基于信念传播的深度神经网络MIMO检测:DNN-BP

Changqing Zhou, Bo Ma
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引用次数: 1

摘要

本文首先介绍了信念传播(BP)算法和阻尼BP算法的原理。然后,结合BP算法和机器学习,提出了一种基于BP的深度神经网络(DNN-BP)检测算法。DNN-BP算法通过机器学习方法选择最优阻尼因子,解决了传统算法中阻尼因子难以确定的问题。仿真结果表明,DNN-BP检测算法可以进一步改善BP算法的收敛性,提高误码率性能。
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Belief Propagation based Deep Neural Networks for MIMO Detection: DNN-BP
The paper introduces principles of Belief Propagation (BP) algorithm and Damped BP algorithm firstly. Then, with the BP algorithm and machine learning, this paper proposes a detection algorithm based on BP based deep neural networks (DNN-BP). The DNN-BP algorithm selects the optimal damping factor through machine learning methods, which solves the problem that the damping factor is difficult to determine in traditional algorithms. Simulation results show that the DNN-BP detection algorithm can further improve the convergence of the BP algorithm and improve the Bit Error Rate performance.
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