研究課題/領域番号 |
18K04132
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研究機関 | 岐阜大学 |
研究代表者 |
LU SHAN 岐阜大学, 工学部, 助教 (30755385)
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研究分担者 |
程 俊 同志社大学, 理工学部, 教授 (00388042)
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研究期間 (年度) |
2018-04-01 – 2022-03-31
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キーワード | signature code / spares recovery |
研究実績の概要 |
In the multiple-access channel, when only a small number of the users are active simultaneously, by considering the signature code as a compressed sensing matrix, it is possible to estimate the channel coefficients while identifying users based on compressed sensing recovery.
In our research, we found that when the signature matrix is uniquely decodable, the decoding on {0,1} can provide the prior information about the position of the zero and nonzero elements. We proposed a modified OMP algorithm with prior information that estimates the fading coefficients for active users based on the prior state information. We also improve the efficiency of the decoding process by deep neural network (DNN)-based decoder.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
When the size of the signature code increases, the computational complexity to obtaining the prior information will be increased exponentially. It sounds that it is not efficient for the massive user. we have to explore the algorithm with low computational complexity to obtain the prior information.
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今後の研究の推進方策 |
A low-complexity list MAP decoding will be investigated to obtain the prior knowledge in the future.
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次年度使用額が生じた理由 |
2020年度、参加予定のアメリカの国際会議にオンラインになったので、出張費を次年度使用額が生じた。
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