Anti-strong Jamming Polar Coding Optimization Method with Multiobjective Reinforcement Learning

LIANG Hao; YE Ganhua; LU Ruimin; WANG Heng; WEI Peng

doi:10.11999/JEIT230572

Volume 45 Issue 11

Nov. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(11): 4092-4100

LIANG Hao, YE Ganhua, LU Ruimin, WANG Heng, WEI Peng. Anti-strong Jamming Polar Coding Optimization Method with Multiobjective Reinforcement Learning[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4092-4100. doi: 10.11999/JEIT230572

Citation:

LIANG Hao, YE Ganhua, LU Ruimin, WANG Heng, WEI Peng. Anti-strong Jamming Polar Coding Optimization Method with Multiobjective Reinforcement Learning[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4092-4100. doi: 10.11999/JEIT230572

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Anti-strong Jamming Polar Coding Optimization Method with Multiobjective Reinforcement Learning

doi: 10.11999/JEIT230572

Sixty-third Research Institute, National University of Defense Technology, Nanjing 210001, China

Funds: The National Natural Science Foundation of China (62201596), The Research Planning Project of the National University of Defense Technology (ZK22-45)

Received Date: 2023-06-09
Rev Recd Date: 2023-11-03

Available Online: 2023-11-13

Publish Date: 2023-11-28

Abstract

Abstract

In order to improve the reliability and anti-jamming ability of information transmission for the Frequency-Hopping (FH) communication system, a Polar coding construction optimization method is proposed to adapt to the strong-jamming environment, which is based on a novel Polar coded slow FH communication system model. Firstly, the multi-objective reinforcement learning algorithm is designed for the hybrid channel containing normal state and jamming state, and then the information bit-channel sequence in the coding process is optimized. Consequently the error correction performance of the designed Polar codewords is improved. In addition, the complexity of algorithm is reduced by preprocessing the initialization and theoretically calculating the reward values. The simulation results show that the overall error performance of the proposed coding optimization method is better than those of conventional coding construction methods in the hybrid channel containing strong jamming. Compared with the 3rd Generation Partnership Project (3GPP) standard scheme in Fifth-Generation (5G) mobile communication systems, the obtained overall coding gain is up to 0.5 dB. Therefore the high-reliability and anti-jamming performance of Polar coded FH transmission is effectively improved.
- Channel coding,
- Anti-jamming,
- Polar codes,
- Reinforcement learning,
- Reliability performance

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References(18)

References

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