SNR,提出了噪声过滤技术,并通过CAD行为仿真对其进行了验证。从本质上讲,时间交错阵列架构是RF和LO域并行信号处理的混合,由于补偿了有源设备在高频下的速度,在补偿系统性能缺陷方面可能具有优势,但会以持久的系统复杂性为代价。

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