清华大学 电子工程系,北京,100084
纸质出版:2016
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韩晨曦, 魏经纬, 李冬梅. 基于压缩传感的模数转换器设计[J]. 微电子学与计算机, 2016, 33(2): 7-11, 17.
HAN Chen-xi, WEI Jing-wei, LI Dong-mei. Design of an ADC Based on Compressed Sensing Theory[J]. 2016, 33(2): 7-11.
随着宽带信号应用的普及
压缩传感理论打破了传统奈奎斯特模数转换器在硬件上的瓶颈.设计了一款基于压缩传感理论的模数转换器
并提出了一种针对多路并行结构、压缩传感信号重构的校准方法.系统在180 nm工艺下进行电路和版图设计.设计指标是基于压缩传感利用低于信号奈奎斯特频率的模数转换器达到160 MHz采样频率
12 bit量化精度.经校准的整体后仿指标达到160 MHz 10.25 bit
核心面积为2.08 mm
优值(FOM)为110 fJ.SAR模数转换器后仿指标达到40 MHz 10.08 bit
优值(FOM)为56 fJ.在整体上验证了设计结构和算法的正确性和有效性.
As the wide band signal application popularizing
traditional ADC based on Nyquist sampling theory is limited
which can be conquered by compressed sensing theory. This paper presents an ADC based on compressed sensing theory
and put forward a calibration method to estimate the mismatch of multipath when reconstructing the original signal from compressed sensing measurement. The whole system is implemented in UMC 180 nm fabrication. It consists multipath to measure the input signal but quantized by a single quantizer. The quantizer is a SAR ADC which can work individually. The object is to design an ADC achieving 160 MHz sampling frequency and 12 bit ENOB with a sub-Nyquist quantizer. The whole system achieves a post-layout 160 MHz 10.25 ENOB with a figure of merit of 110 fJ/conv-step
and occupies 2.08. The SAR ADC achieves a post-layout 40 MHz 10.08 bit with a FOM of 56 fJ/conv-step. The simulation shows the correctness and effectiveness of the system structure and calibration method.
Yenduri P K, Rocca A Z, Rao A S, et al. A low-power compressive sampling time-based analog-to-digital converter[J]. Emerging and Selected Topics in Circuits and Systems, IEEE Journal on, 2012, 2(3): 502-515. DOI: 502
Candès E J, Romberg J, Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. Information Theory, IEEE Transactions on, 2006, 52(2): 489-509. DOI: 489
Mallat S G, Zhang Z. Matching pursuits with time-frequency dictionaries[J]. Signal Processing, IEEE Transactions on, 1993, 41(12): 3397-3415. DOI: 3397
Trakimas M, D'Angelo R, Aeron S, et al. A compressed sensing analog-to-information converter with edge-triggered SAR ADC core[J]. Circuits and Systems Ⅰ: Regular Papers, IEEE Transactions on, 2013, 60(5): 1135-1148. DOI: 1135
Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit[J]. SIAM journal on scientific computing, 1998, 20(1): 33-61. DOI: 33
Rudelson M, Vershynin R. Sparse reconstruction by convex relaxation: Fourier and Gaussian measurements[C]//Information Sciences and Systems, 2006 40th Annual Conference on. New Jersey, Princeton, IEEE, 2006: 207-212.
D'Angelo R, Trakimas M, Sonkusale S, et al. Compressed sensing of EEG using a random sampling ADC in 90nm CMOS[C]//Body Sensor Networks (BSN), 2013 IEEE International Conference on. USA, Cambridge, IEEE, 2013: 1-5.
Deng W, Yin W, Zhang Y. Group sparse optimization by alternating direction method[C]//SPIE Optical Engineering+ Applications. International Society for Optics and Photonics. USA, San Diego, 2013: 88580R-15.
Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. Information Theory, IEEE Transactions on, 2007, 53(12): 4655-4666. DOI: 4655
Litvak A E, Pajor A, Rudelson M, et al. Smallest singular value of random matrices and geometry of random polytopes[J]. Advances in Mathematics, 2005, 195(2): 491-523. DOI: 491
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