A fractional-N sub-sampling PLL using a pipelined phase-interpolator with a FoM of −246dB

Author(s):  
Aravind Tharayil Narayanan ◽  
Makihiko Katsuragi ◽  
Kento Kimura ◽  
Satoshi Kondo ◽  
Korkut Kaan Tokgoz ◽  
...  
Keyword(s):  
Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6824
Author(s):  
Jae-Soub Han ◽  
Tae-Hyeok Eom ◽  
Seong-Wook Choi ◽  
Kiho Seong ◽  
Dong-Hyun Yoon ◽  
...  

Sampling-based PLLs have become a new research trend due to the possibility of removing the frequency divider (FDIV) from the feedback path, where the FDIV increases the contribution of in-band noise by the factor of dividing ratio square (N2). Between two possible sampling methods, sub-sampling and reference-sampling, the latter provides a relatively wide locking range, as the slower input reference signal is sampled with the faster VCO output signal. However, removal of FDIV makes the PLL not feasible to implement fractional-N operation based on varying divider ratios through random sequence generators, such as a Delta-Sigma-Modulator (DSM). To address the above design challenges, we propose a reference-sampling-based calibration-free fractional-N PLL (RSFPLL) with a phase-interpolator-linked sampling clock generator (PSCG). The proposed RSFPLL achieves fractional-N operations through phase-interpolator (PI)-based multi-phase generation instead of a typical frequency divider or digital-to-time converter (DTC). In addition, to alleviate the power burden arising from VCO-rated sampling, a flexible mask window generation method has been used that only passes a few sampling clocks near the point of interest. The prototype PLL system is designed with a 65 nm CMOS process with a chip size of 0.42 mm2. It achieves 322 fs rms jitter, −240.7 dB figure-of-merit (FoM), and −44.06 dBc fractional spurs with 8.17 mW power consumption.


Author(s):  
Anders Jakobsson ◽  
Adriana Serban ◽  
Shaofang Gong
Keyword(s):  

2019 ◽  
Vol 28 (6) ◽  
pp. 1227-1233
Author(s):  
Yuyue Zhao ◽  
Yingdan Jiang ◽  
Yu Yang ◽  
Guangzhen Shen ◽  
kai Hu ◽  
...  

2021 ◽  
Vol 68 (1) ◽  
pp. 156-160
Author(s):  
Ahmed Elnaqib ◽  
Hayate Okuhara ◽  
Taekwang Jang ◽  
Davide Rossi ◽  
Luca Benini

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