IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms
This paper presents a proposal of an open-source index modulation (IM) toolkit, which facilitates reproducible research and accelerates open innovation in IM studies. The proposed toolkit is implemented based on massively parallel algorithms that are designed for state-of-the-art graphics processing...
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8759857/ |
| _version_ | 1818444346946486272 |
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| author | Naoki Ishikawa |
| author_facet | Naoki Ishikawa |
| author_sort | Naoki Ishikawa |
| collection | DOAJ |
| description | This paper presents a proposal of an open-source index modulation (IM) toolkit, which facilitates reproducible research and accelerates open innovation in IM studies. The proposed toolkit is implemented based on massively parallel algorithms that are designed for state-of-the-art graphics processing units (GPUs). Since high-performance GPUs are available at low cost, along with the intensive development in deep learning, this toolkit achieves large scale but significantly fast Monte Carlo simulations at low cost. Two large-tensor-based parallel algorithms are introduced for bit error ratio and average mutual information simulations. Additionally, the design of active indices is newly formulated into an integer linear programming problem that guarantees optimality, which is applicable to the generalized spatial modulation and subcarrier-index modulation schemes. Performance comparisons demonstrated that the proposed GPU-aided algorithms were up to 145 times faster than the conventional CPU-aided efficient counterparts. Furthermore, the designed active indices achieved the theoretical optimum performance in contrast to widely used conventional methods. A comprehensive database of these designed active indices is released online and is available to any researcher. |
| first_indexed | 2024-12-14T19:14:29Z |
| format | Article |
| id | doaj.art-210b5f08fedb4b61b24402d3f631eef0 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T19:14:29Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-210b5f08fedb4b61b24402d3f631eef02022-12-21T22:50:39ZengIEEEIEEE Access2169-35362019-01-017938309384610.1109/ACCESS.2019.29280338759857IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel AlgorithmsNaoki Ishikawa0https://orcid.org/0000-0001-8978-4849Graduate School of Information Sciences, Hiroshima City University, Hiroshima, JapanThis paper presents a proposal of an open-source index modulation (IM) toolkit, which facilitates reproducible research and accelerates open innovation in IM studies. The proposed toolkit is implemented based on massively parallel algorithms that are designed for state-of-the-art graphics processing units (GPUs). Since high-performance GPUs are available at low cost, along with the intensive development in deep learning, this toolkit achieves large scale but significantly fast Monte Carlo simulations at low cost. Two large-tensor-based parallel algorithms are introduced for bit error ratio and average mutual information simulations. Additionally, the design of active indices is newly formulated into an integer linear programming problem that guarantees optimality, which is applicable to the generalized spatial modulation and subcarrier-index modulation schemes. Performance comparisons demonstrated that the proposed GPU-aided algorithms were up to 145 times faster than the conventional CPU-aided efficient counterparts. Furthermore, the designed active indices achieved the theoretical optimum performance in contrast to widely used conventional methods. A comprehensive database of these designed active indices is released online and is available to any researcher.https://ieeexplore.ieee.org/document/8759857/MIMOOFDMindex modulationspatial modulationsubcarrier-index modulationopen-source software |
| spellingShingle | Naoki Ishikawa IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms IEEE Access MIMO OFDM index modulation spatial modulation subcarrier-index modulation open-source software |
| title | IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms |
| title_full | IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms |
| title_fullStr | IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms |
| title_full_unstemmed | IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms |
| title_short | IMToolkit: An Open-Source Index Modulation Toolkit for Reproducible Research Based on Massively Parallel Algorithms |
| title_sort | imtoolkit an open source index modulation toolkit for reproducible research based on massively parallel algorithms |
| topic | MIMO OFDM index modulation spatial modulation subcarrier-index modulation open-source software |
| url | https://ieeexplore.ieee.org/document/8759857/ |
| work_keys_str_mv | AT naokiishikawa imtoolkitanopensourceindexmodulationtoolkitforreproducibleresearchbasedonmassivelyparallelalgorithms |