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具有学习信念传播解码器的端到端DAE-LDPC-OFDM收发器,用于稳固和节能的无线通信
Mohaimen Mohammed1, Mesut Çevik1
1Electrical and Computer Engineering, Altinbas University, 34217 Istanbul, Turkey.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
本研究介绍了一种深度自编码器-LDPC-OFDM系统,配有学习信念传播解码器,用于自适应无线通信. 它在具有挑战性的通道条件下实现了卓越的性能,能源效率和稳定性.
科学领域:
- 无线通信工程 无线通信工程
- 机器学习用于通信.
- 信号处理 信号处理
背景情况:
- 传统的无线系统通常会独立处理编码,调制和解码.
- 现有的系统难以动态适应变化的通道和噪声条件.
- 未来网络需要强大,节能和适应性的通信架构.
研究的目的:
- 提出一个新的深度自编码器-LDPC-OFDM收发器架构.
- 整合一个学习的信念传播解码器,以提高性能.
- 为了实现强大,节能和适应性的无线通信.
主要方法:
- 编码,调制和解码组件的端到端联合优化.
- 集成一个学习的信念传播 (BP) 解码器与可训练的参数.
- 代的消息传递过程,用于对日志概率 (LLR) 统计的自适应性改进.
主要成果:
- 在10dB SNR时,实现了1.72%的比特错误率 (BER) 和2.95%的区块错误率 (BLER).
- 超越了最先进的模型 (变压器-OFDM,CNN-OFDM,GRU-OFDM) 的性能为25-30%.
- 在数据集中,与传统的LDPC-OFDM系统相比,表现出38-42%的优异性能.
- 实现了26.6%的峰值到平均功率比率 (PAPR) 降低和低推理延迟 (3.9毫秒).
结论:
- 拟议的Deep Autoencoder-LDPC-OFDM架构提供了高性能,高功率效率和可扩展性.
- 它提供了卓越的可靠性和低延迟通信,适合6G及以上.
- 该系统在现实的无线环境中表现出稳健性,包括时间变化和多路径色通道.
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