基于稀疏贝叶斯学习的电力线载波通信接收机设计

Design of transceivers based on sparse Bayesian learning for power line carrier communications

针对多径信道和脉冲噪声对电力线载波通信系统性能影响的问题,提出了一种能有效对抗多径信道和脉冲噪声影响的电力线通信系统接收机设计方案。该方案将时域上的电力线信道参数和脉冲噪声联合视作稀疏向量,然后利用稀疏贝叶斯理论联合估计电力线信道和脉冲噪声,从而在接收端得以去除脉冲噪声及补偿信道增益。仿真结果表明,与传统将信道估计与脉冲噪声抑制单独考虑的传统接收机相比,本文提出的接收机方案在误符号率和误比特率等性能指标上有较好的提升。

Aiming at the problem of the influence of multipath channel and impulse noise on the performance of power line carder communication system, a transceiver scheme for power line communication system was proposed which could effectively combat the influence of multipath channel and impulse noise. Firstly, the power line channel impulse response and the impulsive noise in the time domain were jointly viewed as a sparse vector. Then, the sparse Bayesian learning theory was adopted to estimate the power line channel and impulse noise jointly. The impulse noise was removed and the channel gain was compensated at the receiver. The simulation result shows that the proposed receiver scheme has better performance than traditional receiver considering channel estimation and impulse noise suppression separately.