An Open-Source Software-Defined Receiver for GNSS Algorithms Benchmarking

Grenier, Antoine; Lohan, Elena Simona; Ometov, Aleksandr; Nurmi, Jari

doi:10.1109/icumt57764.2022.9943489

Cited by 7 publications

(16 citation statements)

References 21 publications

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“…To further assess the mixed SyDR implementation, we have compared its relative processing times with those of the pure Python implementation. The two processing runs were performed using Python 3.8 on an 8-core Intel i7-10700K CPU with 32 GB of RAM over the same scenario as in [15], whose parameters are listed in Table I, producing more than thirty thousand execution time measurements for the two tracking implementations. Ignoring any potential interference from the operating system, this results in a reasonably representative dataset for execution time analysis.…”

Section: Intermediate Resultsmentioning

confidence: 99%

“…In [15], we introduced the concept of our SDR "SyDR" (previously named "pyGNSS-SDR"), designed for GNSS processing. We analyzed existing GNSS SDRs and the benefits of our architecture.…”

Section: B Previous Work and Contributionsmentioning

confidence: 99%

“…The SyDR software follows the architecture described above. In [15], we defined the state machine logic of the receiver and channels. Each channel is responsible for acquiring and tracking a specific satellite requested by the receiver.…”

Section: B Sydr An Open-source Benchmark Platformmentioning

confidence: 99%

See 2 more Smart Citations

Towards Benchmarking GNSS Algorithms on FPGA using SyDR

Grenier

Damsgaard

Liu

et al. 2023

2023 International Conference on Localization and GNSS (ICL-GNSS)

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Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available off-the-shelf, each tailored to match various applications' requirements. Being implemented as Application-Specific Integrated Circuits, these chips provide good performance and low energy consumption but must be treated as "black boxes" by customers. This prevents modification, research in GNSS processing chain enhancement (e.g., application of Approximate Computing techniques), and designspace exploration for finding the optimal receiver implementation per each use case. In this paper, we review the development of SyDR, an open-source Software-Defined Radio oriented towards benchmarking of GNSS algorithms. Specifically, our goal is to integrate certain components of the GNSS processing chain in a Field-Programmable Gate Array and manage their operation with a Python program using the Xilinx PYNQ flow. We present the early steps of converting parts of SyDR to C, which will be later converted to Hardware Description Language descriptions using High-Level Synthesis. We demonstrate successful conversion of the tracking process and discuss benefits and drawbacks arising thereof, before outlining next steps in preparation for hardware implementation.

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Section: Intermediate Resultsmentioning

confidence: 99%

“…In [15], we introduced the concept of our SDR "SyDR" (previously named "pyGNSS-SDR"), designed for GNSS processing. We analyzed existing GNSS SDRs and the benefits of our architecture.…”

Section: B Previous Work and Contributionsmentioning

confidence: 99%

See 1 more Smart Citation

Towards Benchmarking GNSS Algorithms on FPGA using SyDR

Grenier

Damsgaard

Liu

et al. 2023

2023 International Conference on Localization and GNSS (ICL-GNSS)

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“…Future research is needed to see how these algorithms would behave in real scenarios. A possible solution is by implementing a fully digital GNSS receiver to be used as a controlled environment for algorithm benchmarking [87]- [89].…”

Section: B Algorithms With the Lowest Complexity (Q2)mentioning

confidence: 99%

A Survey on Low-Power GNSS

Grenier

Lohan

Ometov

et al. 2023

IEEE Commun. Surv. Tutorials

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With the miniaturization of electronics, Global Navigation Satellite Systems (GNSS) receivers are getting more and more embedded into devices with harsh energy constraints. This process has led to new signal processing challenges due to the limited processing power on battery-operated devices and to challenging wireless environments, such as deep urban canyons, tunnels and bridges, forest canopies, increased jamming and spoofing. The latter is typically tackled via new GNSS constellations and modernization of the GNSS signals. However, the increase in signal complexity leads to higher computation requirements to recover the signals; thus, the trade-off between precision and energy should be evaluated for each application. This paper dives into low-power GNSS, focusing on the energy consumption of satellite-based positioning receivers used in battery-operated consumer devices and Internet of Things (IoT) sensors. We briefly overview the GNSS basics and the differences between legacy and modernized signals. Factors dominating the energy consumption of GNSS receivers are then reviewed, with special attention given to the complexity of the processing algorithms. Onboard and offloaded (Cloud/Edge) processing strategies are explored and compared. Finally, we highlight the current challenges of today's research in low-power GNSS.

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“…Software-Defined Radios (SDRs) are used extensively to test new Digital Signal Processing (DSP) algorithms in all fields of communication, including a GNSS. However, despite how several such tools are available in open-source [ 4 , 5 , 6 , 7 , 8 ], most of them suffer from at least one of these issues, as reviewed in [ 9 ]: lack of maintenance, little-to-no hardware integration, architecture different from an actual receiver, or not being designed for benchmarking. By benchmarking we refer to comparing the performance of various algorithms over a set of Key Performance Indicators (KPIs) of interest.…”

Section: Introductionmentioning

confidence: 99%

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

Grenier,

Lei,

Damsgaard

et al. 2024

Sensors

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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.

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An Open-Source Software-Defined Receiver for GNSS Algorithms Benchmarking

Cited by 7 publications

References 21 publications

Towards Benchmarking GNSS Algorithms on FPGA using SyDR

Towards Benchmarking GNSS Algorithms on FPGA using SyDR

A Survey on Low-Power GNSS

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

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