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DTSTAMP:20260402T024533Z
LOCATION:3003\, Level 3
DTSTART;TZID=America/Los_Angeles:20250624T160000
DTEND;TZID=America/Los_Angeles:20250624T161500
UID:dac_DAC 2025_sess123_RESEARCH2124@linklings.com
SUMMARY:AdreamDCO: AI-Driven Robust and Efficient Design Automation for Di
 gitally Controlled Oscillators
DESCRIPTION:Yaolong Hu and Hao Guo (Rice University), Shikai Wang (George 
 Washington University), Jiaqi Liu (Rice University), Weidong Cao (George W
 ashington University), and Taiyun Chi (Rice University)\n\nThis paper pres
 ents how we leverage AI-human collaboration to develop an end-to-end, auto
 mated design flow for digitally controlled oscillators (DCOs), a key radio
 -frequency (RF) integrated circuits (ICs) building block that dominates ph
 ase noise and jitter performance of RF systems. Specifically, we decompose
  the DCO design process into two steps and use AI to enhance productivity 
 and optimize performance within each step. Additionally, we demonstrate ho
 w AI can assist RF IC designers in creating unconventional circuit compone
 nts to tackle challenging design specifications. Overall, the proposed flo
 w is capable of synthesizing the DCO design including the schematic and la
 yout in 80 seconds after one-time training, and is frequency agile between
  1 and 20 GHz. Moreover, it can select the most robust design under proces
 s variations when multiple design parameters meet target specifications un
 der the nominal condition. The proposed automated DCO design flow is demon
 strated using two silicon prototypes implemented in the GlobalFoundries 22
 -nm CMOS SOI process. In the measurements, they achieve >192.4-dBc/Hz figu
 re-of-merit (FoM) and <1.5-kHz frequency resolution at 7.1 to 8.6 GHz and 
 3.8 to 4.6 GHz, outperforming existing manual designs at similar frequenci
 es.\n\nTopics: Design\n\nTracks: DES4: Digital and Analog Circuits\n\nSess
 ion Chairs: Ioannis Savidis (Drexel University) and Kishor Kunal (Nvidia)\
 n\n
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