Discrete-Valued Vector Reconstruction from Underdetermined Linear Measurements
| Project/Area Number |
18K04148
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 21020:Communication and network engineering-related
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| Research Institution | Kyoto University (2020)
Osaka City University (2018-2019) |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 劣決定線形観測 / スパース性 / 離散性 / グループスパース性 / 非凸最適化 / 圧縮センシング / スパースモデリング / IoT / 複素信号 / 離散値ベクトル / 過負荷信号処理 |
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| Outline of Final Research Achievements |
By using the performance analysis scheme with CGMT (convex Gaussian min-max theorem) for MIMO signal detection, we have successfully derived the asymptotic theoretical performance of the signal reconstruction via SOAV (sum-of-absolute-value) optimization from underdetermined linear measurements, such as symbol error rate or mean-square-error. Moreover, we have developed the reconstruction algorithms for complex-valued discrete signals or the signals with group sparsity. Furthermore, by employing non-convex sparse regularization term, we have significantly improved the reconstruction performance of discrete and/or sparse signals, and have demonstrated the validity of the proposed approach via computer simulations of data collection from large number of IoT terminals.
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| Academic Significance and Societal Importance of the Research Achievements |
圧縮センシングは多くの信号のもつスパース性を利用することで，その次元よりも少ない線形観測から実際に観測された信号を再構成する手法であり，すでに多くの分野で利用されている．本研究はその適用範囲をさらに拡大するものであり，信号が離散性を有する場合にも圧縮センシングと同様に信号の次元よりも少ない線形観測から未知ベクトルを再構成できるアルゴリズムを開発し，さらにその理論限界を明らかにしている点で学術的な意義がある．また，特に情報通信分野で扱われる信号は複素領域の離散性を有するため，益々重要度を高めつつある情報通信システムの性能改善に直接つながるという点で社会的な意義も大きい．
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Report
(4 results)
Research Products
(28 results)
