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[资料]用于接收和检测的灵活 RFIC 架构(博士论文PDF下载)

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0楼发表于: 2022-06-20 16:20:15

[post]Compressed sensing (CS) is a new signal processing approach that has disrupted the Shannon-Nyquist limit based design methodology and has opened promising avenues for building energy-efficient radio frequency integrated circuits (RFICs) for detecting and estimating particular classes (i.e. sparse) of signals. Whether in application domains where naturally occurring signals are sparse or where representations of signals subject to the fidelity limits or configuration settings of the radio equipment are often found to be sparse, the emergence of CS has forced us to re-imagine the radio receiver. While realizing some of the potential benefits promised by theory, CS-RFIC architectures proposed in earlier research were not particularly suitable for mass-market applications.

This thesis demonstrates how to take a new signal processing technique all the way to the hardware level. So far, the main focus in literature has been how CS offers a significant advantage for signal processing. This work will show how CS techniques drive novel architectures down to the integrated circuit level. This requires close collaboration between communication system developers, integrated circuit designers and signal processing experts. The trans-disciplinary approach presented here has led to the unification of CS-inspired architectures for wideband signal detection with robust, legacy architectures for high-sensitivity signal reception. The result is a functionally flexible and rapidly reconfigurable CMOS RFIC compactly implemented on silicon with the potential to achieve the cost, size and power targets in mass-market applications. While the focus of this thesis is RF signal finding and reception in frequency, the CS-based RFIC design approach presented here is applicable to a wide range of other applications like direction-of-arrival and range finding.

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