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A Sub- μ W Reversed-Body-Bias 8-bit Processor on 65-nm Silicon-on-Thin-Box (SOTB) for IoT Applications.

Authors :
Sarmiento, Marco
Nguyen, Khai-Duy
Duran, Ckristian
Hoang, Trong-Thuc
Serrano, Ronaldo
Hoang, Van-Phuc
Tran, Xuan-Tu
Ishibashi, Koichiro
Pham, Cong-Kha
Source :
IEEE Transactions on Circuits & Systems. Part II: Express Briefs; Sep2021, Vol. 68 Issue 9, p3182-3186, 5p
Publication Year :
2021

Abstract

For most Internet-of-Things (IoT) applications, embedded processors typically execute lightweight tasks such as sensing and communication. The typical IoT program senses some information and sends them via a channel, usually a wireless channel with an RF circuit. These IoT nodes often require a system with networking capabilities and a low-power harvester implementation. This brief presents a sub-μW 8-bit processor which is suitable for such IoT applications. The processor implements the Open8 Instruction Set Architecture (ISA) with an 8-bit datapath and 16-bit bus addressing. The chip contains the processor and a 4-KB of Static Random-Access-Memory (SRAM), and is fabricated by the 65-nm Silicon-On-Thin-Box (SOTB) process. The SOTB process is one of the Fully-Depleted Silicon-On-Insulator (FD-SOI) technology. Hence, the ability to control biasing voltages is one of its key advantages to achieve low-power. The experimental results show that the power consumption at the reverse-body bias can reach down to 50-nW with 0.5-V supply voltage and 32-KHz operating clock frequency. The completed microcontroller consists of the Open8 processor, 32-KB of Read-Only-Memory (ROM), 4-KB of SRAM, Serial Peripheral Interface (SPI), SPI programmer, debug module, General-Purpose In-Outs (GPIOs), and UART. The system was tested using an XC7A100T Xilinx Field-Programmable Gate Array (FPGA); it yielded 1.8% of the total FPGA utilization. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15497747
Volume :
68
Issue :
9
Database :
Complementary Index
Journal :
IEEE Transactions on Circuits & Systems. Part II: Express Briefs
Publication Type :
Academic Journal
Accession number :
153301066
Full Text :
https://doi.org/10.1109/TCSII.2021.3090102