This article presents an instruction-set extension to the open-source RISC-V ISA (RV32IM) dedicated to ultra-low power (ULP) software-defined wireless IoT transceivers. The custom instructions are tailored to the needs of 8/16/32-bit integer complex arithmetic typically required by quadrature modulations. The proposed extension occupies only two major opcodes and most instructions are designed to come at a near-zero energy cost. Both an instruction accurate (IA) and a cycle accurate (CA) model of the new architecture are used to evaluate six IoT baseband processing test benches including FSK demodulation and LoRa preamble detection. Simulation results show cycle count improvements from 19 to 68 percent. Post synthesis simulations for a target 22nm FD-SOI technology show less than 1 percent power and 28 percent area overheads, respectively, relative to a baseline RV32IM design. Power simulations show a peak power consumption of 380 µW for Bluetooth LE demodulation and 225 µW for LoRa preamble detection (BW = 500 kHz, SF = 11).

This work demonstrates an ultra-low power, software-defined wireless transceiver designed for IoT applications using an open-source 32-bit RISC-V core. The key driver behind this success is an optimized hardware/software partitioning of the receiver’s digital signal processing operators. We benchmarked our architecture on an algorithm for the detection of FSK-modulated frames using a RISC-V compatible core and ARM Cortex-M series processors. We use only standard compilation tools and no assembly-level optimizations. Our results show that Bluetooth LE frames can be detected with an estimated peak core power consumption of 1.6 mW on a 28 nm FDSOI technology, and falling to less than 0.6 mW (on average) during symbol demodulation. This is achieved at nominal voltage. Compared to state of the art, our work offers a power efficient alternative to the design of dedicated baseband processors for ultra-low power software-defined radios with a low software complexity.

Exploiting at best every bit of memory on chip is a must for finding the best trade-off between cost and performance when designing Many-Core MPSoCs. In this paper, we propose a new memory hierarchy organization that maximizes the usage of the available memory at each cache level while avoiding data redundancy. We also aim to reduce data access time by avoiding data migration. Our scheme is based on Non-Uniform Cache Architectures (NUCA), and makes use of a novel NoC multicast messaging support. It requires to logically partition the network into imagined layers in which each layer is bound to one of the cache levels. We assess the efficiency of our proposal by evaluating performance metrics, using the Gem5 simulator and the Splash2 benchmark suite. Our results show an improvement of 24% in L2 miss rate over baseline S_NUCA organization and more than 25% in average network latency. We report a maximum improvement of 40% in execution time. Also, we show that our approach outperforms R_NUCA.