2019 Fiscal Year Research-status Report
| Project/Area Number |
18K04132
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| Research Institution | Gifu University |
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Principal Investigator |
LU SHAN 岐阜大学, 工学部, 助教 (30755385)
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| Co-Investigator(Kenkyū-buntansha) |
程 俊 同志社大学, 理工学部, 教授 (00388042)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | signature code / User identification / Channel estimation / DNN based decoder / Multiple-access channel |
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| Outline of Annual Research Achievements |
We are progressing according to the plan in 2020, and achieved the following results.
The first achievement is construction of signature code in algebraic. We propose a coding scheme for a noisy MAAC. In our scheme, given a k-ary code A, with code length n and a (2k－1)-ary code B, with code length n, by a Hadamard matrix of order q we obtain a k-ary code C with code length qn. The main idea behind our coding scheme is to introduce the (2k－1)-ary code B, as well as A for constructing the k-ary code C, thus providing code C with a higher sum rate than A. This is an improvement of the sum rate compared to conventional coding schemes for a noisy MAAC, where the sum rates of C and A are always the same.
The second achievement is considering user identification and channel estimation of binary signature code by DNN-based decoder on multiple-access channel. In the previous works, the signature code was used over a noisy multiple-access adder channel and only the status of uses are decoded by the signature decoder. By considering the communication model as a compressed sensing process, it is possible to estimate the channel coefficients while identifying users. To improve the efficiency of the decoding process, we proposed a iterative deep-neural-network-based decoder. Our simulation results show that for the binary signature code, our proposed DNN-based decoder requires less computing time to achieve higher active user detection accuracy and channel estimation accuracy than the classical signal recovery algorithm used in compressed sensing.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
As summarize in the Research Achievements section, the research work is smoothly progressing according to the plan in 2020.
(1). Our proposed signature code have an improvement of the sum rate compared to conventional coding schemes.
(2).The proposed DNN-based decoder also have less computing time and higher active user detection accuracy and channel estimation accuracy than the classical signal recovery algorithms in multiple-access fading channel.
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| Strategy for Future Research Activity |
今後の研究推進方策は、ランダムアクセススロット割当方式とシステム性能評価。
（１）グラフ理論に基づき、各ユーザの共通符号の符号語のスロットへの割り当てを最適化する。
（２）システム性能評価: 情報理論及び符号理論により、各要素技術を理論解析し、全システム性能を把握したうえ、シミュレーションで確認する。
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| Causes of Carryover |
2020年度に、DNN based multi-user 復号器の提案を行い、その結果を基にシミュレーションを行うとともにシンポジウムにおいて発表する予定であったが、コロナであったため、出張計画を変更し、未使用額が生じた。
このため、その結果をシンポジウムでの発表を次年度に行うこととし、未使用額はその経費に充てること としたい。
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Research Products
(10 results)
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[Presentation] Partial access for LDPC-coded-IDMA systems2019
Author(s)
A. Osamura, G. Song, T. Kimura, and J. Cheng
Organizer
Proc. the 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 6 pages, September 8-11, 2019, Turkey, Istanbul.
Int'l Joint Research
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