Empowering Ultra-Low Power with RISC-V ISA Extension Using Reversible Logic Gates for IOT Devices

An open-source RISC-V instruction-set augmentation (RV32IM) is introduced in this study for use in software-defined Wi-Fi Internet of Things (IoT) transceiver devices with very low power consumption. The purpose of the updated instructions is to address a widespread need for complicated math in quadrature modulations using $8 / 16 / 32$ bits of numerical data. For the most part, the suggested extension’s energy cost is near to nothing, and it uses only two main op-codes. The two novel architectural models, the instruction exact (IA) and the process accurate (CA), are used to evaluate six IoT test seats, such as FSK demodulating and LoRa preamble detection. Simulation findings reveal a large variation in cycle count improvements, ranging from $19 \%$ through $68 \%$. In post-synthesis simulations, the 22 nm FD-SOI technology outperforms a baseline RV32IM design with an electricity overhead of less than $1 \%$ and an area overhead of $28 \%$. According to the power calculations, for $\mathrm{BW}=500 \mathrm{kHz}$ with $\mathrm{SF}=11,380 \mu \mathrm{~W}$ is used for Bluetooth LE demodulation by peak electrical power, and $225 \mu \mathrm{~W}$ is used for LoRa preamble detection.

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Published
2024-10-19
DOI
https://doi.org/10.1109/icccmla63077.2024.10871799
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1
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Quantum-Dot Cellular Automata
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article
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article

Empowering Ultra-Low Power with RISC-V ISA Extension Using Reversible Logic Gates for IOT Devices

Chelimala Anjani, Bikram Kumar, Kusum Soni, Ashok Sangala et al.
1 citations
Quantum-Dot Cellular Automata
0.36
article

Empowering Ultra-Low Power with RISC-V ISA Extension Using Reversible Logic Gates for IOT Devices

Chelimala Anjani, Bikram Kumar, Kusum Soni, Ashok Sangala, U Bhagyalakshmi
article en
1 citations

Abstract

An open-source RISC-V instruction-set augmentation (RV32IM) is introduced in this study for use in software-defined Wi-Fi Internet of Things (IoT) transceiver devices with very low power consumption. The purpose of the updated instructions is to address a widespread need for complicated math in quadrature modulations using $8 / 16 / 32$ bits of numerical data. For the most part, the suggested extension’s energy cost is near to nothing, and it uses only two main op-codes. The two novel architectural models, the instruction exact (IA) and the process accurate (CA), are used to evaluate six IoT test seats, such as FSK demodulating and LoRa preamble detection. Simulation findings reveal a large variation in cycle count improvements, ranging from $19 \%$ through $68 \%$. In post-synthesis simulations, the 22 nm FD-SOI technology outperforms a baseline RV32IM design with an electricity overhead of less than $1 \%$ and an area overhead of $28 \%$. According to the power calculations, for $\mathrm{BW}=500 \mathrm{kHz}$ with $\mathrm{SF}=11,380 \mu \mathrm{~W}$ is used for Bluetooth LE demodulation by peak electrical power, and $225 \mu \mathrm{~W}$ is used for LoRa preamble detection.

University College for Women (IN)
Affordable and clean energy
Openalex Percentile: Top 32%
Quantum-Dot Cellular Automata
0.36
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