Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms
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...
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| Published in | Sensors (Basel, Switzerland) Vol. 24; no. 2; p. 409 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
MDPI AG
01.01.2024
MDPI |
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| Online Access | Get full text |
| ISSN | 1424-8220 1424-8220 |
| DOI | 10.3390/s24020409 |
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| 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. |
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| AbstractList | 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. 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.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. |
| Audience | Academic |
| Author | Lei, Jie Ometov, Aleksandr Damsgaard, Hans Jakob Lohan, Elena Simona Quintana-Ortí, Enrique S. Nurmi, Jari Grenier, Antoine |
| AuthorAffiliation | 2 Parallel Architectures Group, Universitat Politècnica de València, 46010 Valencia, Spain; jlei@disca.upv.es (J.L.); quintana@disca.upv.es (E.S.Q.-O.) 1 Electrical Engineering Unit, Tampere University, 33720 Tampere, Finland; hans.damsgaard@tuni.fi (H.J.D.); aleksandr.ometov@tuni.fi (A.O.); elena-simona.lohan@tuni.fi (E.S.L.); jari.nurmi@tuni.fi (J.N.) |
| AuthorAffiliation_xml | – name: 1 Electrical Engineering Unit, Tampere University, 33720 Tampere, Finland; hans.damsgaard@tuni.fi (H.J.D.); aleksandr.ometov@tuni.fi (A.O.); elena-simona.lohan@tuni.fi (E.S.L.); jari.nurmi@tuni.fi (J.N.) – name: 2 Parallel Architectures Group, Universitat Politècnica de València, 46010 Valencia, Spain; jlei@disca.upv.es (J.L.); quintana@disca.upv.es (E.S.Q.-O.) |
| Author_xml | – sequence: 1 givenname: Antoine orcidid: 0000-0002-3440-8659 surname: Grenier fullname: Grenier, Antoine – sequence: 2 givenname: Jie orcidid: 0000-0002-9998-9503 surname: Lei fullname: Lei, Jie – sequence: 3 givenname: Hans Jakob orcidid: 0000-0001-8409-0282 surname: Damsgaard fullname: Damsgaard, Hans Jakob – sequence: 4 givenname: Enrique S. orcidid: 0000-0002-5454-165X surname: Quintana-Ortí fullname: Quintana-Ortí, Enrique S. – sequence: 5 givenname: Aleksandr orcidid: 0000-0003-3412-1639 surname: Ometov fullname: Ometov, Aleksandr – sequence: 6 givenname: Elena Simona orcidid: 0000-0003-1718-6924 surname: Lohan fullname: Lohan, Elena Simona – sequence: 7 givenname: Jari orcidid: 0000-0003-2169-4606 surname: Nurmi fullname: Nurmi, Jari |
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| Cites_doi | 10.1109/COMST.2023.3265841 10.1145/3572772 10.1109/NAVITEC53682.2022.9847549 10.1109/TCAD.2018.2834439 10.1109/IPDPSW.2018.00031 10.1109/ISVLSI.2018.00112 10.1145/3195970.3196073 10.1109/ICUMT57764.2022.9943489 10.1109/ECICE55674.2022.10042864 10.1109/NEWCAS57931.2023.10198070 10.1145/2348543.2348587 10.1090/S0025-5718-1965-0178586-1 10.1109/ACCESS.2020.3008954 10.1016/j.scico.2021.102609 10.1145/3372224.3380886 10.1145/3388785 10.1145/1117201.1117205 10.23919/DATE54114.2022.9774682 10.1109/TCAD.2020.3003276 10.1109/ICL-GNSS57829.2023.10148916 10.1017/9781108934176 10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00060 |
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| Copyright | COPYRIGHT 2024 MDPI AG 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2024 by the authors. 2024 |
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| Keywords | open-source software global navigation satellite system (GNSS) benchmarking field-programmable gate array (FPGA) computational complexity |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors contributed equally to this work. This paper is an extended version of our paper published in ICL-GNSS 2023, Castellon, Spain, 6–8 June 2023. |
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| Snippet | A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as... |
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| SubjectTerms | Algorithms Application-specific integrated circuits Approximation Artificial satellites benchmarking Benchmarks Communications equipment computational complexity Custom integrated circuits Design Discovery and exploration Energy consumption Field programmable gate arrays field-programmable gate array (FPGA) Fourier transforms global navigation satellite system (GNSS) open-source software Outer space Public software Python Radios Receivers & amplifiers Satellites Semiconductor industry Software |
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| Title | Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms |
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