Power Line communication (PLC) is an attractive approach to provide information transfer services for future smart grids. However, since various modulations are adopted, it is a great challenge to add new nodes to collect the data from the devices or sensors in in-home PLC networks. In this paper, we propose an approach to automatically access to the PLC network by identifying the modulation of signals. To improve the correct recognition rate on identification of modulations, we propose a multiple input and multiple output (MIMO) based cooperative modulation identification scheme. After receiving the recognition results from accessing nodes, the central server makes the comprehensive and accurate recognition decision on the modulation of the PLC network. Furthermore, the fourth-order cumulants for multiple users are adopted as the feature for this modulation classifier. With the feature, we propose an improved modulation classification algorithm based on the maximum likelihood. Simulations show that a high detection rate and low false positive rate can be achieved as we employ the cooperative modulation identifying scheme and the improved recognition algorithm.
ASJC Scopus subject areas
- Physics and Astronomy(all)