An Autonomous Zero-Mask Unique ID Generation System for Next-Generation Neural Interfaces

被引：1
作者：
Ozbek, Berkay [1 ]
Constandinou, Timothy G. [1 ,2 ]
机构：
[1] Imperial Coll London, Dept Elect & Elect Engn, London, England
[2] Imperial Coll London, Ctr Bioinspired Technol, Inst Biomed Engn, London, England
来源：
2023 21ST IEEE INTERREGIONAL NEWCAS CONFERENCE, NEWCAS | 2023年
关键词：
CMOS antifuse; neural interface authentication; non-volatile memory; one-time programmable memory; phase noise; true random number generation; DEEP BRAIN-STIMULATION;
D O I：
10.1109/NEWCAS57931.2023.10198170
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents a 1-kbit autonomous zero-mask unique ID generation system as multiple access and authentication solutions for wireless neural interfaces. The system utilizes the phase noise in a ring oscillator to generate high entropy true random numbers as IDs of the neural interfaces. The randomness of the true random number generator (TRNG) was verified by NIST 800-22 tests. The generated ID is burnt into an antifuse onetime programmable (OTP) memory such that there is no extra mask and extreme programming currents. The programming voltage is generated internally through a charge pump and a high-voltage (HV) multiplexer sets the required voltage for the programming and reading modes so that the system operates autonomously with only enabling inputs. Thus, the proposed system achieves a safe, cost-effective and autonomous on-site unique ID generation and storage for distributed neural interfaces.
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页数：5
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