Narrowband power line communication (NB-PLC) systems are an attractive solution for supporting current and future smart grids. A technology proposed to enhance data rate in NB-PLC is multiple-input multiple-output (MIMO) transmission over multiple power line phases. To achieve reliable communication over MIMO NB-PLC, a key challenge is to take into account and mitigate the effects of temporally and spatially correlated cyclostationary noise. Noise samples in a cycle can be divided into three classes with different distributions, i.e. Gaussian, moderate impulsive, and strong impulsive. However, in this paper we first show that the impulsive classes in their turn can be divided into sub-classes with normal distributions and, after deriving the theoretical capacity, two noise sample sets with such characteristics are used to evaluate achievable information rates: one sample set is the measured noise in laboratory and the other is produced through MIMO frequency-shift (FRESH) filtering. The achievable information rates are attained by means of a spatio-temporal whitening of the portions of the cyclostationary correlated noise samples that belong to the Gaussian sub-classes. The proposed approach can be useful to design the optimal receiver in terms of bit allocation using waterfilling algorithm and to adapt modulation order.

翻译：窄带电力线通信系统是支撑当前及未来智能电网的极具吸引力的解决方案。为提升窄带电力线通信的数据速率，一种被提出的技术是在多个电力线相上进行多输入多输出传输。为实现MIMO NB-PLC的可靠通信，关键挑战在于考虑并抑制具有时间和空间相关性的循环平稳噪声。一个循环周期内的噪声样本可根据分布特性分为三类：高斯噪声、中等脉冲噪声和强脉冲噪声。然而，本文首先证明脉冲噪声类本身可进一步划分为具有正态分布的子类，并在推导理论信道容量后，采用具有此类特征的两组噪声样本评估可达信息速率：一组为实验室实测噪声样本，另一组通过MIMO频移滤波生成。通过对属于高斯子类的循环平稳相关噪声样本进行时空白化处理，可获得可达信息速率。该方法可有效指导基于注水算法的最优接收机比特分配设计，并实现调制阶数的自适应调整。