# Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms

## TL;DR

This paper introduces Hard SyDR, a new benchmarking environment for GNSS algorithms that improves transparency and enables exploration of low-power receiver designs.

## Contribution

The novel contribution is the development of Hard SyDR, an enhanced SDR environment that integrates hardware-level KPIs like power consumption.

## Key findings

- Hard SyDR provides access to hardware-level metrics such as power and resource utilization.
- The system uses HLS and PYNQ to streamline development and enable algorithm benchmarking.
- The framework supports future exploration of Approximate Computing techniques in GNSS receivers.

## Abstract

A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as Application-Specific Integrated Circuit (ASIC)s off-the-shelf, each tailored to the requirements of various applications. These chips deliver good performance and low energy consumption but offer customers little-to-no transparency about their internal features. This prevents modification, research in GNSS processing chain enhancement (e.g., application of Approximate Computing (AxC) techniques), and design space exploration to find the optimal receiver for a use case. In this paper, we review the GNSS processing chain using SyDR, our open-source GNSS Software-Defined Radio (SDR) designed for algorithm benchmarking, and highlight the limitations of a software-only environment. In return, we propose an evolution to our system, called Hard SyDR to become closer to the hardware layer and access new Key Performance Indicator (KPI)s, such as power/energy consumption and resource utilization. We use High-Level Synthesis (HLS) and the PYNQ platform to ease our development process and provide an overview of their advantages/limitations in our project. Finally, we evaluate the foreseen developments, including how this work can serve as the foundation for an exploration of AxC techniques in future low-power GNSS receivers.