2019 Fiscal Year Annual Research Report
Lattice Codes for Gaussian Wireless Networks Beyond 5G
| Project/Area Number |
19H02137
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| Research Institution | Japan Advanced Institute of Science and Technology |
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Principal Investigator |
KURKOSKI Brian 北陸先端科学技術大学院大学, 先端科学技術研究科, 准教授 (80444123)
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| Co-Investigator(Kenkyū-buntansha) |
落合 秀樹 横浜国立大学, 大学院工学研究院, 教授 (20334576)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | lattice / network codes / wireless communications / information theory / coding theory |
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| Outline of Annual Research Achievements |
For future wireless networks, several new methods using lattices and related techniques to increase the bandwidth efficiency, reduce computational complexity and reduce energy consumption were obtained. For integer-forcing MIMO systems where both users have multiple antennas orthogonal precoding outperforms unitary precoding in terms of achievable rate, outage probability, and error rate. The proposed scheme has lower complexity. Published in IEEE Trans on Wireless Communications and were presented at the IEEE Intl. Symp. on Information Theory in Paris, France. For OFDM systems with polar codes, a construction technique using shaping bit patterns significant reduces transmit power, PAPR gain 4.5 dB. Published IEEE Comm. Letters.
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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
We published two journal papers in FY2019, so we judge our progress to be reasonable.
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| Strategy for Future Research Activity |
For 2020, the plan is separated into four work packages WP1-WP4:
(WP1) Lattice Codes for IoT: Develop a new design method for short-block length lattices which minimizes the decoder word error rate using the error rates of the constituent codes for polar code lattices.
(WP2) Network Lattice Codes: Show that low-density lattice codes based on Eisenstein integers can be decoded with lower complexity than those based on Gaussian integers, without performance loss.
(WP3) Simple Gaussian Networks: Develop coding schemes for the compute-forward multiple-access strategy.
(WP4) Multi-Terminal Gaussian Networks: We will investigate an "expanded constellation" approach for compute-forward, in which t he decoder assumes a larger constellation than was used by the transmitter.
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